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Adjust cost estimates for distributed queries
To improve remote query push down, do the following: * Import changes to remote cost estimates from PostgreSQL 14 `postgres_fdw`. The cost estimations for distributed (remote) queries are originally based on the `postgres_fdw` code in PG11. However, fixes and changes have been applied in never PostgreSQL versions, which improves, among other things, costing of sorts and having clauses. * Increase the cost of transferring tuples. This penalizes doing grouping/aggregation on the AN since it requires transferring more tuples, leading to the planner preferring the push-down plans. * As a result of the above, the improved costing also makes distributed queries behave similar across all currently supported PostgreSQL versions for our test cases. * Enable `dist_query` tests on PG14 (since it now passes). * Update the `dist_partial_agg` test to use additional ordering columns so that there is no diff in the test output due to ordering of input to the `first` and `last` functions.
This commit is contained in:
Erik Nordström
Erik Nordström
parent
28a5650382
commit
57744c84ce
@ -29,7 +29,7 @@ jobs:
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ignores: append-13 debug_notice transparent_decompression-13 pg_dump
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pg_major: 13
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- pg: "14.0"
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ignores: append-14 chunk_api debug_notice dist_query transparent_decompression-14
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ignores: append-14 chunk_api debug_notice transparent_decompression-14
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pg_major: 14
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steps:
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@ -108,12 +108,7 @@ def macos_config(overrides):
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# always test debug build on latest of all supported pg versions
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m["include"].append(build_debug_config({"pg":PG12_LATEST}))
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m["include"].append(build_debug_config({"pg":PG13_LATEST}))
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pg14_debug_latest = {
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"pg": PG14_LATEST,
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"installcheck_args": "IGNORES='dist_query'"
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}
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m["include"].append(build_debug_config(pg14_debug_latest))
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m["include"].append(build_debug_config({"pg":PG14_LATEST}))
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m["include"].append(build_release_config(macos_config({})))
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@ -9,9 +9,11 @@
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#include <optimizer/clauses.h>
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#include <optimizer/prep.h>
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#include <optimizer/tlist.h>
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#include <optimizer/paths.h>
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#include <utils/selfuncs.h>
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#include <utils/rel.h>
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#include <lib/stringinfo.h>
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#include <miscadmin.h>
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#include <remote/connection.h>
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#include <remote/async.h>
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@ -70,14 +72,13 @@ get_upper_rel_estimate(PlannerInfo *root, RelOptInfo *rel, CostEstimate *ce)
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{
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TsFdwRelInfo *fpinfo = fdw_relinfo_get(rel);
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TsFdwRelInfo *ofpinfo = fdw_relinfo_get(fpinfo->outerrel);
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PathTarget *ptarget = rel->reltarget;
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AggClauseCosts aggcosts;
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double input_rows;
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int num_group_cols;
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double num_groups = 1;
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/* Make sure the core code set the pathtarget. */
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Assert(ptarget != NULL);
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Assert(rel->reltarget != NULL);
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/*
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* This cost model is mixture of costing done for sorted and
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@ -91,25 +92,19 @@ get_upper_rel_estimate(PlannerInfo *root, RelOptInfo *rel, CostEstimate *ce)
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* considering remote and local conditions for costing.
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*/
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/* Get rows and width from input rel */
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/* Get rows from input rel */
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input_rows = ofpinfo->rows;
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ce->width = ofpinfo->width;
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/* Collect statistics about aggregates for estimating costs. */
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MemSet(&aggcosts, 0, sizeof(AggClauseCosts));
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if (root->parse->hasAggs)
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{
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/* Get the aggsplit to use in order to support push-down of partial
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* aggregation */
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AggSplit aggsplit = get_aggsplit(rel);
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get_agg_clause_costs_compat(root, (Node *) fpinfo->grouped_tlist, aggsplit, &aggcosts);
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/*
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* The cost of aggregates in the HAVING qual will be the same
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* for each child as it is for the parent, so there's no need
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* to use a translated version of havingQual.
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*/
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get_agg_clause_costs_compat(root, (Node *) root->parse->havingQual, aggsplit, &aggcosts);
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}
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/* Get number of grouping columns and possible number of groups */
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@ -122,10 +117,28 @@ get_upper_rel_estimate(PlannerInfo *root, RelOptInfo *rel, CostEstimate *ce)
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NULL);
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/*
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* Number of rows expected from data node will be same as
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* that of number of groups.
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* Get the retrieved_rows and rows estimates. If there are HAVING
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* quals, account for their selectivity.
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*/
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ce->rows = ce->retrieved_rows = num_groups;
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if (root->parse->havingQual)
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{
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/* Factor in the selectivity of the remotely-checked quals */
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ce->retrieved_rows = clamp_row_est(
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num_groups * clauselist_selectivity(root, fpinfo->remote_conds, 0, JOIN_INNER, NULL));
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/* Factor in the selectivity of the locally-checked quals */
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ce->rows = clamp_row_est(ce->retrieved_rows * fpinfo->local_conds_sel);
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}
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else
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{
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/*
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* Number of rows expected from data node will be same as
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* that of number of groups.
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*/
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ce->rows = ce->retrieved_rows = num_groups;
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}
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/* Use width estimate made by the core code. */
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ce->width = rel->reltarget->width;
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/*-----
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* Startup cost includes:
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@ -135,26 +148,41 @@ get_upper_rel_estimate(PlannerInfo *root, RelOptInfo *rel, CostEstimate *ce)
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*-----
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*/
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ce->startup_cost = ofpinfo->rel_startup_cost;
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ce->startup_cost += rel->reltarget->cost.startup;
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ce->startup_cost += aggcosts.transCost.startup;
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ce->startup_cost += aggcosts.transCost.per_tuple * input_rows;
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ce->startup_cost += cpu_operator_cost * num_group_cols * input_rows;
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ce->startup_cost += ptarget->cost.startup;
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ce->startup_cost += aggcosts.finalCost.startup;
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ce->startup_cost += (cpu_operator_cost * num_group_cols) * input_rows;
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/*-----
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* Run time cost includes:
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* 1. Run time cost of underneath input relation
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* 1. Run time cost of underneath input relation, adjusted for
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* tlist replacement by apply_scanjoin_target_to_paths()
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* 2. Run time cost of performing aggregation, per cost_agg()
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* 3. PathTarget eval cost for each output row
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*-----
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*/
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ce->run_cost = ofpinfo->rel_total_cost - ofpinfo->rel_startup_cost;
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ce->run_cost += rel->reltarget->cost.per_tuple * input_rows;
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ce->run_cost += aggcosts.finalCost.per_tuple * num_groups;
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ce->run_cost += cpu_tuple_cost * num_groups;
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ce->run_cost += ptarget->cost.per_tuple * num_groups;
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/* Update the relation's number of output rows. Needed on UPPER rels as
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* "cached" value when we compute costs for different pathkeys */
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rel->rows = ce->rows;
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/* Account for the eval cost of HAVING quals, if any */
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if (root->parse->havingQual)
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{
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QualCost remote_cost;
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/* Add in the eval cost of the remotely-checked quals */
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cost_qual_eval(&remote_cost, fpinfo->remote_conds, root);
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ce->startup_cost += remote_cost.startup;
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ce->run_cost += remote_cost.per_tuple * num_groups;
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/* Add in the eval cost of the locally-checked quals */
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ce->startup_cost += fpinfo->local_conds_cost.startup;
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ce->run_cost += fpinfo->local_conds_cost.per_tuple * ce->retrieved_rows;
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}
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/* Add in tlist eval cost for each output row */
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ce->startup_cost += rel->reltarget->cost.startup;
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ce->run_cost += rel->reltarget->cost.per_tuple * ce->rows;
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}
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static void
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@ -162,8 +190,11 @@ get_base_rel_estimate(PlannerInfo *root, RelOptInfo *rel, CostEstimate *ce)
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{
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TsFdwRelInfo *fpinfo = fdw_relinfo_get(rel);
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ce->rows = rel->rows;
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ce->width = rel->reltarget->width;
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/* Back into an estimate of the number of retrieved rows. */
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ce->retrieved_rows = clamp_row_est(rel->rows / fpinfo->local_conds_sel);
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ce->retrieved_rows = clamp_row_est(ce->rows / fpinfo->local_conds_sel);
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/* Clamp retrieved rows estimates to at most rel->tuples. */
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ce->retrieved_rows = Min(ce->retrieved_rows, rel->tuples);
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@ -180,12 +211,64 @@ get_base_rel_estimate(PlannerInfo *root, RelOptInfo *rel, CostEstimate *ce)
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ce->startup_cost += rel->baserestrictcost.startup;
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ce->cpu_per_tuple = cpu_tuple_cost + rel->baserestrictcost.per_tuple;
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ce->run_cost += ce->cpu_per_tuple * rel->tuples;
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/* Add in tlist eval cost for each output row */
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ce->startup_cost += rel->reltarget->cost.startup;
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ce->run_cost += rel->reltarget->cost.per_tuple * ce->rows;
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}
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#define REL_HAS_CACHED_COSTS(fpinfo) \
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((fpinfo)->rel_startup_cost >= 0 && (fpinfo)->rel_total_cost >= 0 && \
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(fpinfo)->rel_retrieved_rows >= 0)
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/*
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* Adjust the cost estimates of a foreign grouping path to include the cost of
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* generating properly-sorted output.
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*/
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static void
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adjust_foreign_grouping_path_cost(PlannerInfo *root, List *pathkeys, double retrieved_rows,
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double width, double limit_tuples, Cost *p_startup_cost,
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Cost *p_run_cost)
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{
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/*
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* If the GROUP BY clause isn't sort-able, the plan chosen by the remote
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* side is unlikely to generate properly-sorted output, so it would need
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* an explicit sort; adjust the given costs with cost_sort(). Likewise,
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* if the GROUP BY clause is sort-able but isn't a superset of the given
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* pathkeys, adjust the costs with that function. Otherwise, adjust the
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* costs by applying the same heuristic as for the scan or join case.
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*/
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if (!grouping_is_sortable(root->parse->groupClause) ||
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!pathkeys_contained_in(pathkeys, root->group_pathkeys))
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{
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Path sort_path; /* dummy for result of cost_sort */
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cost_sort(&sort_path,
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root,
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pathkeys,
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*p_startup_cost + *p_run_cost,
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retrieved_rows,
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width,
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0.0,
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work_mem,
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limit_tuples);
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*p_startup_cost = sort_path.startup_cost;
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*p_run_cost = sort_path.total_cost - sort_path.startup_cost;
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}
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else
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{
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/*
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* The default extra cost seems too large for foreign-grouping cases;
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* add 1/4th of that default.
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*/
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double sort_multiplier = 1.0 + (DEFAULT_FDW_SORT_MULTIPLIER - 1.0) * 0.25;
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*p_startup_cost *= sort_multiplier;
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*p_run_cost *= sort_multiplier;
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}
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}
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/*
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* fdw_estimate_path_cost_size
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* Get cost and size estimates for a foreign scan on given foreign
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@ -225,6 +308,8 @@ fdw_estimate_path_cost_size(PlannerInfo *root, RelOptInfo *rel, List *pathkeys,
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*/
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if (REL_HAS_CACHED_COSTS(fpinfo))
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{
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ce.rows = fpinfo->rows;
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ce.width = fpinfo->width;
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ce.startup_cost = fpinfo->rel_startup_cost;
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ce.run_cost = fpinfo->rel_total_cost - fpinfo->rel_startup_cost;
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ce.retrieved_rows = fpinfo->rel_retrieved_rows;
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@ -245,9 +330,27 @@ fdw_estimate_path_cost_size(PlannerInfo *root, RelOptInfo *rel, List *pathkeys,
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*/
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if (pathkeys != NIL)
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{
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/* TODO: check if sort covered by local index and use other sort multiplier */
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ce.startup_cost *= DEFAULT_FDW_SORT_MULTIPLIER;
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ce.run_cost *= DEFAULT_FDW_SORT_MULTIPLIER;
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if (IS_UPPER_REL(rel))
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{
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Assert(rel->reloptkind == RELOPT_UPPER_REL ||
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rel->reloptkind == RELOPT_OTHER_UPPER_REL);
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/* FIXME: Currently don't have a way to pass on limit here */
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const double limit_tuples = -1;
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adjust_foreign_grouping_path_cost(root,
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pathkeys,
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ce.retrieved_rows,
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ce.width,
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limit_tuples,
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&ce.startup_cost,
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&ce.run_cost);
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}
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else
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{
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ce.startup_cost *= DEFAULT_FDW_SORT_MULTIPLIER;
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ce.run_cost *= DEFAULT_FDW_SORT_MULTIPLIER;
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}
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}
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ce.total_cost = ce.startup_cost + ce.run_cost;
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@ -37,7 +37,10 @@
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#define DEFAULT_FDW_STARTUP_COST 100.0
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/* Default CPU cost to process 1 row (above and beyond cpu_tuple_cost). */
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#define DEFAULT_FDW_TUPLE_COST 0.01
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/* Note that postgres_fdw sets this to 0.01, but we want to penalize
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* transferring many tuples in order to make it more attractive to push down
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* aggregates and thus transfer/process less tuples. */
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#define DEFAULT_FDW_TUPLE_COST 0.08
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#define DEFAULT_FDW_FETCH_SIZE 10000
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@ -187,32 +187,26 @@ WHERE time BETWEEN '2018-04-19 00:01' AND '2018-06-01 00:00'
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GROUP BY 1, 2
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ORDER BY 1, 2;
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DEBUG: Upper rel stage GROUP_AGG:
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RELOPTINFO [rel name: Aggregate on (public.hyper), type: DATA_NODE, kind: OTHER_UPPER_REL, base rel names: hyper] rows=1 width=20
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RELOPTINFO [rel name: Aggregate on (public.hyper), type: DATA_NODE, kind: OTHER_UPPER_REL, base rel names: hyper] rows=0 width=20
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Path list:
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Agg [rel type: DATA_NODE, kind: OTHER_UPPER_REL, parent's base rels: hyper] rows=1 with pathkeys: ((hyper.time, hyper.time, hyper.time, hyper.time, hyper.time, hyper.time, hyper.time, hyper.time), (hyper.device, hyper.device, hyper.device, hyper.device, hyper.device, hyper.device, hyper.device, hyper.device))
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CustomScan (DataNodeScanPath) [rel type: DATA_NODE, kind: OTHER_MEMBER_REL, parent's base rels: hyper] rows=1 with pathkeys: ((hyper.time, hyper.time, hyper.time, hyper.time, hyper.time, hyper.time, hyper.time, hyper.time), (hyper.device, hyper.device, hyper.device, hyper.device, hyper.device, hyper.device, hyper.device, hyper.device))
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CustomScan (DataNodeScanPath) [rel type: DATA_NODE, kind: OTHER_UPPER_REL, parent's base rels: hyper] rows=1 with pathkeys: ((hyper.time, hyper.time, hyper.time, hyper.time, hyper.time, hyper.time, hyper.time, hyper.time), (hyper.device, hyper.device, hyper.device, hyper.device, hyper.device, hyper.device, hyper.device, hyper.device))
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Pruned paths:
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CustomScan (DataNodeScanPath) [rel type: DATA_NODE, kind: OTHER_UPPER_REL, parent's base rels: hyper] rows=1
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CustomScan (DataNodeScanPath) [rel type: DATA_NODE, kind: OTHER_UPPER_REL, parent's base rels: hyper] rows=1 with pathkeys: ((hyper.time, hyper.time, hyper.time, hyper.time, hyper.time, hyper.time, hyper.time, hyper.time), (hyper.device, hyper.device, hyper.device, hyper.device, hyper.device, hyper.device, hyper.device, hyper.device))
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DEBUG: Upper rel stage GROUP_AGG:
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RELOPTINFO [rel name: Aggregate on (public.hyper), type: DATA_NODE, kind: OTHER_UPPER_REL, base rel names: hyper] rows=3 width=20
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RELOPTINFO [rel name: Aggregate on (public.hyper), type: DATA_NODE, kind: OTHER_UPPER_REL, base rel names: hyper] rows=0 width=20
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Path list:
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Agg [rel type: DATA_NODE, kind: OTHER_UPPER_REL, parent's base rels: hyper] rows=3 with pathkeys: ((hyper.time, hyper.time, hyper.time, hyper.time, hyper.time, hyper.time, hyper.time, hyper.time), (hyper.device, hyper.device, hyper.device, hyper.device, hyper.device, hyper.device, hyper.device, hyper.device))
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CustomScan (DataNodeScanPath) [rel type: DATA_NODE, kind: OTHER_MEMBER_REL, parent's base rels: hyper] rows=3 with pathkeys: ((hyper.time, hyper.time, hyper.time, hyper.time, hyper.time, hyper.time, hyper.time, hyper.time), (hyper.device, hyper.device, hyper.device, hyper.device, hyper.device, hyper.device, hyper.device, hyper.device))
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CustomScan (DataNodeScanPath) [rel type: DATA_NODE, kind: OTHER_UPPER_REL, parent's base rels: hyper] rows=3 with pathkeys: ((hyper.time, hyper.time, hyper.time, hyper.time, hyper.time, hyper.time, hyper.time, hyper.time), (hyper.device, hyper.device, hyper.device, hyper.device, hyper.device, hyper.device, hyper.device, hyper.device))
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Pruned paths:
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CustomScan (DataNodeScanPath) [rel type: DATA_NODE, kind: OTHER_UPPER_REL, parent's base rels: hyper] rows=3
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CustomScan (DataNodeScanPath) [rel type: DATA_NODE, kind: OTHER_UPPER_REL, parent's base rels: hyper] rows=3 with pathkeys: ((hyper.time, hyper.time, hyper.time, hyper.time, hyper.time, hyper.time, hyper.time, hyper.time), (hyper.device, hyper.device, hyper.device, hyper.device, hyper.device, hyper.device, hyper.device, hyper.device))
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DEBUG: Upper rel stage GROUP_AGG:
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RELOPTINFO [rel name: Aggregate on (public.hyper), type: DATA_NODE, kind: OTHER_UPPER_REL, base rel names: hyper] rows=1 width=20
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RELOPTINFO [rel name: Aggregate on (public.hyper), type: DATA_NODE, kind: OTHER_UPPER_REL, base rel names: hyper] rows=0 width=20
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Path list:
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Agg [rel type: DATA_NODE, kind: OTHER_UPPER_REL, parent's base rels: hyper] rows=1 with pathkeys: ((hyper.time, hyper.time, hyper.time, hyper.time, hyper.time, hyper.time, hyper.time, hyper.time), (hyper.device, hyper.device, hyper.device, hyper.device, hyper.device, hyper.device, hyper.device, hyper.device))
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CustomScan (DataNodeScanPath) [rel type: DATA_NODE, kind: OTHER_MEMBER_REL, parent's base rels: hyper] rows=1 with pathkeys: ((hyper.time, hyper.time, hyper.time, hyper.time, hyper.time, hyper.time, hyper.time, hyper.time), (hyper.device, hyper.device, hyper.device, hyper.device, hyper.device, hyper.device, hyper.device, hyper.device))
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CustomScan (DataNodeScanPath) [rel type: DATA_NODE, kind: OTHER_UPPER_REL, parent's base rels: hyper] rows=1 with pathkeys: ((hyper.time, hyper.time, hyper.time, hyper.time, hyper.time, hyper.time, hyper.time, hyper.time), (hyper.device, hyper.device, hyper.device, hyper.device, hyper.device, hyper.device, hyper.device, hyper.device))
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Pruned paths:
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CustomScan (DataNodeScanPath) [rel type: DATA_NODE, kind: OTHER_UPPER_REL, parent's base rels: hyper] rows=1
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CustomScan (DataNodeScanPath) [rel type: DATA_NODE, kind: OTHER_UPPER_REL, parent's base rels: hyper] rows=1 with pathkeys: ((hyper.time, hyper.time, hyper.time, hyper.time, hyper.time, hyper.time, hyper.time, hyper.time), (hyper.device, hyper.device, hyper.device, hyper.device, hyper.device, hyper.device, hyper.device, hyper.device))
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@ -3573,13 +3573,13 @@ SELECT *
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FROM hyper_estimate;
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QUERY PLAN
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---------------------------------------------------------------------------------------------
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Append (cost=100.00..166847.40 rows=4118040 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_38_chunk (cost=100.00..32468.60 rows=915120 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_39_chunk (cost=100.00..32468.60 rows=915120 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_40_chunk (cost=100.00..32468.60 rows=915120 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_41_chunk (cost=100.00..16283.80 rows=457560 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_42_chunk (cost=100.00..16283.80 rows=457560 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_43_chunk (cost=100.00..16283.80 rows=457560 width=20)
|
||||
Append (cost=100.00..455110.20 rows=4118040 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_38_chunk (cost=100.00..96527.00 rows=915120 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_39_chunk (cost=100.00..96527.00 rows=915120 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_40_chunk (cost=100.00..96527.00 rows=915120 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_41_chunk (cost=100.00..48313.00 rows=457560 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_42_chunk (cost=100.00..48313.00 rows=457560 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_43_chunk (cost=100.00..48313.00 rows=457560 width=20)
|
||||
(7 rows)
|
||||
|
||||
-- This will calculate the stats
|
||||
@ -3589,13 +3589,13 @@ SELECT *
|
||||
FROM hyper_estimate;
|
||||
QUERY PLAN
|
||||
--------------------------------------------------------------------------------------
|
||||
Append (cost=100.00..606.52 rows=15 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_38_chunk (cost=100.00..101.12 rows=4 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_39_chunk (cost=100.00..101.06 rows=2 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_40_chunk (cost=100.00..101.09 rows=3 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_41_chunk (cost=100.00..101.06 rows=2 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_42_chunk (cost=100.00..101.09 rows=3 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_43_chunk (cost=100.00..101.03 rows=1 width=20)
|
||||
Append (cost=100.00..607.58 rows=15 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_38_chunk (cost=100.00..101.40 rows=4 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_39_chunk (cost=100.00..101.20 rows=2 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_40_chunk (cost=100.00..101.30 rows=3 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_41_chunk (cost=100.00..101.20 rows=2 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_42_chunk (cost=100.00..101.30 rows=3 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_43_chunk (cost=100.00..101.10 rows=1 width=20)
|
||||
(7 rows)
|
||||
|
||||
-- Let's insert data into a new chunk. This will result in chunk creation.
|
||||
@ -3606,14 +3606,14 @@ SELECT *
|
||||
FROM hyper_estimate;
|
||||
QUERY PLAN
|
||||
--------------------------------------------------------------------------------------
|
||||
Append (cost=100.00..706.58 rows=17 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_38_chunk (cost=100.00..101.12 rows=4 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_39_chunk (cost=100.00..101.06 rows=2 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_40_chunk (cost=100.00..101.09 rows=3 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_41_chunk (cost=100.00..101.06 rows=2 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_42_chunk (cost=100.00..101.09 rows=3 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_43_chunk (cost=100.00..101.03 rows=1 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_44_chunk (cost=100.00..100.05 rows=2 width=20)
|
||||
Append (cost=100.00..707.74 rows=17 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_38_chunk (cost=100.00..101.40 rows=4 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_39_chunk (cost=100.00..101.20 rows=2 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_40_chunk (cost=100.00..101.30 rows=3 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_41_chunk (cost=100.00..101.20 rows=2 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_42_chunk (cost=100.00..101.30 rows=3 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_43_chunk (cost=100.00..101.10 rows=1 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_44_chunk (cost=100.00..100.15 rows=2 width=20)
|
||||
(8 rows)
|
||||
|
||||
CREATE TABLE devices (
|
||||
|
||||
@ -3572,13 +3572,13 @@ SELECT *
|
||||
FROM hyper_estimate;
|
||||
QUERY PLAN
|
||||
---------------------------------------------------------------------------------------------
|
||||
Append (cost=100.00..166847.40 rows=4118040 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_38_chunk (cost=100.00..32468.60 rows=915120 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_39_chunk (cost=100.00..32468.60 rows=915120 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_40_chunk (cost=100.00..32468.60 rows=915120 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_41_chunk (cost=100.00..16283.80 rows=457560 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_42_chunk (cost=100.00..16283.80 rows=457560 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_43_chunk (cost=100.00..16283.80 rows=457560 width=20)
|
||||
Append (cost=100.00..455110.20 rows=4118040 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_38_chunk (cost=100.00..96527.00 rows=915120 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_39_chunk (cost=100.00..96527.00 rows=915120 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_40_chunk (cost=100.00..96527.00 rows=915120 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_41_chunk (cost=100.00..48313.00 rows=457560 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_42_chunk (cost=100.00..48313.00 rows=457560 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_43_chunk (cost=100.00..48313.00 rows=457560 width=20)
|
||||
(7 rows)
|
||||
|
||||
-- This will calculate the stats
|
||||
@ -3588,13 +3588,13 @@ SELECT *
|
||||
FROM hyper_estimate;
|
||||
QUERY PLAN
|
||||
--------------------------------------------------------------------------------------
|
||||
Append (cost=100.00..606.52 rows=15 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_38_chunk (cost=100.00..101.12 rows=4 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_39_chunk (cost=100.00..101.06 rows=2 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_40_chunk (cost=100.00..101.09 rows=3 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_41_chunk (cost=100.00..101.06 rows=2 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_42_chunk (cost=100.00..101.09 rows=3 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_43_chunk (cost=100.00..101.03 rows=1 width=20)
|
||||
Append (cost=100.00..607.58 rows=15 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_38_chunk (cost=100.00..101.40 rows=4 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_39_chunk (cost=100.00..101.20 rows=2 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_40_chunk (cost=100.00..101.30 rows=3 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_41_chunk (cost=100.00..101.20 rows=2 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_42_chunk (cost=100.00..101.30 rows=3 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_43_chunk (cost=100.00..101.10 rows=1 width=20)
|
||||
(7 rows)
|
||||
|
||||
-- Let's insert data into a new chunk. This will result in chunk creation.
|
||||
@ -3605,14 +3605,14 @@ SELECT *
|
||||
FROM hyper_estimate;
|
||||
QUERY PLAN
|
||||
--------------------------------------------------------------------------------------
|
||||
Append (cost=100.00..706.58 rows=17 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_38_chunk (cost=100.00..101.12 rows=4 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_39_chunk (cost=100.00..101.06 rows=2 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_40_chunk (cost=100.00..101.09 rows=3 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_41_chunk (cost=100.00..101.06 rows=2 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_42_chunk (cost=100.00..101.09 rows=3 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_43_chunk (cost=100.00..101.03 rows=1 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_44_chunk (cost=100.00..100.05 rows=2 width=20)
|
||||
Append (cost=100.00..707.74 rows=17 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_38_chunk (cost=100.00..101.40 rows=4 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_39_chunk (cost=100.00..101.20 rows=2 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_40_chunk (cost=100.00..101.30 rows=3 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_41_chunk (cost=100.00..101.20 rows=2 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_42_chunk (cost=100.00..101.30 rows=3 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_43_chunk (cost=100.00..101.10 rows=1 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_44_chunk (cost=100.00..100.15 rows=2 width=20)
|
||||
(8 rows)
|
||||
|
||||
CREATE TABLE devices (
|
||||
|
||||
@ -3575,13 +3575,13 @@ SELECT *
|
||||
FROM hyper_estimate;
|
||||
QUERY PLAN
|
||||
---------------------------------------------------------------------------------------------
|
||||
Append (cost=100.00..166847.40 rows=4118040 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_38_chunk (cost=100.00..32468.60 rows=915120 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_39_chunk (cost=100.00..32468.60 rows=915120 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_40_chunk (cost=100.00..32468.60 rows=915120 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_41_chunk (cost=100.00..16283.80 rows=457560 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_42_chunk (cost=100.00..16283.80 rows=457560 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_43_chunk (cost=100.00..16283.80 rows=457560 width=20)
|
||||
Append (cost=100.00..455110.20 rows=4118040 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_38_chunk (cost=100.00..96527.00 rows=915120 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_39_chunk (cost=100.00..96527.00 rows=915120 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_40_chunk (cost=100.00..96527.00 rows=915120 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_41_chunk (cost=100.00..48313.00 rows=457560 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_42_chunk (cost=100.00..48313.00 rows=457560 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_43_chunk (cost=100.00..48313.00 rows=457560 width=20)
|
||||
(7 rows)
|
||||
|
||||
-- This will calculate the stats
|
||||
@ -3591,13 +3591,13 @@ SELECT *
|
||||
FROM hyper_estimate;
|
||||
QUERY PLAN
|
||||
--------------------------------------------------------------------------------------
|
||||
Append (cost=100.00..606.52 rows=15 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_38_chunk (cost=100.00..101.12 rows=4 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_39_chunk (cost=100.00..101.06 rows=2 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_40_chunk (cost=100.00..101.09 rows=3 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_41_chunk (cost=100.00..101.06 rows=2 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_42_chunk (cost=100.00..101.09 rows=3 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_43_chunk (cost=100.00..101.03 rows=1 width=20)
|
||||
Append (cost=100.00..607.58 rows=15 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_38_chunk (cost=100.00..101.40 rows=4 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_39_chunk (cost=100.00..101.20 rows=2 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_40_chunk (cost=100.00..101.30 rows=3 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_41_chunk (cost=100.00..101.20 rows=2 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_42_chunk (cost=100.00..101.30 rows=3 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_43_chunk (cost=100.00..101.10 rows=1 width=20)
|
||||
(7 rows)
|
||||
|
||||
-- Let's insert data into a new chunk. This will result in chunk creation.
|
||||
@ -3608,14 +3608,14 @@ SELECT *
|
||||
FROM hyper_estimate;
|
||||
QUERY PLAN
|
||||
--------------------------------------------------------------------------------------
|
||||
Append (cost=100.00..706.58 rows=17 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_38_chunk (cost=100.00..101.12 rows=4 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_39_chunk (cost=100.00..101.06 rows=2 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_40_chunk (cost=100.00..101.09 rows=3 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_41_chunk (cost=100.00..101.06 rows=2 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_42_chunk (cost=100.00..101.09 rows=3 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_43_chunk (cost=100.00..101.03 rows=1 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_44_chunk (cost=100.00..100.05 rows=2 width=20)
|
||||
Append (cost=100.00..707.74 rows=17 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_38_chunk (cost=100.00..101.40 rows=4 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_39_chunk (cost=100.00..101.20 rows=2 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_40_chunk (cost=100.00..101.30 rows=3 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_41_chunk (cost=100.00..101.20 rows=2 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_42_chunk (cost=100.00..101.30 rows=3 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_43_chunk (cost=100.00..101.10 rows=1 width=20)
|
||||
-> Foreign Scan on _dist_hyper_16_44_chunk (cost=100.00..100.15 rows=2 width=20)
|
||||
(8 rows)
|
||||
|
||||
CREATE TABLE devices (
|
||||
|
||||
@ -165,76 +165,70 @@ SET enable_partitionwise_aggregate = ON;
|
||||
last(temperature, timec) as last_temp,
|
||||
histogram(temperature, 0, 100, 1)
|
||||
FROM :TEST_TABLE
|
||||
GROUP BY :GROUPING
|
||||
ORDER BY :GROUPING;
|
||||
QUERY PLAN
|
||||
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Sort
|
||||
Output: location, (min(allnull)), (max(temperature)), ((sum(temperature) + sum(humidity))), (avg(humidity)), (round(stddev((humidity)::integer), 5)), (bit_and(bit_int)), (bit_or(bit_int)), (bool_and(good_life)), (every((temperature > '0'::double precision))), (bool_or(good_life)), (count(*)), (count(temperature)), (count(allnull)), (round((corr(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((covar_pop(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((covar_samp(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_avgx(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_avgy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_count(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_intercept(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_r2(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_slope(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_sxx(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_sxy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_syy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round(stddev((temperature)::integer), 5)), (round(stddev_pop((temperature)::integer), 5)), (round(stddev_samp((temperature)::integer), 5)), (round(variance((temperature)::integer), 5)), (round(var_pop((temperature)::integer), 5)), (round(var_samp((temperature)::integer), 5)), (last(temperature, timec)), (histogram(temperature, '0'::double precision, '100'::double precision, 1))
|
||||
Sort Key: location
|
||||
-> Custom Scan (AsyncAppend)
|
||||
Output: location, (min(allnull)), (max(temperature)), ((sum(temperature) + sum(humidity))), (avg(humidity)), (round(stddev((humidity)::integer), 5)), (bit_and(bit_int)), (bit_or(bit_int)), (bool_and(good_life)), (every((temperature > '0'::double precision))), (bool_or(good_life)), (count(*)), (count(temperature)), (count(allnull)), (round((corr(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((covar_pop(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((covar_samp(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_avgx(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_avgy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_count(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_intercept(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_r2(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_slope(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_sxx(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_sxy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_syy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round(stddev((temperature)::integer), 5)), (round(stddev_pop((temperature)::integer), 5)), (round(stddev_samp((temperature)::integer), 5)), (round(variance((temperature)::integer), 5)), (round(var_pop((temperature)::integer), 5)), (round(var_samp((temperature)::integer), 5)), (last(temperature, timec)), (histogram(temperature, '0'::double precision, '100'::double precision, 1))
|
||||
-> Append
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: conditions.location, (min(conditions.allnull)), (max(conditions.temperature)), ((sum(conditions.temperature) + sum(conditions.humidity))), (avg(conditions.humidity)), (round(stddev((conditions.humidity)::integer), 5)), (bit_and(conditions.bit_int)), (bit_or(conditions.bit_int)), (bool_and(conditions.good_life)), (every((conditions.temperature > '0'::double precision))), (bool_or(conditions.good_life)), (count(*)), (count(conditions.temperature)), (count(conditions.allnull)), (round((corr(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((covar_pop(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((covar_samp(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((regr_avgx(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((regr_avgy(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((regr_count(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((regr_intercept(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((regr_r2(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((regr_slope(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((regr_sxx(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((regr_sxy(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((regr_syy(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round(stddev((conditions.temperature)::integer), 5)), (round(stddev_pop((conditions.temperature)::integer), 5)), (round(stddev_samp((conditions.temperature)::integer), 5)), (round(variance((conditions.temperature)::integer), 5)), (round(var_pop((conditions.temperature)::integer), 5)), (round(var_samp((conditions.temperature)::integer), 5)), (last(conditions.temperature, conditions.timec)), (histogram(conditions.temperature, '0'::double precision, '100'::double precision, 1))
|
||||
Relations: Aggregate on (public.conditions)
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_1_chunk, _dist_hyper_1_2_chunk, _dist_hyper_1_3_chunk, _dist_hyper_1_4_chunk
|
||||
Remote SQL: SELECT location, min(allnull), max(temperature), (sum(temperature) + sum(humidity)), avg(humidity), round(stddev(humidity::integer), 5), bit_and(bit_int), bit_or(bit_int), bool_and(good_life), every((temperature > 0::double precision)), bool_or(good_life), count(*), count(temperature), count(allnull), round(corr(temperature::integer, humidity::integer)::numeric, 5), round(covar_pop(temperature::integer, humidity::integer)::numeric, 5), round(covar_samp(temperature::integer, humidity::integer)::numeric, 5), round(regr_avgx(temperature::integer, humidity::integer)::numeric, 5), round(regr_avgy(temperature::integer, humidity::integer)::numeric, 5), round(regr_count(temperature::integer, humidity::integer)::numeric, 5), round(regr_intercept(temperature::integer, humidity::integer)::numeric, 5), round(regr_r2(temperature::integer, humidity::integer)::numeric, 5), round(regr_slope(temperature::integer, humidity::integer)::numeric, 5), round(regr_sxx(temperature::integer, humidity::integer)::numeric, 5), round(regr_sxy(temperature::integer, humidity::integer)::numeric, 5), round(regr_syy(temperature::integer, humidity::integer)::numeric, 5), round(stddev(temperature::integer), 5), round(stddev_pop(temperature::integer), 5), round(stddev_samp(temperature::integer), 5), round(variance(temperature::integer), 5), round(var_pop(temperature::integer), 5), round(var_samp(temperature::integer), 5), public.last(temperature, timec), public.histogram(temperature, 0::double precision, 100::double precision, 1) FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) GROUP BY 1
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: conditions_1.location, (min(conditions_1.allnull)), (max(conditions_1.temperature)), ((sum(conditions_1.temperature) + sum(conditions_1.humidity))), (avg(conditions_1.humidity)), (round(stddev((conditions_1.humidity)::integer), 5)), (bit_and(conditions_1.bit_int)), (bit_or(conditions_1.bit_int)), (bool_and(conditions_1.good_life)), (every((conditions_1.temperature > '0'::double precision))), (bool_or(conditions_1.good_life)), (count(*)), (count(conditions_1.temperature)), (count(conditions_1.allnull)), (round((corr(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((covar_pop(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((covar_samp(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((regr_avgx(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((regr_avgy(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((regr_count(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((regr_intercept(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((regr_r2(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((regr_slope(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((regr_sxx(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((regr_sxy(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((regr_syy(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round(stddev((conditions_1.temperature)::integer), 5)), (round(stddev_pop((conditions_1.temperature)::integer), 5)), (round(stddev_samp((conditions_1.temperature)::integer), 5)), (round(variance((conditions_1.temperature)::integer), 5)), (round(var_pop((conditions_1.temperature)::integer), 5)), (round(var_samp((conditions_1.temperature)::integer), 5)), (last(conditions_1.temperature, conditions_1.timec)), (histogram(conditions_1.temperature, '0'::double precision, '100'::double precision, 1))
|
||||
Relations: Aggregate on (public.conditions)
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_9_chunk, _dist_hyper_1_10_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_12_chunk
|
||||
Remote SQL: SELECT location, min(allnull), max(temperature), (sum(temperature) + sum(humidity)), avg(humidity), round(stddev(humidity::integer), 5), bit_and(bit_int), bit_or(bit_int), bool_and(good_life), every((temperature > 0::double precision)), bool_or(good_life), count(*), count(temperature), count(allnull), round(corr(temperature::integer, humidity::integer)::numeric, 5), round(covar_pop(temperature::integer, humidity::integer)::numeric, 5), round(covar_samp(temperature::integer, humidity::integer)::numeric, 5), round(regr_avgx(temperature::integer, humidity::integer)::numeric, 5), round(regr_avgy(temperature::integer, humidity::integer)::numeric, 5), round(regr_count(temperature::integer, humidity::integer)::numeric, 5), round(regr_intercept(temperature::integer, humidity::integer)::numeric, 5), round(regr_r2(temperature::integer, humidity::integer)::numeric, 5), round(regr_slope(temperature::integer, humidity::integer)::numeric, 5), round(regr_sxx(temperature::integer, humidity::integer)::numeric, 5), round(regr_sxy(temperature::integer, humidity::integer)::numeric, 5), round(regr_syy(temperature::integer, humidity::integer)::numeric, 5), round(stddev(temperature::integer), 5), round(stddev_pop(temperature::integer), 5), round(stddev_samp(temperature::integer), 5), round(variance(temperature::integer), 5), round(var_pop(temperature::integer), 5), round(var_samp(temperature::integer), 5), public.last(temperature, timec), public.histogram(temperature, 0::double precision, 100::double precision, 1) FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) GROUP BY 1
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: conditions_2.location, (min(conditions_2.allnull)), (max(conditions_2.temperature)), ((sum(conditions_2.temperature) + sum(conditions_2.humidity))), (avg(conditions_2.humidity)), (round(stddev((conditions_2.humidity)::integer), 5)), (bit_and(conditions_2.bit_int)), (bit_or(conditions_2.bit_int)), (bool_and(conditions_2.good_life)), (every((conditions_2.temperature > '0'::double precision))), (bool_or(conditions_2.good_life)), (count(*)), (count(conditions_2.temperature)), (count(conditions_2.allnull)), (round((corr(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((covar_pop(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((covar_samp(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((regr_avgx(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((regr_avgy(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((regr_count(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((regr_intercept(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((regr_r2(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((regr_slope(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((regr_sxx(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((regr_sxy(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((regr_syy(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round(stddev((conditions_2.temperature)::integer), 5)), (round(stddev_pop((conditions_2.temperature)::integer), 5)), (round(stddev_samp((conditions_2.temperature)::integer), 5)), (round(variance((conditions_2.temperature)::integer), 5)), (round(var_pop((conditions_2.temperature)::integer), 5)), (round(var_samp((conditions_2.temperature)::integer), 5)), (last(conditions_2.temperature, conditions_2.timec)), (histogram(conditions_2.temperature, '0'::double precision, '100'::double precision, 1))
|
||||
Relations: Aggregate on (public.conditions)
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_5_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_7_chunk, _dist_hyper_1_8_chunk
|
||||
Remote SQL: SELECT location, min(allnull), max(temperature), (sum(temperature) + sum(humidity)), avg(humidity), round(stddev(humidity::integer), 5), bit_and(bit_int), bit_or(bit_int), bool_and(good_life), every((temperature > 0::double precision)), bool_or(good_life), count(*), count(temperature), count(allnull), round(corr(temperature::integer, humidity::integer)::numeric, 5), round(covar_pop(temperature::integer, humidity::integer)::numeric, 5), round(covar_samp(temperature::integer, humidity::integer)::numeric, 5), round(regr_avgx(temperature::integer, humidity::integer)::numeric, 5), round(regr_avgy(temperature::integer, humidity::integer)::numeric, 5), round(regr_count(temperature::integer, humidity::integer)::numeric, 5), round(regr_intercept(temperature::integer, humidity::integer)::numeric, 5), round(regr_r2(temperature::integer, humidity::integer)::numeric, 5), round(regr_slope(temperature::integer, humidity::integer)::numeric, 5), round(regr_sxx(temperature::integer, humidity::integer)::numeric, 5), round(regr_sxy(temperature::integer, humidity::integer)::numeric, 5), round(regr_syy(temperature::integer, humidity::integer)::numeric, 5), round(stddev(temperature::integer), 5), round(stddev_pop(temperature::integer), 5), round(stddev_samp(temperature::integer), 5), round(variance(temperature::integer), 5), round(var_pop(temperature::integer), 5), round(var_samp(temperature::integer), 5), public.last(temperature, timec), public.histogram(temperature, 0::double precision, 100::double precision, 1) FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) GROUP BY 1
|
||||
(24 rows)
|
||||
GROUP BY :GROUPING, timec
|
||||
ORDER BY :GROUPING, timec;
|
||||
QUERY PLAN
|
||||
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Custom Scan (AsyncAppend)
|
||||
Output: location, (min(allnull)), (max(temperature)), ((sum(temperature) + sum(humidity))), (avg(humidity)), (round(stddev((humidity)::integer), 5)), (bit_and(bit_int)), (bit_or(bit_int)), (bool_and(good_life)), (every((temperature > '0'::double precision))), (bool_or(good_life)), (count(*)), (count(temperature)), (count(allnull)), (round((corr(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((covar_pop(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((covar_samp(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_avgx(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_avgy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_count(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_intercept(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_r2(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_slope(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_sxx(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_sxy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_syy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round(stddev((temperature)::integer), 5)), (round(stddev_pop((temperature)::integer), 5)), (round(stddev_samp((temperature)::integer), 5)), (round(variance((temperature)::integer), 5)), (round(var_pop((temperature)::integer), 5)), (round(var_samp((temperature)::integer), 5)), (last(temperature, timec)), (histogram(temperature, '0'::double precision, '100'::double precision, 1)), timec
|
||||
-> Merge Append
|
||||
Sort Key: conditions.location, conditions.timec
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: conditions.location, (min(conditions.allnull)), (max(conditions.temperature)), ((sum(conditions.temperature) + sum(conditions.humidity))), (avg(conditions.humidity)), (round(stddev((conditions.humidity)::integer), 5)), (bit_and(conditions.bit_int)), (bit_or(conditions.bit_int)), (bool_and(conditions.good_life)), (every((conditions.temperature > '0'::double precision))), (bool_or(conditions.good_life)), (count(*)), (count(conditions.temperature)), (count(conditions.allnull)), (round((corr(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((covar_pop(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((covar_samp(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((regr_avgx(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((regr_avgy(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((regr_count(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((regr_intercept(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((regr_r2(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((regr_slope(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((regr_sxx(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((regr_sxy(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((regr_syy(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round(stddev((conditions.temperature)::integer), 5)), (round(stddev_pop((conditions.temperature)::integer), 5)), (round(stddev_samp((conditions.temperature)::integer), 5)), (round(variance((conditions.temperature)::integer), 5)), (round(var_pop((conditions.temperature)::integer), 5)), (round(var_samp((conditions.temperature)::integer), 5)), (last(conditions.temperature, conditions.timec)), (histogram(conditions.temperature, '0'::double precision, '100'::double precision, 1)), conditions.timec
|
||||
Relations: Aggregate on (public.conditions)
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_1_chunk, _dist_hyper_1_2_chunk, _dist_hyper_1_3_chunk, _dist_hyper_1_4_chunk
|
||||
Remote SQL: SELECT location, min(allnull), max(temperature), (sum(temperature) + sum(humidity)), avg(humidity), round(stddev(humidity::integer), 5), bit_and(bit_int), bit_or(bit_int), bool_and(good_life), every((temperature > 0::double precision)), bool_or(good_life), count(*), count(temperature), count(allnull), round(corr(temperature::integer, humidity::integer)::numeric, 5), round(covar_pop(temperature::integer, humidity::integer)::numeric, 5), round(covar_samp(temperature::integer, humidity::integer)::numeric, 5), round(regr_avgx(temperature::integer, humidity::integer)::numeric, 5), round(regr_avgy(temperature::integer, humidity::integer)::numeric, 5), round(regr_count(temperature::integer, humidity::integer)::numeric, 5), round(regr_intercept(temperature::integer, humidity::integer)::numeric, 5), round(regr_r2(temperature::integer, humidity::integer)::numeric, 5), round(regr_slope(temperature::integer, humidity::integer)::numeric, 5), round(regr_sxx(temperature::integer, humidity::integer)::numeric, 5), round(regr_sxy(temperature::integer, humidity::integer)::numeric, 5), round(regr_syy(temperature::integer, humidity::integer)::numeric, 5), round(stddev(temperature::integer), 5), round(stddev_pop(temperature::integer), 5), round(stddev_samp(temperature::integer), 5), round(variance(temperature::integer), 5), round(var_pop(temperature::integer), 5), round(var_samp(temperature::integer), 5), public.last(temperature, timec), public.histogram(temperature, 0::double precision, 100::double precision, 1), timec FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) GROUP BY 1, 35 ORDER BY location ASC NULLS LAST, timec ASC NULLS LAST
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: conditions_1.location, (min(conditions_1.allnull)), (max(conditions_1.temperature)), ((sum(conditions_1.temperature) + sum(conditions_1.humidity))), (avg(conditions_1.humidity)), (round(stddev((conditions_1.humidity)::integer), 5)), (bit_and(conditions_1.bit_int)), (bit_or(conditions_1.bit_int)), (bool_and(conditions_1.good_life)), (every((conditions_1.temperature > '0'::double precision))), (bool_or(conditions_1.good_life)), (count(*)), (count(conditions_1.temperature)), (count(conditions_1.allnull)), (round((corr(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((covar_pop(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((covar_samp(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((regr_avgx(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((regr_avgy(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((regr_count(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((regr_intercept(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((regr_r2(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((regr_slope(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((regr_sxx(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((regr_sxy(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((regr_syy(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round(stddev((conditions_1.temperature)::integer), 5)), (round(stddev_pop((conditions_1.temperature)::integer), 5)), (round(stddev_samp((conditions_1.temperature)::integer), 5)), (round(variance((conditions_1.temperature)::integer), 5)), (round(var_pop((conditions_1.temperature)::integer), 5)), (round(var_samp((conditions_1.temperature)::integer), 5)), (last(conditions_1.temperature, conditions_1.timec)), (histogram(conditions_1.temperature, '0'::double precision, '100'::double precision, 1)), conditions_1.timec
|
||||
Relations: Aggregate on (public.conditions)
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_9_chunk, _dist_hyper_1_10_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_12_chunk
|
||||
Remote SQL: SELECT location, min(allnull), max(temperature), (sum(temperature) + sum(humidity)), avg(humidity), round(stddev(humidity::integer), 5), bit_and(bit_int), bit_or(bit_int), bool_and(good_life), every((temperature > 0::double precision)), bool_or(good_life), count(*), count(temperature), count(allnull), round(corr(temperature::integer, humidity::integer)::numeric, 5), round(covar_pop(temperature::integer, humidity::integer)::numeric, 5), round(covar_samp(temperature::integer, humidity::integer)::numeric, 5), round(regr_avgx(temperature::integer, humidity::integer)::numeric, 5), round(regr_avgy(temperature::integer, humidity::integer)::numeric, 5), round(regr_count(temperature::integer, humidity::integer)::numeric, 5), round(regr_intercept(temperature::integer, humidity::integer)::numeric, 5), round(regr_r2(temperature::integer, humidity::integer)::numeric, 5), round(regr_slope(temperature::integer, humidity::integer)::numeric, 5), round(regr_sxx(temperature::integer, humidity::integer)::numeric, 5), round(regr_sxy(temperature::integer, humidity::integer)::numeric, 5), round(regr_syy(temperature::integer, humidity::integer)::numeric, 5), round(stddev(temperature::integer), 5), round(stddev_pop(temperature::integer), 5), round(stddev_samp(temperature::integer), 5), round(variance(temperature::integer), 5), round(var_pop(temperature::integer), 5), round(var_samp(temperature::integer), 5), public.last(temperature, timec), public.histogram(temperature, 0::double precision, 100::double precision, 1), timec FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) GROUP BY 1, 35 ORDER BY location ASC NULLS LAST, timec ASC NULLS LAST
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: conditions_2.location, (min(conditions_2.allnull)), (max(conditions_2.temperature)), ((sum(conditions_2.temperature) + sum(conditions_2.humidity))), (avg(conditions_2.humidity)), (round(stddev((conditions_2.humidity)::integer), 5)), (bit_and(conditions_2.bit_int)), (bit_or(conditions_2.bit_int)), (bool_and(conditions_2.good_life)), (every((conditions_2.temperature > '0'::double precision))), (bool_or(conditions_2.good_life)), (count(*)), (count(conditions_2.temperature)), (count(conditions_2.allnull)), (round((corr(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((covar_pop(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((covar_samp(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((regr_avgx(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((regr_avgy(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((regr_count(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((regr_intercept(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((regr_r2(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((regr_slope(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((regr_sxx(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((regr_sxy(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((regr_syy(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round(stddev((conditions_2.temperature)::integer), 5)), (round(stddev_pop((conditions_2.temperature)::integer), 5)), (round(stddev_samp((conditions_2.temperature)::integer), 5)), (round(variance((conditions_2.temperature)::integer), 5)), (round(var_pop((conditions_2.temperature)::integer), 5)), (round(var_samp((conditions_2.temperature)::integer), 5)), (last(conditions_2.temperature, conditions_2.timec)), (histogram(conditions_2.temperature, '0'::double precision, '100'::double precision, 1)), conditions_2.timec
|
||||
Relations: Aggregate on (public.conditions)
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_5_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_7_chunk, _dist_hyper_1_8_chunk
|
||||
Remote SQL: SELECT location, min(allnull), max(temperature), (sum(temperature) + sum(humidity)), avg(humidity), round(stddev(humidity::integer), 5), bit_and(bit_int), bit_or(bit_int), bool_and(good_life), every((temperature > 0::double precision)), bool_or(good_life), count(*), count(temperature), count(allnull), round(corr(temperature::integer, humidity::integer)::numeric, 5), round(covar_pop(temperature::integer, humidity::integer)::numeric, 5), round(covar_samp(temperature::integer, humidity::integer)::numeric, 5), round(regr_avgx(temperature::integer, humidity::integer)::numeric, 5), round(regr_avgy(temperature::integer, humidity::integer)::numeric, 5), round(regr_count(temperature::integer, humidity::integer)::numeric, 5), round(regr_intercept(temperature::integer, humidity::integer)::numeric, 5), round(regr_r2(temperature::integer, humidity::integer)::numeric, 5), round(regr_slope(temperature::integer, humidity::integer)::numeric, 5), round(regr_sxx(temperature::integer, humidity::integer)::numeric, 5), round(regr_sxy(temperature::integer, humidity::integer)::numeric, 5), round(regr_syy(temperature::integer, humidity::integer)::numeric, 5), round(stddev(temperature::integer), 5), round(stddev_pop(temperature::integer), 5), round(stddev_samp(temperature::integer), 5), round(variance(temperature::integer), 5), round(var_pop(temperature::integer), 5), round(var_samp(temperature::integer), 5), public.last(temperature, timec), public.histogram(temperature, 0::double precision, 100::double precision, 1), timec FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) GROUP BY 1, 35 ORDER BY location ASC NULLS LAST, timec ASC NULLS LAST
|
||||
(22 rows)
|
||||
|
||||
-- Aggregates on custom types are not yet pushed down
|
||||
:PREFIX SELECT :GROUPING,
|
||||
last(highlow, timec) as last_hl,
|
||||
first(highlow, timec) as first_hl
|
||||
FROM :TEST_TABLE
|
||||
GROUP BY :GROUPING
|
||||
ORDER BY :GROUPING;
|
||||
QUERY PLAN
|
||||
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Sort
|
||||
Output: location, (last(highlow, timec)), (first(highlow, timec))
|
||||
Sort Key: location
|
||||
-> Custom Scan (AsyncAppend)
|
||||
Output: location, (last(highlow, timec)), (first(highlow, timec))
|
||||
-> Append
|
||||
-> HashAggregate
|
||||
Output: conditions.location, last(conditions.highlow, conditions.timec), first(conditions.highlow, conditions.timec)
|
||||
Group Key: conditions.location
|
||||
-> Custom Scan (DataNodeScan) on public.conditions
|
||||
Output: conditions.location, conditions.highlow, conditions.timec
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_1_chunk, _dist_hyper_1_2_chunk, _dist_hyper_1_3_chunk, _dist_hyper_1_4_chunk
|
||||
Remote SQL: SELECT timec, location, highlow FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4])
|
||||
-> HashAggregate
|
||||
Output: conditions_1.location, last(conditions_1.highlow, conditions_1.timec), first(conditions_1.highlow, conditions_1.timec)
|
||||
Group Key: conditions_1.location
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_1
|
||||
Output: conditions_1.location, conditions_1.highlow, conditions_1.timec
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_9_chunk, _dist_hyper_1_10_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_12_chunk
|
||||
Remote SQL: SELECT timec, location, highlow FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4])
|
||||
-> HashAggregate
|
||||
Output: conditions_2.location, last(conditions_2.highlow, conditions_2.timec), first(conditions_2.highlow, conditions_2.timec)
|
||||
Group Key: conditions_2.location
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_2
|
||||
Output: conditions_2.location, conditions_2.highlow, conditions_2.timec
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_5_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_7_chunk, _dist_hyper_1_8_chunk
|
||||
Remote SQL: SELECT timec, location, highlow FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4])
|
||||
(30 rows)
|
||||
GROUP BY :GROUPING, timec
|
||||
ORDER BY :GROUPING, timec;
|
||||
QUERY PLAN
|
||||
-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Merge Append
|
||||
Sort Key: conditions.location, conditions.timec
|
||||
-> GroupAggregate
|
||||
Output: conditions.location, last(conditions.highlow, conditions.timec), first(conditions.highlow, conditions.timec), conditions.timec
|
||||
Group Key: conditions.location, conditions.timec
|
||||
-> Custom Scan (DataNodeScan) on public.conditions
|
||||
Output: conditions.location, conditions.timec, conditions.highlow
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_1_chunk, _dist_hyper_1_2_chunk, _dist_hyper_1_3_chunk, _dist_hyper_1_4_chunk
|
||||
Remote SQL: SELECT timec, location, highlow FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) ORDER BY location ASC NULLS LAST, timec ASC NULLS LAST
|
||||
-> GroupAggregate
|
||||
Output: conditions_1.location, last(conditions_1.highlow, conditions_1.timec), first(conditions_1.highlow, conditions_1.timec), conditions_1.timec
|
||||
Group Key: conditions_1.location, conditions_1.timec
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_1
|
||||
Output: conditions_1.location, conditions_1.timec, conditions_1.highlow
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_9_chunk, _dist_hyper_1_10_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_12_chunk
|
||||
Remote SQL: SELECT timec, location, highlow FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) ORDER BY location ASC NULLS LAST, timec ASC NULLS LAST
|
||||
-> GroupAggregate
|
||||
Output: conditions_2.location, last(conditions_2.highlow, conditions_2.timec), first(conditions_2.highlow, conditions_2.timec), conditions_2.timec
|
||||
Group Key: conditions_2.location, conditions_2.timec
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_2
|
||||
Output: conditions_2.location, conditions_2.timec, conditions_2.highlow
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_5_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_7_chunk, _dist_hyper_1_8_chunk
|
||||
Remote SQL: SELECT timec, location, highlow FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) ORDER BY location ASC NULLS LAST, timec ASC NULLS LAST
|
||||
(26 rows)
|
||||
|
||||
-- Mix of aggregates that push down and those that don't
|
||||
:PREFIX SELECT :GROUPING,
|
||||
@ -250,43 +244,39 @@ SET enable_partitionwise_aggregate = ON;
|
||||
bool_or(good_life),
|
||||
first(highlow, timec) as first_hl
|
||||
FROM :TEST_TABLE
|
||||
GROUP BY :GROUPING
|
||||
ORDER BY :GROUPING;
|
||||
QUERY PLAN
|
||||
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Sort
|
||||
Output: location, (min(allnull)), (max(temperature)), ((sum(temperature) + sum(humidity))), (avg(humidity)), (round(stddev((humidity)::integer), 5)), (bit_and(bit_int)), (bit_or(bit_int)), (bool_and(good_life)), (every((temperature > '0'::double precision))), (bool_or(good_life)), (first(highlow, timec))
|
||||
Sort Key: location
|
||||
-> Custom Scan (AsyncAppend)
|
||||
Output: location, (min(allnull)), (max(temperature)), ((sum(temperature) + sum(humidity))), (avg(humidity)), (round(stddev((humidity)::integer), 5)), (bit_and(bit_int)), (bit_or(bit_int)), (bool_and(good_life)), (every((temperature > '0'::double precision))), (bool_or(good_life)), (first(highlow, timec))
|
||||
-> Append
|
||||
-> HashAggregate
|
||||
Output: conditions.location, min(conditions.allnull), max(conditions.temperature), (sum(conditions.temperature) + sum(conditions.humidity)), avg(conditions.humidity), round(stddev((conditions.humidity)::integer), 5), bit_and(conditions.bit_int), bit_or(conditions.bit_int), bool_and(conditions.good_life), every((conditions.temperature > '0'::double precision)), bool_or(conditions.good_life), first(conditions.highlow, conditions.timec)
|
||||
Group Key: conditions.location
|
||||
-> Custom Scan (DataNodeScan) on public.conditions
|
||||
Output: conditions.location, conditions.allnull, conditions.temperature, conditions.humidity, conditions.bit_int, conditions.good_life, conditions.highlow, conditions.timec
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_1_chunk, _dist_hyper_1_2_chunk, _dist_hyper_1_3_chunk, _dist_hyper_1_4_chunk
|
||||
Remote SQL: SELECT timec, location, temperature, humidity, allnull, highlow, bit_int, good_life FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4])
|
||||
-> HashAggregate
|
||||
Output: conditions_1.location, min(conditions_1.allnull), max(conditions_1.temperature), (sum(conditions_1.temperature) + sum(conditions_1.humidity)), avg(conditions_1.humidity), round(stddev((conditions_1.humidity)::integer), 5), bit_and(conditions_1.bit_int), bit_or(conditions_1.bit_int), bool_and(conditions_1.good_life), every((conditions_1.temperature > '0'::double precision)), bool_or(conditions_1.good_life), first(conditions_1.highlow, conditions_1.timec)
|
||||
Group Key: conditions_1.location
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_1
|
||||
Output: conditions_1.location, conditions_1.allnull, conditions_1.temperature, conditions_1.humidity, conditions_1.bit_int, conditions_1.good_life, conditions_1.highlow, conditions_1.timec
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_9_chunk, _dist_hyper_1_10_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_12_chunk
|
||||
Remote SQL: SELECT timec, location, temperature, humidity, allnull, highlow, bit_int, good_life FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4])
|
||||
-> HashAggregate
|
||||
Output: conditions_2.location, min(conditions_2.allnull), max(conditions_2.temperature), (sum(conditions_2.temperature) + sum(conditions_2.humidity)), avg(conditions_2.humidity), round(stddev((conditions_2.humidity)::integer), 5), bit_and(conditions_2.bit_int), bit_or(conditions_2.bit_int), bool_and(conditions_2.good_life), every((conditions_2.temperature > '0'::double precision)), bool_or(conditions_2.good_life), first(conditions_2.highlow, conditions_2.timec)
|
||||
Group Key: conditions_2.location
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_2
|
||||
Output: conditions_2.location, conditions_2.allnull, conditions_2.temperature, conditions_2.humidity, conditions_2.bit_int, conditions_2.good_life, conditions_2.highlow, conditions_2.timec
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_5_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_7_chunk, _dist_hyper_1_8_chunk
|
||||
Remote SQL: SELECT timec, location, temperature, humidity, allnull, highlow, bit_int, good_life FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4])
|
||||
(30 rows)
|
||||
GROUP BY :GROUPING, timec
|
||||
ORDER BY :GROUPING, timec;
|
||||
QUERY PLAN
|
||||
---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Merge Append
|
||||
Sort Key: conditions.location, conditions.timec
|
||||
-> GroupAggregate
|
||||
Output: conditions.location, min(conditions.allnull), max(conditions.temperature), (sum(conditions.temperature) + sum(conditions.humidity)), avg(conditions.humidity), round(stddev((conditions.humidity)::integer), 5), bit_and(conditions.bit_int), bit_or(conditions.bit_int), bool_and(conditions.good_life), every((conditions.temperature > '0'::double precision)), bool_or(conditions.good_life), first(conditions.highlow, conditions.timec), conditions.timec
|
||||
Group Key: conditions.location, conditions.timec
|
||||
-> Custom Scan (DataNodeScan) on public.conditions
|
||||
Output: conditions.location, conditions.timec, conditions.allnull, conditions.temperature, conditions.humidity, conditions.bit_int, conditions.good_life, conditions.highlow
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_1_chunk, _dist_hyper_1_2_chunk, _dist_hyper_1_3_chunk, _dist_hyper_1_4_chunk
|
||||
Remote SQL: SELECT timec, location, temperature, humidity, allnull, highlow, bit_int, good_life FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) ORDER BY location ASC NULLS LAST, timec ASC NULLS LAST
|
||||
-> GroupAggregate
|
||||
Output: conditions_1.location, min(conditions_1.allnull), max(conditions_1.temperature), (sum(conditions_1.temperature) + sum(conditions_1.humidity)), avg(conditions_1.humidity), round(stddev((conditions_1.humidity)::integer), 5), bit_and(conditions_1.bit_int), bit_or(conditions_1.bit_int), bool_and(conditions_1.good_life), every((conditions_1.temperature > '0'::double precision)), bool_or(conditions_1.good_life), first(conditions_1.highlow, conditions_1.timec), conditions_1.timec
|
||||
Group Key: conditions_1.location, conditions_1.timec
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_1
|
||||
Output: conditions_1.location, conditions_1.timec, conditions_1.allnull, conditions_1.temperature, conditions_1.humidity, conditions_1.bit_int, conditions_1.good_life, conditions_1.highlow
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_9_chunk, _dist_hyper_1_10_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_12_chunk
|
||||
Remote SQL: SELECT timec, location, temperature, humidity, allnull, highlow, bit_int, good_life FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) ORDER BY location ASC NULLS LAST, timec ASC NULLS LAST
|
||||
-> GroupAggregate
|
||||
Output: conditions_2.location, min(conditions_2.allnull), max(conditions_2.temperature), (sum(conditions_2.temperature) + sum(conditions_2.humidity)), avg(conditions_2.humidity), round(stddev((conditions_2.humidity)::integer), 5), bit_and(conditions_2.bit_int), bit_or(conditions_2.bit_int), bool_and(conditions_2.good_life), every((conditions_2.temperature > '0'::double precision)), bool_or(conditions_2.good_life), first(conditions_2.highlow, conditions_2.timec), conditions_2.timec
|
||||
Group Key: conditions_2.location, conditions_2.timec
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_2
|
||||
Output: conditions_2.location, conditions_2.timec, conditions_2.allnull, conditions_2.temperature, conditions_2.humidity, conditions_2.bit_int, conditions_2.good_life, conditions_2.highlow
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_5_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_7_chunk, _dist_hyper_1_8_chunk
|
||||
Remote SQL: SELECT timec, location, temperature, humidity, allnull, highlow, bit_int, good_life FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) ORDER BY location ASC NULLS LAST, timec ASC NULLS LAST
|
||||
(26 rows)
|
||||
|
||||
\set GROUPING 'region'
|
||||
\set GROUPING 'region, temperature'
|
||||
\ir 'include/aggregate_queries.sql'
|
||||
-- This file and its contents are licensed under the Timescale License.
|
||||
-- Please see the included NOTICE for copyright information and
|
||||
@ -328,82 +318,76 @@ SET enable_partitionwise_aggregate = ON;
|
||||
last(temperature, timec) as last_temp,
|
||||
histogram(temperature, 0, 100, 1)
|
||||
FROM :TEST_TABLE
|
||||
GROUP BY :GROUPING
|
||||
ORDER BY :GROUPING;
|
||||
QUERY PLAN
|
||||
---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
GROUP BY :GROUPING, timec
|
||||
ORDER BY :GROUPING, timec;
|
||||
QUERY PLAN
|
||||
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Finalize GroupAggregate
|
||||
Output: region, min(allnull), max(temperature), (sum(temperature) + sum(humidity)), avg(humidity), round(stddev((humidity)::integer), 5), bit_and(bit_int), bit_or(bit_int), bool_and(good_life), every((temperature > '0'::double precision)), bool_or(good_life), count(*), count(temperature), count(allnull), round((corr(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((covar_pop(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((covar_samp(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_avgx(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_avgy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_count(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_intercept(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_r2(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_slope(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_sxx(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_sxy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_syy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round(stddev((temperature)::integer), 5), round(stddev_pop((temperature)::integer), 5), round(stddev_samp((temperature)::integer), 5), round(variance((temperature)::integer), 5), round(var_pop((temperature)::integer), 5), round(var_samp((temperature)::integer), 5), last(temperature, timec), histogram(temperature, '0'::double precision, '100'::double precision, 1)
|
||||
Group Key: region
|
||||
-> Sort
|
||||
Output: region, (PARTIAL min(allnull)), (PARTIAL max(temperature)), (PARTIAL sum(temperature)), (PARTIAL sum(humidity)), (PARTIAL avg(humidity)), (PARTIAL stddev((humidity)::integer)), (PARTIAL bit_and(bit_int)), (PARTIAL bit_or(bit_int)), (PARTIAL bool_and(good_life)), (PARTIAL every((temperature > '0'::double precision))), (PARTIAL bool_or(good_life)), (PARTIAL count(*)), (PARTIAL count(temperature)), (PARTIAL count(allnull)), (PARTIAL corr(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL covar_pop(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL covar_samp(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_avgx(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_avgy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_count(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_intercept(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_r2(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_slope(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_sxx(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_sxy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_syy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL stddev((temperature)::integer)), (PARTIAL stddev_pop((temperature)::integer)), (PARTIAL stddev_samp((temperature)::integer)), (PARTIAL variance((temperature)::integer)), (PARTIAL var_pop((temperature)::integer)), (PARTIAL var_samp((temperature)::integer)), (PARTIAL last(temperature, timec)), (PARTIAL histogram(temperature, '0'::double precision, '100'::double precision, 1))
|
||||
Sort Key: region
|
||||
-> Custom Scan (AsyncAppend)
|
||||
Output: region, (PARTIAL min(allnull)), (PARTIAL max(temperature)), (PARTIAL sum(temperature)), (PARTIAL sum(humidity)), (PARTIAL avg(humidity)), (PARTIAL stddev((humidity)::integer)), (PARTIAL bit_and(bit_int)), (PARTIAL bit_or(bit_int)), (PARTIAL bool_and(good_life)), (PARTIAL every((temperature > '0'::double precision))), (PARTIAL bool_or(good_life)), (PARTIAL count(*)), (PARTIAL count(temperature)), (PARTIAL count(allnull)), (PARTIAL corr(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL covar_pop(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL covar_samp(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_avgx(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_avgy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_count(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_intercept(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_r2(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_slope(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_sxx(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_sxy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_syy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL stddev((temperature)::integer)), (PARTIAL stddev_pop((temperature)::integer)), (PARTIAL stddev_samp((temperature)::integer)), (PARTIAL variance((temperature)::integer)), (PARTIAL var_pop((temperature)::integer)), (PARTIAL var_samp((temperature)::integer)), (PARTIAL last(temperature, timec)), (PARTIAL histogram(temperature, '0'::double precision, '100'::double precision, 1))
|
||||
-> Append
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: conditions.region, (PARTIAL min(conditions.allnull)), (PARTIAL max(conditions.temperature)), (PARTIAL sum(conditions.temperature)), (PARTIAL sum(conditions.humidity)), (PARTIAL avg(conditions.humidity)), (PARTIAL stddev((conditions.humidity)::integer)), (PARTIAL bit_and(conditions.bit_int)), (PARTIAL bit_or(conditions.bit_int)), (PARTIAL bool_and(conditions.good_life)), (PARTIAL every((conditions.temperature > '0'::double precision))), (PARTIAL bool_or(conditions.good_life)), (PARTIAL count(*)), (PARTIAL count(conditions.temperature)), (PARTIAL count(conditions.allnull)), (PARTIAL corr(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL covar_pop(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL covar_samp(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL regr_avgx(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL regr_avgy(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL regr_count(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL regr_intercept(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL regr_r2(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL regr_slope(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL regr_sxx(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL regr_sxy(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL regr_syy(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL stddev((conditions.temperature)::integer)), (PARTIAL stddev_pop((conditions.temperature)::integer)), (PARTIAL stddev_samp((conditions.temperature)::integer)), (PARTIAL variance((conditions.temperature)::integer)), (PARTIAL var_pop((conditions.temperature)::integer)), (PARTIAL var_samp((conditions.temperature)::integer)), (PARTIAL last(conditions.temperature, conditions.timec)), (PARTIAL histogram(conditions.temperature, '0'::double precision, '100'::double precision, 1))
|
||||
Relations: Aggregate on (public.conditions)
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_1_chunk, _dist_hyper_1_2_chunk, _dist_hyper_1_3_chunk, _dist_hyper_1_4_chunk
|
||||
Remote SQL: SELECT region, _timescaledb_internal.partialize_agg(min(allnull)), _timescaledb_internal.partialize_agg(max(temperature)), _timescaledb_internal.partialize_agg(sum(temperature)), _timescaledb_internal.partialize_agg(sum(humidity)), _timescaledb_internal.partialize_agg(avg(humidity)), _timescaledb_internal.partialize_agg(stddev(humidity::integer)), _timescaledb_internal.partialize_agg(bit_and(bit_int)), _timescaledb_internal.partialize_agg(bit_or(bit_int)), _timescaledb_internal.partialize_agg(bool_and(good_life)), _timescaledb_internal.partialize_agg(every((temperature > 0::double precision))), _timescaledb_internal.partialize_agg(bool_or(good_life)), _timescaledb_internal.partialize_agg(count(*)), _timescaledb_internal.partialize_agg(count(temperature)), _timescaledb_internal.partialize_agg(count(allnull)), _timescaledb_internal.partialize_agg(corr(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(covar_pop(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(covar_samp(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_avgx(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_avgy(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_count(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_intercept(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_r2(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_slope(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_sxx(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_sxy(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_syy(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(stddev(temperature::integer)), _timescaledb_internal.partialize_agg(stddev_pop(temperature::integer)), _timescaledb_internal.partialize_agg(stddev_samp(temperature::integer)), _timescaledb_internal.partialize_agg(variance(temperature::integer)), _timescaledb_internal.partialize_agg(var_pop(temperature::integer)), _timescaledb_internal.partialize_agg(var_samp(temperature::integer)), _timescaledb_internal.partialize_agg(public.last(temperature, timec)), _timescaledb_internal.partialize_agg(public.histogram(temperature, 0::double precision, 100::double precision, 1)) FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) GROUP BY 1
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: conditions_1.region, (PARTIAL min(conditions_1.allnull)), (PARTIAL max(conditions_1.temperature)), (PARTIAL sum(conditions_1.temperature)), (PARTIAL sum(conditions_1.humidity)), (PARTIAL avg(conditions_1.humidity)), (PARTIAL stddev((conditions_1.humidity)::integer)), (PARTIAL bit_and(conditions_1.bit_int)), (PARTIAL bit_or(conditions_1.bit_int)), (PARTIAL bool_and(conditions_1.good_life)), (PARTIAL every((conditions_1.temperature > '0'::double precision))), (PARTIAL bool_or(conditions_1.good_life)), (PARTIAL count(*)), (PARTIAL count(conditions_1.temperature)), (PARTIAL count(conditions_1.allnull)), (PARTIAL corr(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL covar_pop(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL covar_samp(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL regr_avgx(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL regr_avgy(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL regr_count(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL regr_intercept(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL regr_r2(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL regr_slope(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL regr_sxx(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL regr_sxy(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL regr_syy(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL stddev((conditions_1.temperature)::integer)), (PARTIAL stddev_pop((conditions_1.temperature)::integer)), (PARTIAL stddev_samp((conditions_1.temperature)::integer)), (PARTIAL variance((conditions_1.temperature)::integer)), (PARTIAL var_pop((conditions_1.temperature)::integer)), (PARTIAL var_samp((conditions_1.temperature)::integer)), (PARTIAL last(conditions_1.temperature, conditions_1.timec)), (PARTIAL histogram(conditions_1.temperature, '0'::double precision, '100'::double precision, 1))
|
||||
Relations: Aggregate on (public.conditions)
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_9_chunk, _dist_hyper_1_10_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_12_chunk
|
||||
Remote SQL: SELECT region, _timescaledb_internal.partialize_agg(min(allnull)), _timescaledb_internal.partialize_agg(max(temperature)), _timescaledb_internal.partialize_agg(sum(temperature)), _timescaledb_internal.partialize_agg(sum(humidity)), _timescaledb_internal.partialize_agg(avg(humidity)), _timescaledb_internal.partialize_agg(stddev(humidity::integer)), _timescaledb_internal.partialize_agg(bit_and(bit_int)), _timescaledb_internal.partialize_agg(bit_or(bit_int)), _timescaledb_internal.partialize_agg(bool_and(good_life)), _timescaledb_internal.partialize_agg(every((temperature > 0::double precision))), _timescaledb_internal.partialize_agg(bool_or(good_life)), _timescaledb_internal.partialize_agg(count(*)), _timescaledb_internal.partialize_agg(count(temperature)), _timescaledb_internal.partialize_agg(count(allnull)), _timescaledb_internal.partialize_agg(corr(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(covar_pop(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(covar_samp(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_avgx(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_avgy(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_count(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_intercept(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_r2(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_slope(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_sxx(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_sxy(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_syy(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(stddev(temperature::integer)), _timescaledb_internal.partialize_agg(stddev_pop(temperature::integer)), _timescaledb_internal.partialize_agg(stddev_samp(temperature::integer)), _timescaledb_internal.partialize_agg(variance(temperature::integer)), _timescaledb_internal.partialize_agg(var_pop(temperature::integer)), _timescaledb_internal.partialize_agg(var_samp(temperature::integer)), _timescaledb_internal.partialize_agg(public.last(temperature, timec)), _timescaledb_internal.partialize_agg(public.histogram(temperature, 0::double precision, 100::double precision, 1)) FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) GROUP BY 1
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: conditions_2.region, (PARTIAL min(conditions_2.allnull)), (PARTIAL max(conditions_2.temperature)), (PARTIAL sum(conditions_2.temperature)), (PARTIAL sum(conditions_2.humidity)), (PARTIAL avg(conditions_2.humidity)), (PARTIAL stddev((conditions_2.humidity)::integer)), (PARTIAL bit_and(conditions_2.bit_int)), (PARTIAL bit_or(conditions_2.bit_int)), (PARTIAL bool_and(conditions_2.good_life)), (PARTIAL every((conditions_2.temperature > '0'::double precision))), (PARTIAL bool_or(conditions_2.good_life)), (PARTIAL count(*)), (PARTIAL count(conditions_2.temperature)), (PARTIAL count(conditions_2.allnull)), (PARTIAL corr(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL covar_pop(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL covar_samp(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL regr_avgx(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL regr_avgy(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL regr_count(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL regr_intercept(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL regr_r2(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL regr_slope(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL regr_sxx(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL regr_sxy(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL regr_syy(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL stddev((conditions_2.temperature)::integer)), (PARTIAL stddev_pop((conditions_2.temperature)::integer)), (PARTIAL stddev_samp((conditions_2.temperature)::integer)), (PARTIAL variance((conditions_2.temperature)::integer)), (PARTIAL var_pop((conditions_2.temperature)::integer)), (PARTIAL var_samp((conditions_2.temperature)::integer)), (PARTIAL last(conditions_2.temperature, conditions_2.timec)), (PARTIAL histogram(conditions_2.temperature, '0'::double precision, '100'::double precision, 1))
|
||||
Relations: Aggregate on (public.conditions)
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_5_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_7_chunk, _dist_hyper_1_8_chunk
|
||||
Remote SQL: SELECT region, _timescaledb_internal.partialize_agg(min(allnull)), _timescaledb_internal.partialize_agg(max(temperature)), _timescaledb_internal.partialize_agg(sum(temperature)), _timescaledb_internal.partialize_agg(sum(humidity)), _timescaledb_internal.partialize_agg(avg(humidity)), _timescaledb_internal.partialize_agg(stddev(humidity::integer)), _timescaledb_internal.partialize_agg(bit_and(bit_int)), _timescaledb_internal.partialize_agg(bit_or(bit_int)), _timescaledb_internal.partialize_agg(bool_and(good_life)), _timescaledb_internal.partialize_agg(every((temperature > 0::double precision))), _timescaledb_internal.partialize_agg(bool_or(good_life)), _timescaledb_internal.partialize_agg(count(*)), _timescaledb_internal.partialize_agg(count(temperature)), _timescaledb_internal.partialize_agg(count(allnull)), _timescaledb_internal.partialize_agg(corr(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(covar_pop(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(covar_samp(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_avgx(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_avgy(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_count(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_intercept(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_r2(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_slope(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_sxx(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_sxy(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_syy(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(stddev(temperature::integer)), _timescaledb_internal.partialize_agg(stddev_pop(temperature::integer)), _timescaledb_internal.partialize_agg(stddev_samp(temperature::integer)), _timescaledb_internal.partialize_agg(variance(temperature::integer)), _timescaledb_internal.partialize_agg(var_pop(temperature::integer)), _timescaledb_internal.partialize_agg(var_samp(temperature::integer)), _timescaledb_internal.partialize_agg(public.last(temperature, timec)), _timescaledb_internal.partialize_agg(public.histogram(temperature, 0::double precision, 100::double precision, 1)) FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) GROUP BY 1
|
||||
(27 rows)
|
||||
Output: region, temperature, min(allnull), max(temperature), (sum(temperature) + sum(humidity)), avg(humidity), round(stddev((humidity)::integer), 5), bit_and(bit_int), bit_or(bit_int), bool_and(good_life), every((temperature > '0'::double precision)), bool_or(good_life), count(*), count(temperature), count(allnull), round((corr(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((covar_pop(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((covar_samp(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_avgx(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_avgy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_count(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_intercept(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_r2(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_slope(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_sxx(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_sxy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_syy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round(stddev((temperature)::integer), 5), round(stddev_pop((temperature)::integer), 5), round(stddev_samp((temperature)::integer), 5), round(variance((temperature)::integer), 5), round(var_pop((temperature)::integer), 5), round(var_samp((temperature)::integer), 5), last(temperature, timec), histogram(temperature, '0'::double precision, '100'::double precision, 1), timec
|
||||
Group Key: region, temperature, timec
|
||||
-> Custom Scan (AsyncAppend)
|
||||
Output: region, temperature, timec, (PARTIAL min(allnull)), (PARTIAL max(temperature)), (PARTIAL sum(temperature)), (PARTIAL sum(humidity)), (PARTIAL avg(humidity)), (PARTIAL stddev((humidity)::integer)), (PARTIAL bit_and(bit_int)), (PARTIAL bit_or(bit_int)), (PARTIAL bool_and(good_life)), (PARTIAL every((temperature > '0'::double precision))), (PARTIAL bool_or(good_life)), (PARTIAL count(*)), (PARTIAL count(temperature)), (PARTIAL count(allnull)), (PARTIAL corr(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL covar_pop(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL covar_samp(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_avgx(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_avgy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_count(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_intercept(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_r2(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_slope(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_sxx(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_sxy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_syy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL stddev((temperature)::integer)), (PARTIAL stddev_pop((temperature)::integer)), (PARTIAL stddev_samp((temperature)::integer)), (PARTIAL variance((temperature)::integer)), (PARTIAL var_pop((temperature)::integer)), (PARTIAL var_samp((temperature)::integer)), (PARTIAL last(temperature, timec)), (PARTIAL histogram(temperature, '0'::double precision, '100'::double precision, 1))
|
||||
-> Merge Append
|
||||
Sort Key: conditions.region, conditions.temperature, conditions.timec
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: conditions.region, conditions.temperature, conditions.timec, (PARTIAL min(conditions.allnull)), (PARTIAL max(conditions.temperature)), (PARTIAL sum(conditions.temperature)), (PARTIAL sum(conditions.humidity)), (PARTIAL avg(conditions.humidity)), (PARTIAL stddev((conditions.humidity)::integer)), (PARTIAL bit_and(conditions.bit_int)), (PARTIAL bit_or(conditions.bit_int)), (PARTIAL bool_and(conditions.good_life)), (PARTIAL every((conditions.temperature > '0'::double precision))), (PARTIAL bool_or(conditions.good_life)), (PARTIAL count(*)), (PARTIAL count(conditions.temperature)), (PARTIAL count(conditions.allnull)), (PARTIAL corr(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL covar_pop(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL covar_samp(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL regr_avgx(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL regr_avgy(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL regr_count(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL regr_intercept(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL regr_r2(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL regr_slope(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL regr_sxx(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL regr_sxy(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL regr_syy(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL stddev((conditions.temperature)::integer)), (PARTIAL stddev_pop((conditions.temperature)::integer)), (PARTIAL stddev_samp((conditions.temperature)::integer)), (PARTIAL variance((conditions.temperature)::integer)), (PARTIAL var_pop((conditions.temperature)::integer)), (PARTIAL var_samp((conditions.temperature)::integer)), (PARTIAL last(conditions.temperature, conditions.timec)), (PARTIAL histogram(conditions.temperature, '0'::double precision, '100'::double precision, 1))
|
||||
Relations: Aggregate on (public.conditions)
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_1_chunk, _dist_hyper_1_2_chunk, _dist_hyper_1_3_chunk, _dist_hyper_1_4_chunk
|
||||
Remote SQL: SELECT region, temperature, timec, _timescaledb_internal.partialize_agg(min(allnull)), _timescaledb_internal.partialize_agg(max(temperature)), _timescaledb_internal.partialize_agg(sum(temperature)), _timescaledb_internal.partialize_agg(sum(humidity)), _timescaledb_internal.partialize_agg(avg(humidity)), _timescaledb_internal.partialize_agg(stddev(humidity::integer)), _timescaledb_internal.partialize_agg(bit_and(bit_int)), _timescaledb_internal.partialize_agg(bit_or(bit_int)), _timescaledb_internal.partialize_agg(bool_and(good_life)), _timescaledb_internal.partialize_agg(every((temperature > 0::double precision))), _timescaledb_internal.partialize_agg(bool_or(good_life)), _timescaledb_internal.partialize_agg(count(*)), _timescaledb_internal.partialize_agg(count(temperature)), _timescaledb_internal.partialize_agg(count(allnull)), _timescaledb_internal.partialize_agg(corr(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(covar_pop(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(covar_samp(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_avgx(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_avgy(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_count(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_intercept(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_r2(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_slope(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_sxx(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_sxy(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_syy(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(stddev(temperature::integer)), _timescaledb_internal.partialize_agg(stddev_pop(temperature::integer)), _timescaledb_internal.partialize_agg(stddev_samp(temperature::integer)), _timescaledb_internal.partialize_agg(variance(temperature::integer)), _timescaledb_internal.partialize_agg(var_pop(temperature::integer)), _timescaledb_internal.partialize_agg(var_samp(temperature::integer)), _timescaledb_internal.partialize_agg(public.last(temperature, timec)), _timescaledb_internal.partialize_agg(public.histogram(temperature, 0::double precision, 100::double precision, 1)) FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) GROUP BY 1, 2, 3 ORDER BY region ASC NULLS LAST, temperature ASC NULLS LAST, timec ASC NULLS LAST
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: conditions_1.region, conditions_1.temperature, conditions_1.timec, (PARTIAL min(conditions_1.allnull)), (PARTIAL max(conditions_1.temperature)), (PARTIAL sum(conditions_1.temperature)), (PARTIAL sum(conditions_1.humidity)), (PARTIAL avg(conditions_1.humidity)), (PARTIAL stddev((conditions_1.humidity)::integer)), (PARTIAL bit_and(conditions_1.bit_int)), (PARTIAL bit_or(conditions_1.bit_int)), (PARTIAL bool_and(conditions_1.good_life)), (PARTIAL every((conditions_1.temperature > '0'::double precision))), (PARTIAL bool_or(conditions_1.good_life)), (PARTIAL count(*)), (PARTIAL count(conditions_1.temperature)), (PARTIAL count(conditions_1.allnull)), (PARTIAL corr(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL covar_pop(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL covar_samp(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL regr_avgx(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL regr_avgy(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL regr_count(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL regr_intercept(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL regr_r2(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL regr_slope(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL regr_sxx(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL regr_sxy(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL regr_syy(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL stddev((conditions_1.temperature)::integer)), (PARTIAL stddev_pop((conditions_1.temperature)::integer)), (PARTIAL stddev_samp((conditions_1.temperature)::integer)), (PARTIAL variance((conditions_1.temperature)::integer)), (PARTIAL var_pop((conditions_1.temperature)::integer)), (PARTIAL var_samp((conditions_1.temperature)::integer)), (PARTIAL last(conditions_1.temperature, conditions_1.timec)), (PARTIAL histogram(conditions_1.temperature, '0'::double precision, '100'::double precision, 1))
|
||||
Relations: Aggregate on (public.conditions)
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_9_chunk, _dist_hyper_1_10_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_12_chunk
|
||||
Remote SQL: SELECT region, temperature, timec, _timescaledb_internal.partialize_agg(min(allnull)), _timescaledb_internal.partialize_agg(max(temperature)), _timescaledb_internal.partialize_agg(sum(temperature)), _timescaledb_internal.partialize_agg(sum(humidity)), _timescaledb_internal.partialize_agg(avg(humidity)), _timescaledb_internal.partialize_agg(stddev(humidity::integer)), _timescaledb_internal.partialize_agg(bit_and(bit_int)), _timescaledb_internal.partialize_agg(bit_or(bit_int)), _timescaledb_internal.partialize_agg(bool_and(good_life)), _timescaledb_internal.partialize_agg(every((temperature > 0::double precision))), _timescaledb_internal.partialize_agg(bool_or(good_life)), _timescaledb_internal.partialize_agg(count(*)), _timescaledb_internal.partialize_agg(count(temperature)), _timescaledb_internal.partialize_agg(count(allnull)), _timescaledb_internal.partialize_agg(corr(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(covar_pop(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(covar_samp(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_avgx(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_avgy(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_count(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_intercept(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_r2(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_slope(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_sxx(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_sxy(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_syy(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(stddev(temperature::integer)), _timescaledb_internal.partialize_agg(stddev_pop(temperature::integer)), _timescaledb_internal.partialize_agg(stddev_samp(temperature::integer)), _timescaledb_internal.partialize_agg(variance(temperature::integer)), _timescaledb_internal.partialize_agg(var_pop(temperature::integer)), _timescaledb_internal.partialize_agg(var_samp(temperature::integer)), _timescaledb_internal.partialize_agg(public.last(temperature, timec)), _timescaledb_internal.partialize_agg(public.histogram(temperature, 0::double precision, 100::double precision, 1)) FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) GROUP BY 1, 2, 3 ORDER BY region ASC NULLS LAST, temperature ASC NULLS LAST, timec ASC NULLS LAST
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: conditions_2.region, conditions_2.temperature, conditions_2.timec, (PARTIAL min(conditions_2.allnull)), (PARTIAL max(conditions_2.temperature)), (PARTIAL sum(conditions_2.temperature)), (PARTIAL sum(conditions_2.humidity)), (PARTIAL avg(conditions_2.humidity)), (PARTIAL stddev((conditions_2.humidity)::integer)), (PARTIAL bit_and(conditions_2.bit_int)), (PARTIAL bit_or(conditions_2.bit_int)), (PARTIAL bool_and(conditions_2.good_life)), (PARTIAL every((conditions_2.temperature > '0'::double precision))), (PARTIAL bool_or(conditions_2.good_life)), (PARTIAL count(*)), (PARTIAL count(conditions_2.temperature)), (PARTIAL count(conditions_2.allnull)), (PARTIAL corr(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL covar_pop(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL covar_samp(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL regr_avgx(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL regr_avgy(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL regr_count(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL regr_intercept(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL regr_r2(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL regr_slope(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL regr_sxx(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL regr_sxy(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL regr_syy(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL stddev((conditions_2.temperature)::integer)), (PARTIAL stddev_pop((conditions_2.temperature)::integer)), (PARTIAL stddev_samp((conditions_2.temperature)::integer)), (PARTIAL variance((conditions_2.temperature)::integer)), (PARTIAL var_pop((conditions_2.temperature)::integer)), (PARTIAL var_samp((conditions_2.temperature)::integer)), (PARTIAL last(conditions_2.temperature, conditions_2.timec)), (PARTIAL histogram(conditions_2.temperature, '0'::double precision, '100'::double precision, 1))
|
||||
Relations: Aggregate on (public.conditions)
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_5_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_7_chunk, _dist_hyper_1_8_chunk
|
||||
Remote SQL: SELECT region, temperature, timec, _timescaledb_internal.partialize_agg(min(allnull)), _timescaledb_internal.partialize_agg(max(temperature)), _timescaledb_internal.partialize_agg(sum(temperature)), _timescaledb_internal.partialize_agg(sum(humidity)), _timescaledb_internal.partialize_agg(avg(humidity)), _timescaledb_internal.partialize_agg(stddev(humidity::integer)), _timescaledb_internal.partialize_agg(bit_and(bit_int)), _timescaledb_internal.partialize_agg(bit_or(bit_int)), _timescaledb_internal.partialize_agg(bool_and(good_life)), _timescaledb_internal.partialize_agg(every((temperature > 0::double precision))), _timescaledb_internal.partialize_agg(bool_or(good_life)), _timescaledb_internal.partialize_agg(count(*)), _timescaledb_internal.partialize_agg(count(temperature)), _timescaledb_internal.partialize_agg(count(allnull)), _timescaledb_internal.partialize_agg(corr(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(covar_pop(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(covar_samp(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_avgx(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_avgy(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_count(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_intercept(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_r2(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_slope(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_sxx(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_sxy(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_syy(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(stddev(temperature::integer)), _timescaledb_internal.partialize_agg(stddev_pop(temperature::integer)), _timescaledb_internal.partialize_agg(stddev_samp(temperature::integer)), _timescaledb_internal.partialize_agg(variance(temperature::integer)), _timescaledb_internal.partialize_agg(var_pop(temperature::integer)), _timescaledb_internal.partialize_agg(var_samp(temperature::integer)), _timescaledb_internal.partialize_agg(public.last(temperature, timec)), _timescaledb_internal.partialize_agg(public.histogram(temperature, 0::double precision, 100::double precision, 1)) FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) GROUP BY 1, 2, 3 ORDER BY region ASC NULLS LAST, temperature ASC NULLS LAST, timec ASC NULLS LAST
|
||||
(25 rows)
|
||||
|
||||
-- Aggregates on custom types are not yet pushed down
|
||||
:PREFIX SELECT :GROUPING,
|
||||
last(highlow, timec) as last_hl,
|
||||
first(highlow, timec) as first_hl
|
||||
FROM :TEST_TABLE
|
||||
GROUP BY :GROUPING
|
||||
ORDER BY :GROUPING;
|
||||
QUERY PLAN
|
||||
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
GROUP BY :GROUPING, timec
|
||||
ORDER BY :GROUPING, timec;
|
||||
QUERY PLAN
|
||||
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Finalize GroupAggregate
|
||||
Output: region, last(highlow, timec), first(highlow, timec)
|
||||
Group Key: region
|
||||
-> Sort
|
||||
Output: region, (PARTIAL last(highlow, timec)), (PARTIAL first(highlow, timec))
|
||||
Sort Key: region
|
||||
-> Custom Scan (AsyncAppend)
|
||||
Output: region, (PARTIAL last(highlow, timec)), (PARTIAL first(highlow, timec))
|
||||
-> Append
|
||||
-> Partial HashAggregate
|
||||
Output: conditions.region, PARTIAL last(conditions.highlow, conditions.timec), PARTIAL first(conditions.highlow, conditions.timec)
|
||||
Group Key: conditions.region
|
||||
-> Custom Scan (DataNodeScan) on public.conditions
|
||||
Output: conditions.region, conditions.highlow, conditions.timec
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_1_chunk, _dist_hyper_1_2_chunk, _dist_hyper_1_3_chunk, _dist_hyper_1_4_chunk
|
||||
Remote SQL: SELECT timec, region, highlow FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4])
|
||||
-> Partial HashAggregate
|
||||
Output: conditions_1.region, PARTIAL last(conditions_1.highlow, conditions_1.timec), PARTIAL first(conditions_1.highlow, conditions_1.timec)
|
||||
Group Key: conditions_1.region
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_1
|
||||
Output: conditions_1.region, conditions_1.highlow, conditions_1.timec
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_9_chunk, _dist_hyper_1_10_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_12_chunk
|
||||
Remote SQL: SELECT timec, region, highlow FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4])
|
||||
-> Partial HashAggregate
|
||||
Output: conditions_2.region, PARTIAL last(conditions_2.highlow, conditions_2.timec), PARTIAL first(conditions_2.highlow, conditions_2.timec)
|
||||
Group Key: conditions_2.region
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_2
|
||||
Output: conditions_2.region, conditions_2.highlow, conditions_2.timec
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_5_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_7_chunk, _dist_hyper_1_8_chunk
|
||||
Remote SQL: SELECT timec, region, highlow FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4])
|
||||
(33 rows)
|
||||
Output: conditions.region, conditions.temperature, last(conditions.highlow, conditions.timec), first(conditions.highlow, conditions.timec), conditions.timec
|
||||
Group Key: conditions.region, conditions.temperature, conditions.timec
|
||||
-> Merge Append
|
||||
Sort Key: conditions.region, conditions.temperature, conditions.timec
|
||||
-> Partial GroupAggregate
|
||||
Output: conditions.region, conditions.temperature, conditions.timec, PARTIAL last(conditions.highlow, conditions.timec), PARTIAL first(conditions.highlow, conditions.timec)
|
||||
Group Key: conditions.region, conditions.temperature, conditions.timec
|
||||
-> Custom Scan (DataNodeScan) on public.conditions
|
||||
Output: conditions.region, conditions.temperature, conditions.timec, conditions.highlow
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_1_chunk, _dist_hyper_1_2_chunk, _dist_hyper_1_3_chunk, _dist_hyper_1_4_chunk
|
||||
Remote SQL: SELECT timec, region, temperature, highlow FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) ORDER BY region ASC NULLS LAST, temperature ASC NULLS LAST, timec ASC NULLS LAST
|
||||
-> Partial GroupAggregate
|
||||
Output: conditions_1.region, conditions_1.temperature, conditions_1.timec, PARTIAL last(conditions_1.highlow, conditions_1.timec), PARTIAL first(conditions_1.highlow, conditions_1.timec)
|
||||
Group Key: conditions_1.region, conditions_1.temperature, conditions_1.timec
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_1
|
||||
Output: conditions_1.region, conditions_1.temperature, conditions_1.timec, conditions_1.highlow
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_9_chunk, _dist_hyper_1_10_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_12_chunk
|
||||
Remote SQL: SELECT timec, region, temperature, highlow FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) ORDER BY region ASC NULLS LAST, temperature ASC NULLS LAST, timec ASC NULLS LAST
|
||||
-> Partial GroupAggregate
|
||||
Output: conditions_2.region, conditions_2.temperature, conditions_2.timec, PARTIAL last(conditions_2.highlow, conditions_2.timec), PARTIAL first(conditions_2.highlow, conditions_2.timec)
|
||||
Group Key: conditions_2.region, conditions_2.temperature, conditions_2.timec
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_2
|
||||
Output: conditions_2.region, conditions_2.temperature, conditions_2.timec, conditions_2.highlow
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_5_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_7_chunk, _dist_hyper_1_8_chunk
|
||||
Remote SQL: SELECT timec, region, temperature, highlow FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) ORDER BY region ASC NULLS LAST, temperature ASC NULLS LAST, timec ASC NULLS LAST
|
||||
(29 rows)
|
||||
|
||||
-- Mix of aggregates that push down and those that don't
|
||||
:PREFIX SELECT :GROUPING,
|
||||
@ -419,44 +403,40 @@ SET enable_partitionwise_aggregate = ON;
|
||||
bool_or(good_life),
|
||||
first(highlow, timec) as first_hl
|
||||
FROM :TEST_TABLE
|
||||
GROUP BY :GROUPING
|
||||
ORDER BY :GROUPING;
|
||||
QUERY PLAN
|
||||
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
GROUP BY :GROUPING, timec
|
||||
ORDER BY :GROUPING, timec;
|
||||
QUERY PLAN
|
||||
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Finalize GroupAggregate
|
||||
Output: region, min(allnull), max(temperature), (sum(temperature) + sum(humidity)), avg(humidity), round(stddev((humidity)::integer), 5), bit_and(bit_int), bit_or(bit_int), bool_and(good_life), every((temperature > '0'::double precision)), bool_or(good_life), first(highlow, timec)
|
||||
Group Key: region
|
||||
-> Sort
|
||||
Output: region, (PARTIAL min(allnull)), (PARTIAL max(temperature)), (PARTIAL sum(temperature)), (PARTIAL sum(humidity)), (PARTIAL avg(humidity)), (PARTIAL stddev((humidity)::integer)), (PARTIAL bit_and(bit_int)), (PARTIAL bit_or(bit_int)), (PARTIAL bool_and(good_life)), (PARTIAL every((temperature > '0'::double precision))), (PARTIAL bool_or(good_life)), (PARTIAL first(highlow, timec))
|
||||
Sort Key: region
|
||||
-> Custom Scan (AsyncAppend)
|
||||
Output: region, (PARTIAL min(allnull)), (PARTIAL max(temperature)), (PARTIAL sum(temperature)), (PARTIAL sum(humidity)), (PARTIAL avg(humidity)), (PARTIAL stddev((humidity)::integer)), (PARTIAL bit_and(bit_int)), (PARTIAL bit_or(bit_int)), (PARTIAL bool_and(good_life)), (PARTIAL every((temperature > '0'::double precision))), (PARTIAL bool_or(good_life)), (PARTIAL first(highlow, timec))
|
||||
-> Append
|
||||
-> Partial HashAggregate
|
||||
Output: conditions.region, PARTIAL min(conditions.allnull), PARTIAL max(conditions.temperature), PARTIAL sum(conditions.temperature), PARTIAL sum(conditions.humidity), PARTIAL avg(conditions.humidity), PARTIAL stddev((conditions.humidity)::integer), PARTIAL bit_and(conditions.bit_int), PARTIAL bit_or(conditions.bit_int), PARTIAL bool_and(conditions.good_life), PARTIAL every((conditions.temperature > '0'::double precision)), PARTIAL bool_or(conditions.good_life), PARTIAL first(conditions.highlow, conditions.timec)
|
||||
Group Key: conditions.region
|
||||
-> Custom Scan (DataNodeScan) on public.conditions
|
||||
Output: conditions.region, conditions.allnull, conditions.temperature, conditions.humidity, conditions.bit_int, conditions.good_life, conditions.highlow, conditions.timec
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_1_chunk, _dist_hyper_1_2_chunk, _dist_hyper_1_3_chunk, _dist_hyper_1_4_chunk
|
||||
Remote SQL: SELECT timec, region, temperature, humidity, allnull, highlow, bit_int, good_life FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4])
|
||||
-> Partial HashAggregate
|
||||
Output: conditions_1.region, PARTIAL min(conditions_1.allnull), PARTIAL max(conditions_1.temperature), PARTIAL sum(conditions_1.temperature), PARTIAL sum(conditions_1.humidity), PARTIAL avg(conditions_1.humidity), PARTIAL stddev((conditions_1.humidity)::integer), PARTIAL bit_and(conditions_1.bit_int), PARTIAL bit_or(conditions_1.bit_int), PARTIAL bool_and(conditions_1.good_life), PARTIAL every((conditions_1.temperature > '0'::double precision)), PARTIAL bool_or(conditions_1.good_life), PARTIAL first(conditions_1.highlow, conditions_1.timec)
|
||||
Group Key: conditions_1.region
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_1
|
||||
Output: conditions_1.region, conditions_1.allnull, conditions_1.temperature, conditions_1.humidity, conditions_1.bit_int, conditions_1.good_life, conditions_1.highlow, conditions_1.timec
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_9_chunk, _dist_hyper_1_10_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_12_chunk
|
||||
Remote SQL: SELECT timec, region, temperature, humidity, allnull, highlow, bit_int, good_life FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4])
|
||||
-> Partial HashAggregate
|
||||
Output: conditions_2.region, PARTIAL min(conditions_2.allnull), PARTIAL max(conditions_2.temperature), PARTIAL sum(conditions_2.temperature), PARTIAL sum(conditions_2.humidity), PARTIAL avg(conditions_2.humidity), PARTIAL stddev((conditions_2.humidity)::integer), PARTIAL bit_and(conditions_2.bit_int), PARTIAL bit_or(conditions_2.bit_int), PARTIAL bool_and(conditions_2.good_life), PARTIAL every((conditions_2.temperature > '0'::double precision)), PARTIAL bool_or(conditions_2.good_life), PARTIAL first(conditions_2.highlow, conditions_2.timec)
|
||||
Group Key: conditions_2.region
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_2
|
||||
Output: conditions_2.region, conditions_2.allnull, conditions_2.temperature, conditions_2.humidity, conditions_2.bit_int, conditions_2.good_life, conditions_2.highlow, conditions_2.timec
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_5_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_7_chunk, _dist_hyper_1_8_chunk
|
||||
Remote SQL: SELECT timec, region, temperature, humidity, allnull, highlow, bit_int, good_life FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4])
|
||||
(33 rows)
|
||||
Output: conditions.region, conditions.temperature, min(conditions.allnull), max(conditions.temperature), (sum(conditions.temperature) + sum(conditions.humidity)), avg(conditions.humidity), round(stddev((conditions.humidity)::integer), 5), bit_and(conditions.bit_int), bit_or(conditions.bit_int), bool_and(conditions.good_life), every((conditions.temperature > '0'::double precision)), bool_or(conditions.good_life), first(conditions.highlow, conditions.timec), conditions.timec
|
||||
Group Key: conditions.region, conditions.temperature, conditions.timec
|
||||
-> Merge Append
|
||||
Sort Key: conditions.region, conditions.temperature, conditions.timec
|
||||
-> Partial GroupAggregate
|
||||
Output: conditions.region, conditions.temperature, conditions.timec, PARTIAL min(conditions.allnull), PARTIAL max(conditions.temperature), PARTIAL sum(conditions.temperature), PARTIAL sum(conditions.humidity), PARTIAL avg(conditions.humidity), PARTIAL stddev((conditions.humidity)::integer), PARTIAL bit_and(conditions.bit_int), PARTIAL bit_or(conditions.bit_int), PARTIAL bool_and(conditions.good_life), PARTIAL every((conditions.temperature > '0'::double precision)), PARTIAL bool_or(conditions.good_life), PARTIAL first(conditions.highlow, conditions.timec)
|
||||
Group Key: conditions.region, conditions.temperature, conditions.timec
|
||||
-> Custom Scan (DataNodeScan) on public.conditions
|
||||
Output: conditions.region, conditions.temperature, conditions.timec, conditions.allnull, conditions.humidity, conditions.bit_int, conditions.good_life, conditions.highlow
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_1_chunk, _dist_hyper_1_2_chunk, _dist_hyper_1_3_chunk, _dist_hyper_1_4_chunk
|
||||
Remote SQL: SELECT timec, region, temperature, humidity, allnull, highlow, bit_int, good_life FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) ORDER BY region ASC NULLS LAST, temperature ASC NULLS LAST, timec ASC NULLS LAST
|
||||
-> Partial GroupAggregate
|
||||
Output: conditions_1.region, conditions_1.temperature, conditions_1.timec, PARTIAL min(conditions_1.allnull), PARTIAL max(conditions_1.temperature), PARTIAL sum(conditions_1.temperature), PARTIAL sum(conditions_1.humidity), PARTIAL avg(conditions_1.humidity), PARTIAL stddev((conditions_1.humidity)::integer), PARTIAL bit_and(conditions_1.bit_int), PARTIAL bit_or(conditions_1.bit_int), PARTIAL bool_and(conditions_1.good_life), PARTIAL every((conditions_1.temperature > '0'::double precision)), PARTIAL bool_or(conditions_1.good_life), PARTIAL first(conditions_1.highlow, conditions_1.timec)
|
||||
Group Key: conditions_1.region, conditions_1.temperature, conditions_1.timec
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_1
|
||||
Output: conditions_1.region, conditions_1.temperature, conditions_1.timec, conditions_1.allnull, conditions_1.humidity, conditions_1.bit_int, conditions_1.good_life, conditions_1.highlow
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_9_chunk, _dist_hyper_1_10_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_12_chunk
|
||||
Remote SQL: SELECT timec, region, temperature, humidity, allnull, highlow, bit_int, good_life FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) ORDER BY region ASC NULLS LAST, temperature ASC NULLS LAST, timec ASC NULLS LAST
|
||||
-> Partial GroupAggregate
|
||||
Output: conditions_2.region, conditions_2.temperature, conditions_2.timec, PARTIAL min(conditions_2.allnull), PARTIAL max(conditions_2.temperature), PARTIAL sum(conditions_2.temperature), PARTIAL sum(conditions_2.humidity), PARTIAL avg(conditions_2.humidity), PARTIAL stddev((conditions_2.humidity)::integer), PARTIAL bit_and(conditions_2.bit_int), PARTIAL bit_or(conditions_2.bit_int), PARTIAL bool_and(conditions_2.good_life), PARTIAL every((conditions_2.temperature > '0'::double precision)), PARTIAL bool_or(conditions_2.good_life), PARTIAL first(conditions_2.highlow, conditions_2.timec)
|
||||
Group Key: conditions_2.region, conditions_2.temperature, conditions_2.timec
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_2
|
||||
Output: conditions_2.region, conditions_2.temperature, conditions_2.timec, conditions_2.allnull, conditions_2.humidity, conditions_2.bit_int, conditions_2.good_life, conditions_2.highlow
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_5_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_7_chunk, _dist_hyper_1_8_chunk
|
||||
Remote SQL: SELECT timec, region, temperature, humidity, allnull, highlow, bit_int, good_life FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) ORDER BY region ASC NULLS LAST, temperature ASC NULLS LAST, timec ASC NULLS LAST
|
||||
(29 rows)
|
||||
|
||||
-- Full aggregate pushdown correctness check, compare location grouped query results with partionwise aggregates on and off
|
||||
\set GROUPING 'location'
|
||||
@ -477,10 +457,6 @@ SELECT format('\! diff %s %s', :'RESULTS_CONTROL2', :'RESULTS_TEST2') as "DIFF_C
|
||||
\gset
|
||||
--generate the results into two different files
|
||||
\set ECHO errors
|
||||
-- Note that some difference in output could happen here because
|
||||
-- queries include last(col, time) and first(col, time); there are
|
||||
-- multiple values for "col" that has the same timestamp, so the
|
||||
-- output depends on the order of arriving tuples.
|
||||
:DIFF_CMD2
|
||||
\c :TEST_DBNAME :ROLE_CLUSTER_SUPERUSER
|
||||
DROP DATABASE :DN_DBNAME_1;
|
||||
|
||||
@ -165,76 +165,70 @@ SET enable_partitionwise_aggregate = ON;
|
||||
last(temperature, timec) as last_temp,
|
||||
histogram(temperature, 0, 100, 1)
|
||||
FROM :TEST_TABLE
|
||||
GROUP BY :GROUPING
|
||||
ORDER BY :GROUPING;
|
||||
QUERY PLAN
|
||||
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Sort
|
||||
Output: location, (min(allnull)), (max(temperature)), ((sum(temperature) + sum(humidity))), (avg(humidity)), (round(stddev((humidity)::integer), 5)), (bit_and(bit_int)), (bit_or(bit_int)), (bool_and(good_life)), (every((temperature > '0'::double precision))), (bool_or(good_life)), (count(*)), (count(temperature)), (count(allnull)), (round((corr(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((covar_pop(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((covar_samp(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_avgx(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_avgy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_count(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_intercept(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_r2(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_slope(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_sxx(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_sxy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_syy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round(stddev((temperature)::integer), 5)), (round(stddev_pop((temperature)::integer), 5)), (round(stddev_samp((temperature)::integer), 5)), (round(variance((temperature)::integer), 5)), (round(var_pop((temperature)::integer), 5)), (round(var_samp((temperature)::integer), 5)), (last(temperature, timec)), (histogram(temperature, '0'::double precision, '100'::double precision, 1))
|
||||
Sort Key: location
|
||||
-> Custom Scan (AsyncAppend)
|
||||
Output: location, (min(allnull)), (max(temperature)), ((sum(temperature) + sum(humidity))), (avg(humidity)), (round(stddev((humidity)::integer), 5)), (bit_and(bit_int)), (bit_or(bit_int)), (bool_and(good_life)), (every((temperature > '0'::double precision))), (bool_or(good_life)), (count(*)), (count(temperature)), (count(allnull)), (round((corr(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((covar_pop(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((covar_samp(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_avgx(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_avgy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_count(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_intercept(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_r2(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_slope(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_sxx(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_sxy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_syy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round(stddev((temperature)::integer), 5)), (round(stddev_pop((temperature)::integer), 5)), (round(stddev_samp((temperature)::integer), 5)), (round(variance((temperature)::integer), 5)), (round(var_pop((temperature)::integer), 5)), (round(var_samp((temperature)::integer), 5)), (last(temperature, timec)), (histogram(temperature, '0'::double precision, '100'::double precision, 1))
|
||||
-> Append
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: conditions.location, (min(conditions.allnull)), (max(conditions.temperature)), ((sum(conditions.temperature) + sum(conditions.humidity))), (avg(conditions.humidity)), (round(stddev((conditions.humidity)::integer), 5)), (bit_and(conditions.bit_int)), (bit_or(conditions.bit_int)), (bool_and(conditions.good_life)), (every((conditions.temperature > '0'::double precision))), (bool_or(conditions.good_life)), (count(*)), (count(conditions.temperature)), (count(conditions.allnull)), (round((corr(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((covar_pop(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((covar_samp(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((regr_avgx(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((regr_avgy(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((regr_count(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((regr_intercept(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((regr_r2(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((regr_slope(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((regr_sxx(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((regr_sxy(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((regr_syy(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round(stddev((conditions.temperature)::integer), 5)), (round(stddev_pop((conditions.temperature)::integer), 5)), (round(stddev_samp((conditions.temperature)::integer), 5)), (round(variance((conditions.temperature)::integer), 5)), (round(var_pop((conditions.temperature)::integer), 5)), (round(var_samp((conditions.temperature)::integer), 5)), (last(conditions.temperature, conditions.timec)), (histogram(conditions.temperature, '0'::double precision, '100'::double precision, 1))
|
||||
Relations: Aggregate on (public.conditions)
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_1_chunk, _dist_hyper_1_2_chunk, _dist_hyper_1_3_chunk, _dist_hyper_1_4_chunk
|
||||
Remote SQL: SELECT location, min(allnull), max(temperature), (sum(temperature) + sum(humidity)), avg(humidity), round(stddev(humidity::integer), 5), bit_and(bit_int), bit_or(bit_int), bool_and(good_life), every((temperature > 0::double precision)), bool_or(good_life), count(*), count(temperature), count(allnull), round(corr(temperature::integer, humidity::integer)::numeric, 5), round(covar_pop(temperature::integer, humidity::integer)::numeric, 5), round(covar_samp(temperature::integer, humidity::integer)::numeric, 5), round(regr_avgx(temperature::integer, humidity::integer)::numeric, 5), round(regr_avgy(temperature::integer, humidity::integer)::numeric, 5), round(regr_count(temperature::integer, humidity::integer)::numeric, 5), round(regr_intercept(temperature::integer, humidity::integer)::numeric, 5), round(regr_r2(temperature::integer, humidity::integer)::numeric, 5), round(regr_slope(temperature::integer, humidity::integer)::numeric, 5), round(regr_sxx(temperature::integer, humidity::integer)::numeric, 5), round(regr_sxy(temperature::integer, humidity::integer)::numeric, 5), round(regr_syy(temperature::integer, humidity::integer)::numeric, 5), round(stddev(temperature::integer), 5), round(stddev_pop(temperature::integer), 5), round(stddev_samp(temperature::integer), 5), round(variance(temperature::integer), 5), round(var_pop(temperature::integer), 5), round(var_samp(temperature::integer), 5), public.last(temperature, timec), public.histogram(temperature, 0::double precision, 100::double precision, 1) FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) GROUP BY 1
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: conditions_1.location, (min(conditions_1.allnull)), (max(conditions_1.temperature)), ((sum(conditions_1.temperature) + sum(conditions_1.humidity))), (avg(conditions_1.humidity)), (round(stddev((conditions_1.humidity)::integer), 5)), (bit_and(conditions_1.bit_int)), (bit_or(conditions_1.bit_int)), (bool_and(conditions_1.good_life)), (every((conditions_1.temperature > '0'::double precision))), (bool_or(conditions_1.good_life)), (count(*)), (count(conditions_1.temperature)), (count(conditions_1.allnull)), (round((corr(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((covar_pop(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((covar_samp(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((regr_avgx(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((regr_avgy(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((regr_count(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((regr_intercept(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((regr_r2(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((regr_slope(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((regr_sxx(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((regr_sxy(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((regr_syy(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round(stddev((conditions_1.temperature)::integer), 5)), (round(stddev_pop((conditions_1.temperature)::integer), 5)), (round(stddev_samp((conditions_1.temperature)::integer), 5)), (round(variance((conditions_1.temperature)::integer), 5)), (round(var_pop((conditions_1.temperature)::integer), 5)), (round(var_samp((conditions_1.temperature)::integer), 5)), (last(conditions_1.temperature, conditions_1.timec)), (histogram(conditions_1.temperature, '0'::double precision, '100'::double precision, 1))
|
||||
Relations: Aggregate on (public.conditions)
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_9_chunk, _dist_hyper_1_10_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_12_chunk
|
||||
Remote SQL: SELECT location, min(allnull), max(temperature), (sum(temperature) + sum(humidity)), avg(humidity), round(stddev(humidity::integer), 5), bit_and(bit_int), bit_or(bit_int), bool_and(good_life), every((temperature > 0::double precision)), bool_or(good_life), count(*), count(temperature), count(allnull), round(corr(temperature::integer, humidity::integer)::numeric, 5), round(covar_pop(temperature::integer, humidity::integer)::numeric, 5), round(covar_samp(temperature::integer, humidity::integer)::numeric, 5), round(regr_avgx(temperature::integer, humidity::integer)::numeric, 5), round(regr_avgy(temperature::integer, humidity::integer)::numeric, 5), round(regr_count(temperature::integer, humidity::integer)::numeric, 5), round(regr_intercept(temperature::integer, humidity::integer)::numeric, 5), round(regr_r2(temperature::integer, humidity::integer)::numeric, 5), round(regr_slope(temperature::integer, humidity::integer)::numeric, 5), round(regr_sxx(temperature::integer, humidity::integer)::numeric, 5), round(regr_sxy(temperature::integer, humidity::integer)::numeric, 5), round(regr_syy(temperature::integer, humidity::integer)::numeric, 5), round(stddev(temperature::integer), 5), round(stddev_pop(temperature::integer), 5), round(stddev_samp(temperature::integer), 5), round(variance(temperature::integer), 5), round(var_pop(temperature::integer), 5), round(var_samp(temperature::integer), 5), public.last(temperature, timec), public.histogram(temperature, 0::double precision, 100::double precision, 1) FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) GROUP BY 1
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: conditions_2.location, (min(conditions_2.allnull)), (max(conditions_2.temperature)), ((sum(conditions_2.temperature) + sum(conditions_2.humidity))), (avg(conditions_2.humidity)), (round(stddev((conditions_2.humidity)::integer), 5)), (bit_and(conditions_2.bit_int)), (bit_or(conditions_2.bit_int)), (bool_and(conditions_2.good_life)), (every((conditions_2.temperature > '0'::double precision))), (bool_or(conditions_2.good_life)), (count(*)), (count(conditions_2.temperature)), (count(conditions_2.allnull)), (round((corr(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((covar_pop(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((covar_samp(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((regr_avgx(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((regr_avgy(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((regr_count(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((regr_intercept(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((regr_r2(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((regr_slope(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((regr_sxx(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((regr_sxy(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((regr_syy(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round(stddev((conditions_2.temperature)::integer), 5)), (round(stddev_pop((conditions_2.temperature)::integer), 5)), (round(stddev_samp((conditions_2.temperature)::integer), 5)), (round(variance((conditions_2.temperature)::integer), 5)), (round(var_pop((conditions_2.temperature)::integer), 5)), (round(var_samp((conditions_2.temperature)::integer), 5)), (last(conditions_2.temperature, conditions_2.timec)), (histogram(conditions_2.temperature, '0'::double precision, '100'::double precision, 1))
|
||||
Relations: Aggregate on (public.conditions)
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_5_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_7_chunk, _dist_hyper_1_8_chunk
|
||||
Remote SQL: SELECT location, min(allnull), max(temperature), (sum(temperature) + sum(humidity)), avg(humidity), round(stddev(humidity::integer), 5), bit_and(bit_int), bit_or(bit_int), bool_and(good_life), every((temperature > 0::double precision)), bool_or(good_life), count(*), count(temperature), count(allnull), round(corr(temperature::integer, humidity::integer)::numeric, 5), round(covar_pop(temperature::integer, humidity::integer)::numeric, 5), round(covar_samp(temperature::integer, humidity::integer)::numeric, 5), round(regr_avgx(temperature::integer, humidity::integer)::numeric, 5), round(regr_avgy(temperature::integer, humidity::integer)::numeric, 5), round(regr_count(temperature::integer, humidity::integer)::numeric, 5), round(regr_intercept(temperature::integer, humidity::integer)::numeric, 5), round(regr_r2(temperature::integer, humidity::integer)::numeric, 5), round(regr_slope(temperature::integer, humidity::integer)::numeric, 5), round(regr_sxx(temperature::integer, humidity::integer)::numeric, 5), round(regr_sxy(temperature::integer, humidity::integer)::numeric, 5), round(regr_syy(temperature::integer, humidity::integer)::numeric, 5), round(stddev(temperature::integer), 5), round(stddev_pop(temperature::integer), 5), round(stddev_samp(temperature::integer), 5), round(variance(temperature::integer), 5), round(var_pop(temperature::integer), 5), round(var_samp(temperature::integer), 5), public.last(temperature, timec), public.histogram(temperature, 0::double precision, 100::double precision, 1) FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) GROUP BY 1
|
||||
(24 rows)
|
||||
GROUP BY :GROUPING, timec
|
||||
ORDER BY :GROUPING, timec;
|
||||
QUERY PLAN
|
||||
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Custom Scan (AsyncAppend)
|
||||
Output: location, (min(allnull)), (max(temperature)), ((sum(temperature) + sum(humidity))), (avg(humidity)), (round(stddev((humidity)::integer), 5)), (bit_and(bit_int)), (bit_or(bit_int)), (bool_and(good_life)), (every((temperature > '0'::double precision))), (bool_or(good_life)), (count(*)), (count(temperature)), (count(allnull)), (round((corr(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((covar_pop(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((covar_samp(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_avgx(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_avgy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_count(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_intercept(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_r2(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_slope(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_sxx(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_sxy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_syy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round(stddev((temperature)::integer), 5)), (round(stddev_pop((temperature)::integer), 5)), (round(stddev_samp((temperature)::integer), 5)), (round(variance((temperature)::integer), 5)), (round(var_pop((temperature)::integer), 5)), (round(var_samp((temperature)::integer), 5)), (last(temperature, timec)), (histogram(temperature, '0'::double precision, '100'::double precision, 1)), timec
|
||||
-> Merge Append
|
||||
Sort Key: conditions.location, conditions.timec
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: conditions.location, (min(conditions.allnull)), (max(conditions.temperature)), ((sum(conditions.temperature) + sum(conditions.humidity))), (avg(conditions.humidity)), (round(stddev((conditions.humidity)::integer), 5)), (bit_and(conditions.bit_int)), (bit_or(conditions.bit_int)), (bool_and(conditions.good_life)), (every((conditions.temperature > '0'::double precision))), (bool_or(conditions.good_life)), (count(*)), (count(conditions.temperature)), (count(conditions.allnull)), (round((corr(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((covar_pop(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((covar_samp(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((regr_avgx(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((regr_avgy(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((regr_count(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((regr_intercept(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((regr_r2(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((regr_slope(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((regr_sxx(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((regr_sxy(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((regr_syy(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round(stddev((conditions.temperature)::integer), 5)), (round(stddev_pop((conditions.temperature)::integer), 5)), (round(stddev_samp((conditions.temperature)::integer), 5)), (round(variance((conditions.temperature)::integer), 5)), (round(var_pop((conditions.temperature)::integer), 5)), (round(var_samp((conditions.temperature)::integer), 5)), (last(conditions.temperature, conditions.timec)), (histogram(conditions.temperature, '0'::double precision, '100'::double precision, 1)), conditions.timec
|
||||
Relations: Aggregate on (public.conditions)
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_1_chunk, _dist_hyper_1_2_chunk, _dist_hyper_1_3_chunk, _dist_hyper_1_4_chunk
|
||||
Remote SQL: SELECT location, min(allnull), max(temperature), (sum(temperature) + sum(humidity)), avg(humidity), round(stddev(humidity::integer), 5), bit_and(bit_int), bit_or(bit_int), bool_and(good_life), every((temperature > 0::double precision)), bool_or(good_life), count(*), count(temperature), count(allnull), round(corr(temperature::integer, humidity::integer)::numeric, 5), round(covar_pop(temperature::integer, humidity::integer)::numeric, 5), round(covar_samp(temperature::integer, humidity::integer)::numeric, 5), round(regr_avgx(temperature::integer, humidity::integer)::numeric, 5), round(regr_avgy(temperature::integer, humidity::integer)::numeric, 5), round(regr_count(temperature::integer, humidity::integer)::numeric, 5), round(regr_intercept(temperature::integer, humidity::integer)::numeric, 5), round(regr_r2(temperature::integer, humidity::integer)::numeric, 5), round(regr_slope(temperature::integer, humidity::integer)::numeric, 5), round(regr_sxx(temperature::integer, humidity::integer)::numeric, 5), round(regr_sxy(temperature::integer, humidity::integer)::numeric, 5), round(regr_syy(temperature::integer, humidity::integer)::numeric, 5), round(stddev(temperature::integer), 5), round(stddev_pop(temperature::integer), 5), round(stddev_samp(temperature::integer), 5), round(variance(temperature::integer), 5), round(var_pop(temperature::integer), 5), round(var_samp(temperature::integer), 5), public.last(temperature, timec), public.histogram(temperature, 0::double precision, 100::double precision, 1), timec FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) GROUP BY 1, 35 ORDER BY location ASC NULLS LAST, timec ASC NULLS LAST
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: conditions_1.location, (min(conditions_1.allnull)), (max(conditions_1.temperature)), ((sum(conditions_1.temperature) + sum(conditions_1.humidity))), (avg(conditions_1.humidity)), (round(stddev((conditions_1.humidity)::integer), 5)), (bit_and(conditions_1.bit_int)), (bit_or(conditions_1.bit_int)), (bool_and(conditions_1.good_life)), (every((conditions_1.temperature > '0'::double precision))), (bool_or(conditions_1.good_life)), (count(*)), (count(conditions_1.temperature)), (count(conditions_1.allnull)), (round((corr(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((covar_pop(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((covar_samp(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((regr_avgx(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((regr_avgy(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((regr_count(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((regr_intercept(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((regr_r2(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((regr_slope(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((regr_sxx(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((regr_sxy(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((regr_syy(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round(stddev((conditions_1.temperature)::integer), 5)), (round(stddev_pop((conditions_1.temperature)::integer), 5)), (round(stddev_samp((conditions_1.temperature)::integer), 5)), (round(variance((conditions_1.temperature)::integer), 5)), (round(var_pop((conditions_1.temperature)::integer), 5)), (round(var_samp((conditions_1.temperature)::integer), 5)), (last(conditions_1.temperature, conditions_1.timec)), (histogram(conditions_1.temperature, '0'::double precision, '100'::double precision, 1)), conditions_1.timec
|
||||
Relations: Aggregate on (public.conditions)
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_9_chunk, _dist_hyper_1_10_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_12_chunk
|
||||
Remote SQL: SELECT location, min(allnull), max(temperature), (sum(temperature) + sum(humidity)), avg(humidity), round(stddev(humidity::integer), 5), bit_and(bit_int), bit_or(bit_int), bool_and(good_life), every((temperature > 0::double precision)), bool_or(good_life), count(*), count(temperature), count(allnull), round(corr(temperature::integer, humidity::integer)::numeric, 5), round(covar_pop(temperature::integer, humidity::integer)::numeric, 5), round(covar_samp(temperature::integer, humidity::integer)::numeric, 5), round(regr_avgx(temperature::integer, humidity::integer)::numeric, 5), round(regr_avgy(temperature::integer, humidity::integer)::numeric, 5), round(regr_count(temperature::integer, humidity::integer)::numeric, 5), round(regr_intercept(temperature::integer, humidity::integer)::numeric, 5), round(regr_r2(temperature::integer, humidity::integer)::numeric, 5), round(regr_slope(temperature::integer, humidity::integer)::numeric, 5), round(regr_sxx(temperature::integer, humidity::integer)::numeric, 5), round(regr_sxy(temperature::integer, humidity::integer)::numeric, 5), round(regr_syy(temperature::integer, humidity::integer)::numeric, 5), round(stddev(temperature::integer), 5), round(stddev_pop(temperature::integer), 5), round(stddev_samp(temperature::integer), 5), round(variance(temperature::integer), 5), round(var_pop(temperature::integer), 5), round(var_samp(temperature::integer), 5), public.last(temperature, timec), public.histogram(temperature, 0::double precision, 100::double precision, 1), timec FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) GROUP BY 1, 35 ORDER BY location ASC NULLS LAST, timec ASC NULLS LAST
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: conditions_2.location, (min(conditions_2.allnull)), (max(conditions_2.temperature)), ((sum(conditions_2.temperature) + sum(conditions_2.humidity))), (avg(conditions_2.humidity)), (round(stddev((conditions_2.humidity)::integer), 5)), (bit_and(conditions_2.bit_int)), (bit_or(conditions_2.bit_int)), (bool_and(conditions_2.good_life)), (every((conditions_2.temperature > '0'::double precision))), (bool_or(conditions_2.good_life)), (count(*)), (count(conditions_2.temperature)), (count(conditions_2.allnull)), (round((corr(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((covar_pop(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((covar_samp(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((regr_avgx(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((regr_avgy(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((regr_count(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((regr_intercept(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((regr_r2(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((regr_slope(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((regr_sxx(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((regr_sxy(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((regr_syy(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round(stddev((conditions_2.temperature)::integer), 5)), (round(stddev_pop((conditions_2.temperature)::integer), 5)), (round(stddev_samp((conditions_2.temperature)::integer), 5)), (round(variance((conditions_2.temperature)::integer), 5)), (round(var_pop((conditions_2.temperature)::integer), 5)), (round(var_samp((conditions_2.temperature)::integer), 5)), (last(conditions_2.temperature, conditions_2.timec)), (histogram(conditions_2.temperature, '0'::double precision, '100'::double precision, 1)), conditions_2.timec
|
||||
Relations: Aggregate on (public.conditions)
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_5_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_7_chunk, _dist_hyper_1_8_chunk
|
||||
Remote SQL: SELECT location, min(allnull), max(temperature), (sum(temperature) + sum(humidity)), avg(humidity), round(stddev(humidity::integer), 5), bit_and(bit_int), bit_or(bit_int), bool_and(good_life), every((temperature > 0::double precision)), bool_or(good_life), count(*), count(temperature), count(allnull), round(corr(temperature::integer, humidity::integer)::numeric, 5), round(covar_pop(temperature::integer, humidity::integer)::numeric, 5), round(covar_samp(temperature::integer, humidity::integer)::numeric, 5), round(regr_avgx(temperature::integer, humidity::integer)::numeric, 5), round(regr_avgy(temperature::integer, humidity::integer)::numeric, 5), round(regr_count(temperature::integer, humidity::integer)::numeric, 5), round(regr_intercept(temperature::integer, humidity::integer)::numeric, 5), round(regr_r2(temperature::integer, humidity::integer)::numeric, 5), round(regr_slope(temperature::integer, humidity::integer)::numeric, 5), round(regr_sxx(temperature::integer, humidity::integer)::numeric, 5), round(regr_sxy(temperature::integer, humidity::integer)::numeric, 5), round(regr_syy(temperature::integer, humidity::integer)::numeric, 5), round(stddev(temperature::integer), 5), round(stddev_pop(temperature::integer), 5), round(stddev_samp(temperature::integer), 5), round(variance(temperature::integer), 5), round(var_pop(temperature::integer), 5), round(var_samp(temperature::integer), 5), public.last(temperature, timec), public.histogram(temperature, 0::double precision, 100::double precision, 1), timec FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) GROUP BY 1, 35 ORDER BY location ASC NULLS LAST, timec ASC NULLS LAST
|
||||
(22 rows)
|
||||
|
||||
-- Aggregates on custom types are not yet pushed down
|
||||
:PREFIX SELECT :GROUPING,
|
||||
last(highlow, timec) as last_hl,
|
||||
first(highlow, timec) as first_hl
|
||||
FROM :TEST_TABLE
|
||||
GROUP BY :GROUPING
|
||||
ORDER BY :GROUPING;
|
||||
QUERY PLAN
|
||||
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Sort
|
||||
Output: location, (last(highlow, timec)), (first(highlow, timec))
|
||||
Sort Key: location
|
||||
-> Custom Scan (AsyncAppend)
|
||||
Output: location, (last(highlow, timec)), (first(highlow, timec))
|
||||
-> Append
|
||||
-> HashAggregate
|
||||
Output: conditions.location, last(conditions.highlow, conditions.timec), first(conditions.highlow, conditions.timec)
|
||||
Group Key: conditions.location
|
||||
-> Custom Scan (DataNodeScan) on public.conditions
|
||||
Output: conditions.location, conditions.highlow, conditions.timec
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_1_chunk, _dist_hyper_1_2_chunk, _dist_hyper_1_3_chunk, _dist_hyper_1_4_chunk
|
||||
Remote SQL: SELECT timec, location, highlow FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4])
|
||||
-> HashAggregate
|
||||
Output: conditions_1.location, last(conditions_1.highlow, conditions_1.timec), first(conditions_1.highlow, conditions_1.timec)
|
||||
Group Key: conditions_1.location
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_1
|
||||
Output: conditions_1.location, conditions_1.highlow, conditions_1.timec
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_9_chunk, _dist_hyper_1_10_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_12_chunk
|
||||
Remote SQL: SELECT timec, location, highlow FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4])
|
||||
-> HashAggregate
|
||||
Output: conditions_2.location, last(conditions_2.highlow, conditions_2.timec), first(conditions_2.highlow, conditions_2.timec)
|
||||
Group Key: conditions_2.location
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_2
|
||||
Output: conditions_2.location, conditions_2.highlow, conditions_2.timec
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_5_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_7_chunk, _dist_hyper_1_8_chunk
|
||||
Remote SQL: SELECT timec, location, highlow FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4])
|
||||
(30 rows)
|
||||
GROUP BY :GROUPING, timec
|
||||
ORDER BY :GROUPING, timec;
|
||||
QUERY PLAN
|
||||
-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Merge Append
|
||||
Sort Key: conditions.location, conditions.timec
|
||||
-> GroupAggregate
|
||||
Output: conditions.location, last(conditions.highlow, conditions.timec), first(conditions.highlow, conditions.timec), conditions.timec
|
||||
Group Key: conditions.location, conditions.timec
|
||||
-> Custom Scan (DataNodeScan) on public.conditions
|
||||
Output: conditions.location, conditions.timec, conditions.highlow
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_1_chunk, _dist_hyper_1_2_chunk, _dist_hyper_1_3_chunk, _dist_hyper_1_4_chunk
|
||||
Remote SQL: SELECT timec, location, highlow FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) ORDER BY location ASC NULLS LAST, timec ASC NULLS LAST
|
||||
-> GroupAggregate
|
||||
Output: conditions_1.location, last(conditions_1.highlow, conditions_1.timec), first(conditions_1.highlow, conditions_1.timec), conditions_1.timec
|
||||
Group Key: conditions_1.location, conditions_1.timec
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_1
|
||||
Output: conditions_1.location, conditions_1.timec, conditions_1.highlow
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_9_chunk, _dist_hyper_1_10_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_12_chunk
|
||||
Remote SQL: SELECT timec, location, highlow FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) ORDER BY location ASC NULLS LAST, timec ASC NULLS LAST
|
||||
-> GroupAggregate
|
||||
Output: conditions_2.location, last(conditions_2.highlow, conditions_2.timec), first(conditions_2.highlow, conditions_2.timec), conditions_2.timec
|
||||
Group Key: conditions_2.location, conditions_2.timec
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_2
|
||||
Output: conditions_2.location, conditions_2.timec, conditions_2.highlow
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_5_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_7_chunk, _dist_hyper_1_8_chunk
|
||||
Remote SQL: SELECT timec, location, highlow FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) ORDER BY location ASC NULLS LAST, timec ASC NULLS LAST
|
||||
(26 rows)
|
||||
|
||||
-- Mix of aggregates that push down and those that don't
|
||||
:PREFIX SELECT :GROUPING,
|
||||
@ -250,43 +244,39 @@ SET enable_partitionwise_aggregate = ON;
|
||||
bool_or(good_life),
|
||||
first(highlow, timec) as first_hl
|
||||
FROM :TEST_TABLE
|
||||
GROUP BY :GROUPING
|
||||
ORDER BY :GROUPING;
|
||||
QUERY PLAN
|
||||
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Sort
|
||||
Output: location, (min(allnull)), (max(temperature)), ((sum(temperature) + sum(humidity))), (avg(humidity)), (round(stddev((humidity)::integer), 5)), (bit_and(bit_int)), (bit_or(bit_int)), (bool_and(good_life)), (every((temperature > '0'::double precision))), (bool_or(good_life)), (first(highlow, timec))
|
||||
Sort Key: location
|
||||
-> Custom Scan (AsyncAppend)
|
||||
Output: location, (min(allnull)), (max(temperature)), ((sum(temperature) + sum(humidity))), (avg(humidity)), (round(stddev((humidity)::integer), 5)), (bit_and(bit_int)), (bit_or(bit_int)), (bool_and(good_life)), (every((temperature > '0'::double precision))), (bool_or(good_life)), (first(highlow, timec))
|
||||
-> Append
|
||||
-> HashAggregate
|
||||
Output: conditions.location, min(conditions.allnull), max(conditions.temperature), (sum(conditions.temperature) + sum(conditions.humidity)), avg(conditions.humidity), round(stddev((conditions.humidity)::integer), 5), bit_and(conditions.bit_int), bit_or(conditions.bit_int), bool_and(conditions.good_life), every((conditions.temperature > '0'::double precision)), bool_or(conditions.good_life), first(conditions.highlow, conditions.timec)
|
||||
Group Key: conditions.location
|
||||
-> Custom Scan (DataNodeScan) on public.conditions
|
||||
Output: conditions.location, conditions.allnull, conditions.temperature, conditions.humidity, conditions.bit_int, conditions.good_life, conditions.highlow, conditions.timec
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_1_chunk, _dist_hyper_1_2_chunk, _dist_hyper_1_3_chunk, _dist_hyper_1_4_chunk
|
||||
Remote SQL: SELECT timec, location, temperature, humidity, allnull, highlow, bit_int, good_life FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4])
|
||||
-> HashAggregate
|
||||
Output: conditions_1.location, min(conditions_1.allnull), max(conditions_1.temperature), (sum(conditions_1.temperature) + sum(conditions_1.humidity)), avg(conditions_1.humidity), round(stddev((conditions_1.humidity)::integer), 5), bit_and(conditions_1.bit_int), bit_or(conditions_1.bit_int), bool_and(conditions_1.good_life), every((conditions_1.temperature > '0'::double precision)), bool_or(conditions_1.good_life), first(conditions_1.highlow, conditions_1.timec)
|
||||
Group Key: conditions_1.location
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_1
|
||||
Output: conditions_1.location, conditions_1.allnull, conditions_1.temperature, conditions_1.humidity, conditions_1.bit_int, conditions_1.good_life, conditions_1.highlow, conditions_1.timec
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_9_chunk, _dist_hyper_1_10_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_12_chunk
|
||||
Remote SQL: SELECT timec, location, temperature, humidity, allnull, highlow, bit_int, good_life FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4])
|
||||
-> HashAggregate
|
||||
Output: conditions_2.location, min(conditions_2.allnull), max(conditions_2.temperature), (sum(conditions_2.temperature) + sum(conditions_2.humidity)), avg(conditions_2.humidity), round(stddev((conditions_2.humidity)::integer), 5), bit_and(conditions_2.bit_int), bit_or(conditions_2.bit_int), bool_and(conditions_2.good_life), every((conditions_2.temperature > '0'::double precision)), bool_or(conditions_2.good_life), first(conditions_2.highlow, conditions_2.timec)
|
||||
Group Key: conditions_2.location
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_2
|
||||
Output: conditions_2.location, conditions_2.allnull, conditions_2.temperature, conditions_2.humidity, conditions_2.bit_int, conditions_2.good_life, conditions_2.highlow, conditions_2.timec
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_5_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_7_chunk, _dist_hyper_1_8_chunk
|
||||
Remote SQL: SELECT timec, location, temperature, humidity, allnull, highlow, bit_int, good_life FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4])
|
||||
(30 rows)
|
||||
GROUP BY :GROUPING, timec
|
||||
ORDER BY :GROUPING, timec;
|
||||
QUERY PLAN
|
||||
---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Merge Append
|
||||
Sort Key: conditions.location, conditions.timec
|
||||
-> GroupAggregate
|
||||
Output: conditions.location, min(conditions.allnull), max(conditions.temperature), (sum(conditions.temperature) + sum(conditions.humidity)), avg(conditions.humidity), round(stddev((conditions.humidity)::integer), 5), bit_and(conditions.bit_int), bit_or(conditions.bit_int), bool_and(conditions.good_life), every((conditions.temperature > '0'::double precision)), bool_or(conditions.good_life), first(conditions.highlow, conditions.timec), conditions.timec
|
||||
Group Key: conditions.location, conditions.timec
|
||||
-> Custom Scan (DataNodeScan) on public.conditions
|
||||
Output: conditions.location, conditions.timec, conditions.allnull, conditions.temperature, conditions.humidity, conditions.bit_int, conditions.good_life, conditions.highlow
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_1_chunk, _dist_hyper_1_2_chunk, _dist_hyper_1_3_chunk, _dist_hyper_1_4_chunk
|
||||
Remote SQL: SELECT timec, location, temperature, humidity, allnull, highlow, bit_int, good_life FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) ORDER BY location ASC NULLS LAST, timec ASC NULLS LAST
|
||||
-> GroupAggregate
|
||||
Output: conditions_1.location, min(conditions_1.allnull), max(conditions_1.temperature), (sum(conditions_1.temperature) + sum(conditions_1.humidity)), avg(conditions_1.humidity), round(stddev((conditions_1.humidity)::integer), 5), bit_and(conditions_1.bit_int), bit_or(conditions_1.bit_int), bool_and(conditions_1.good_life), every((conditions_1.temperature > '0'::double precision)), bool_or(conditions_1.good_life), first(conditions_1.highlow, conditions_1.timec), conditions_1.timec
|
||||
Group Key: conditions_1.location, conditions_1.timec
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_1
|
||||
Output: conditions_1.location, conditions_1.timec, conditions_1.allnull, conditions_1.temperature, conditions_1.humidity, conditions_1.bit_int, conditions_1.good_life, conditions_1.highlow
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_9_chunk, _dist_hyper_1_10_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_12_chunk
|
||||
Remote SQL: SELECT timec, location, temperature, humidity, allnull, highlow, bit_int, good_life FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) ORDER BY location ASC NULLS LAST, timec ASC NULLS LAST
|
||||
-> GroupAggregate
|
||||
Output: conditions_2.location, min(conditions_2.allnull), max(conditions_2.temperature), (sum(conditions_2.temperature) + sum(conditions_2.humidity)), avg(conditions_2.humidity), round(stddev((conditions_2.humidity)::integer), 5), bit_and(conditions_2.bit_int), bit_or(conditions_2.bit_int), bool_and(conditions_2.good_life), every((conditions_2.temperature > '0'::double precision)), bool_or(conditions_2.good_life), first(conditions_2.highlow, conditions_2.timec), conditions_2.timec
|
||||
Group Key: conditions_2.location, conditions_2.timec
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_2
|
||||
Output: conditions_2.location, conditions_2.timec, conditions_2.allnull, conditions_2.temperature, conditions_2.humidity, conditions_2.bit_int, conditions_2.good_life, conditions_2.highlow
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_5_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_7_chunk, _dist_hyper_1_8_chunk
|
||||
Remote SQL: SELECT timec, location, temperature, humidity, allnull, highlow, bit_int, good_life FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) ORDER BY location ASC NULLS LAST, timec ASC NULLS LAST
|
||||
(26 rows)
|
||||
|
||||
\set GROUPING 'region'
|
||||
\set GROUPING 'region, temperature'
|
||||
\ir 'include/aggregate_queries.sql'
|
||||
-- This file and its contents are licensed under the Timescale License.
|
||||
-- Please see the included NOTICE for copyright information and
|
||||
@ -328,82 +318,76 @@ SET enable_partitionwise_aggregate = ON;
|
||||
last(temperature, timec) as last_temp,
|
||||
histogram(temperature, 0, 100, 1)
|
||||
FROM :TEST_TABLE
|
||||
GROUP BY :GROUPING
|
||||
ORDER BY :GROUPING;
|
||||
QUERY PLAN
|
||||
---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
GROUP BY :GROUPING, timec
|
||||
ORDER BY :GROUPING, timec;
|
||||
QUERY PLAN
|
||||
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Finalize GroupAggregate
|
||||
Output: region, min(allnull), max(temperature), (sum(temperature) + sum(humidity)), avg(humidity), round(stddev((humidity)::integer), 5), bit_and(bit_int), bit_or(bit_int), bool_and(good_life), every((temperature > '0'::double precision)), bool_or(good_life), count(*), count(temperature), count(allnull), round((corr(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((covar_pop(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((covar_samp(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_avgx(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_avgy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_count(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_intercept(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_r2(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_slope(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_sxx(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_sxy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_syy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round(stddev((temperature)::integer), 5), round(stddev_pop((temperature)::integer), 5), round(stddev_samp((temperature)::integer), 5), round(variance((temperature)::integer), 5), round(var_pop((temperature)::integer), 5), round(var_samp((temperature)::integer), 5), last(temperature, timec), histogram(temperature, '0'::double precision, '100'::double precision, 1)
|
||||
Group Key: region
|
||||
-> Sort
|
||||
Output: region, (PARTIAL min(allnull)), (PARTIAL max(temperature)), (PARTIAL sum(temperature)), (PARTIAL sum(humidity)), (PARTIAL avg(humidity)), (PARTIAL stddev((humidity)::integer)), (PARTIAL bit_and(bit_int)), (PARTIAL bit_or(bit_int)), (PARTIAL bool_and(good_life)), (PARTIAL every((temperature > '0'::double precision))), (PARTIAL bool_or(good_life)), (PARTIAL count(*)), (PARTIAL count(temperature)), (PARTIAL count(allnull)), (PARTIAL corr(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL covar_pop(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL covar_samp(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_avgx(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_avgy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_count(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_intercept(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_r2(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_slope(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_sxx(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_sxy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_syy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL stddev((temperature)::integer)), (PARTIAL stddev_pop((temperature)::integer)), (PARTIAL stddev_samp((temperature)::integer)), (PARTIAL variance((temperature)::integer)), (PARTIAL var_pop((temperature)::integer)), (PARTIAL var_samp((temperature)::integer)), (PARTIAL last(temperature, timec)), (PARTIAL histogram(temperature, '0'::double precision, '100'::double precision, 1))
|
||||
Sort Key: region
|
||||
-> Custom Scan (AsyncAppend)
|
||||
Output: region, (PARTIAL min(allnull)), (PARTIAL max(temperature)), (PARTIAL sum(temperature)), (PARTIAL sum(humidity)), (PARTIAL avg(humidity)), (PARTIAL stddev((humidity)::integer)), (PARTIAL bit_and(bit_int)), (PARTIAL bit_or(bit_int)), (PARTIAL bool_and(good_life)), (PARTIAL every((temperature > '0'::double precision))), (PARTIAL bool_or(good_life)), (PARTIAL count(*)), (PARTIAL count(temperature)), (PARTIAL count(allnull)), (PARTIAL corr(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL covar_pop(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL covar_samp(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_avgx(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_avgy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_count(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_intercept(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_r2(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_slope(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_sxx(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_sxy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_syy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL stddev((temperature)::integer)), (PARTIAL stddev_pop((temperature)::integer)), (PARTIAL stddev_samp((temperature)::integer)), (PARTIAL variance((temperature)::integer)), (PARTIAL var_pop((temperature)::integer)), (PARTIAL var_samp((temperature)::integer)), (PARTIAL last(temperature, timec)), (PARTIAL histogram(temperature, '0'::double precision, '100'::double precision, 1))
|
||||
-> Append
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: conditions.region, (PARTIAL min(conditions.allnull)), (PARTIAL max(conditions.temperature)), (PARTIAL sum(conditions.temperature)), (PARTIAL sum(conditions.humidity)), (PARTIAL avg(conditions.humidity)), (PARTIAL stddev((conditions.humidity)::integer)), (PARTIAL bit_and(conditions.bit_int)), (PARTIAL bit_or(conditions.bit_int)), (PARTIAL bool_and(conditions.good_life)), (PARTIAL every((conditions.temperature > '0'::double precision))), (PARTIAL bool_or(conditions.good_life)), (PARTIAL count(*)), (PARTIAL count(conditions.temperature)), (PARTIAL count(conditions.allnull)), (PARTIAL corr(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL covar_pop(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL covar_samp(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL regr_avgx(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL regr_avgy(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL regr_count(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL regr_intercept(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL regr_r2(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL regr_slope(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL regr_sxx(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL regr_sxy(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL regr_syy(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL stddev((conditions.temperature)::integer)), (PARTIAL stddev_pop((conditions.temperature)::integer)), (PARTIAL stddev_samp((conditions.temperature)::integer)), (PARTIAL variance((conditions.temperature)::integer)), (PARTIAL var_pop((conditions.temperature)::integer)), (PARTIAL var_samp((conditions.temperature)::integer)), (PARTIAL last(conditions.temperature, conditions.timec)), (PARTIAL histogram(conditions.temperature, '0'::double precision, '100'::double precision, 1))
|
||||
Relations: Aggregate on (public.conditions)
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_1_chunk, _dist_hyper_1_2_chunk, _dist_hyper_1_3_chunk, _dist_hyper_1_4_chunk
|
||||
Remote SQL: SELECT region, _timescaledb_internal.partialize_agg(min(allnull)), _timescaledb_internal.partialize_agg(max(temperature)), _timescaledb_internal.partialize_agg(sum(temperature)), _timescaledb_internal.partialize_agg(sum(humidity)), _timescaledb_internal.partialize_agg(avg(humidity)), _timescaledb_internal.partialize_agg(stddev(humidity::integer)), _timescaledb_internal.partialize_agg(bit_and(bit_int)), _timescaledb_internal.partialize_agg(bit_or(bit_int)), _timescaledb_internal.partialize_agg(bool_and(good_life)), _timescaledb_internal.partialize_agg(every((temperature > 0::double precision))), _timescaledb_internal.partialize_agg(bool_or(good_life)), _timescaledb_internal.partialize_agg(count(*)), _timescaledb_internal.partialize_agg(count(temperature)), _timescaledb_internal.partialize_agg(count(allnull)), _timescaledb_internal.partialize_agg(corr(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(covar_pop(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(covar_samp(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_avgx(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_avgy(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_count(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_intercept(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_r2(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_slope(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_sxx(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_sxy(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_syy(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(stddev(temperature::integer)), _timescaledb_internal.partialize_agg(stddev_pop(temperature::integer)), _timescaledb_internal.partialize_agg(stddev_samp(temperature::integer)), _timescaledb_internal.partialize_agg(variance(temperature::integer)), _timescaledb_internal.partialize_agg(var_pop(temperature::integer)), _timescaledb_internal.partialize_agg(var_samp(temperature::integer)), _timescaledb_internal.partialize_agg(public.last(temperature, timec)), _timescaledb_internal.partialize_agg(public.histogram(temperature, 0::double precision, 100::double precision, 1)) FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) GROUP BY 1
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: conditions_1.region, (PARTIAL min(conditions_1.allnull)), (PARTIAL max(conditions_1.temperature)), (PARTIAL sum(conditions_1.temperature)), (PARTIAL sum(conditions_1.humidity)), (PARTIAL avg(conditions_1.humidity)), (PARTIAL stddev((conditions_1.humidity)::integer)), (PARTIAL bit_and(conditions_1.bit_int)), (PARTIAL bit_or(conditions_1.bit_int)), (PARTIAL bool_and(conditions_1.good_life)), (PARTIAL every((conditions_1.temperature > '0'::double precision))), (PARTIAL bool_or(conditions_1.good_life)), (PARTIAL count(*)), (PARTIAL count(conditions_1.temperature)), (PARTIAL count(conditions_1.allnull)), (PARTIAL corr(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL covar_pop(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL covar_samp(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL regr_avgx(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL regr_avgy(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL regr_count(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL regr_intercept(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL regr_r2(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL regr_slope(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL regr_sxx(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL regr_sxy(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL regr_syy(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL stddev((conditions_1.temperature)::integer)), (PARTIAL stddev_pop((conditions_1.temperature)::integer)), (PARTIAL stddev_samp((conditions_1.temperature)::integer)), (PARTIAL variance((conditions_1.temperature)::integer)), (PARTIAL var_pop((conditions_1.temperature)::integer)), (PARTIAL var_samp((conditions_1.temperature)::integer)), (PARTIAL last(conditions_1.temperature, conditions_1.timec)), (PARTIAL histogram(conditions_1.temperature, '0'::double precision, '100'::double precision, 1))
|
||||
Relations: Aggregate on (public.conditions)
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_9_chunk, _dist_hyper_1_10_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_12_chunk
|
||||
Remote SQL: SELECT region, _timescaledb_internal.partialize_agg(min(allnull)), _timescaledb_internal.partialize_agg(max(temperature)), _timescaledb_internal.partialize_agg(sum(temperature)), _timescaledb_internal.partialize_agg(sum(humidity)), _timescaledb_internal.partialize_agg(avg(humidity)), _timescaledb_internal.partialize_agg(stddev(humidity::integer)), _timescaledb_internal.partialize_agg(bit_and(bit_int)), _timescaledb_internal.partialize_agg(bit_or(bit_int)), _timescaledb_internal.partialize_agg(bool_and(good_life)), _timescaledb_internal.partialize_agg(every((temperature > 0::double precision))), _timescaledb_internal.partialize_agg(bool_or(good_life)), _timescaledb_internal.partialize_agg(count(*)), _timescaledb_internal.partialize_agg(count(temperature)), _timescaledb_internal.partialize_agg(count(allnull)), _timescaledb_internal.partialize_agg(corr(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(covar_pop(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(covar_samp(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_avgx(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_avgy(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_count(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_intercept(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_r2(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_slope(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_sxx(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_sxy(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_syy(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(stddev(temperature::integer)), _timescaledb_internal.partialize_agg(stddev_pop(temperature::integer)), _timescaledb_internal.partialize_agg(stddev_samp(temperature::integer)), _timescaledb_internal.partialize_agg(variance(temperature::integer)), _timescaledb_internal.partialize_agg(var_pop(temperature::integer)), _timescaledb_internal.partialize_agg(var_samp(temperature::integer)), _timescaledb_internal.partialize_agg(public.last(temperature, timec)), _timescaledb_internal.partialize_agg(public.histogram(temperature, 0::double precision, 100::double precision, 1)) FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) GROUP BY 1
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: conditions_2.region, (PARTIAL min(conditions_2.allnull)), (PARTIAL max(conditions_2.temperature)), (PARTIAL sum(conditions_2.temperature)), (PARTIAL sum(conditions_2.humidity)), (PARTIAL avg(conditions_2.humidity)), (PARTIAL stddev((conditions_2.humidity)::integer)), (PARTIAL bit_and(conditions_2.bit_int)), (PARTIAL bit_or(conditions_2.bit_int)), (PARTIAL bool_and(conditions_2.good_life)), (PARTIAL every((conditions_2.temperature > '0'::double precision))), (PARTIAL bool_or(conditions_2.good_life)), (PARTIAL count(*)), (PARTIAL count(conditions_2.temperature)), (PARTIAL count(conditions_2.allnull)), (PARTIAL corr(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL covar_pop(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL covar_samp(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL regr_avgx(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL regr_avgy(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL regr_count(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL regr_intercept(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL regr_r2(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL regr_slope(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL regr_sxx(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL regr_sxy(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL regr_syy(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL stddev((conditions_2.temperature)::integer)), (PARTIAL stddev_pop((conditions_2.temperature)::integer)), (PARTIAL stddev_samp((conditions_2.temperature)::integer)), (PARTIAL variance((conditions_2.temperature)::integer)), (PARTIAL var_pop((conditions_2.temperature)::integer)), (PARTIAL var_samp((conditions_2.temperature)::integer)), (PARTIAL last(conditions_2.temperature, conditions_2.timec)), (PARTIAL histogram(conditions_2.temperature, '0'::double precision, '100'::double precision, 1))
|
||||
Relations: Aggregate on (public.conditions)
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_5_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_7_chunk, _dist_hyper_1_8_chunk
|
||||
Remote SQL: SELECT region, _timescaledb_internal.partialize_agg(min(allnull)), _timescaledb_internal.partialize_agg(max(temperature)), _timescaledb_internal.partialize_agg(sum(temperature)), _timescaledb_internal.partialize_agg(sum(humidity)), _timescaledb_internal.partialize_agg(avg(humidity)), _timescaledb_internal.partialize_agg(stddev(humidity::integer)), _timescaledb_internal.partialize_agg(bit_and(bit_int)), _timescaledb_internal.partialize_agg(bit_or(bit_int)), _timescaledb_internal.partialize_agg(bool_and(good_life)), _timescaledb_internal.partialize_agg(every((temperature > 0::double precision))), _timescaledb_internal.partialize_agg(bool_or(good_life)), _timescaledb_internal.partialize_agg(count(*)), _timescaledb_internal.partialize_agg(count(temperature)), _timescaledb_internal.partialize_agg(count(allnull)), _timescaledb_internal.partialize_agg(corr(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(covar_pop(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(covar_samp(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_avgx(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_avgy(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_count(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_intercept(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_r2(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_slope(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_sxx(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_sxy(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_syy(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(stddev(temperature::integer)), _timescaledb_internal.partialize_agg(stddev_pop(temperature::integer)), _timescaledb_internal.partialize_agg(stddev_samp(temperature::integer)), _timescaledb_internal.partialize_agg(variance(temperature::integer)), _timescaledb_internal.partialize_agg(var_pop(temperature::integer)), _timescaledb_internal.partialize_agg(var_samp(temperature::integer)), _timescaledb_internal.partialize_agg(public.last(temperature, timec)), _timescaledb_internal.partialize_agg(public.histogram(temperature, 0::double precision, 100::double precision, 1)) FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) GROUP BY 1
|
||||
(27 rows)
|
||||
Output: region, temperature, min(allnull), max(temperature), (sum(temperature) + sum(humidity)), avg(humidity), round(stddev((humidity)::integer), 5), bit_and(bit_int), bit_or(bit_int), bool_and(good_life), every((temperature > '0'::double precision)), bool_or(good_life), count(*), count(temperature), count(allnull), round((corr(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((covar_pop(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((covar_samp(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_avgx(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_avgy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_count(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_intercept(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_r2(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_slope(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_sxx(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_sxy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_syy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round(stddev((temperature)::integer), 5), round(stddev_pop((temperature)::integer), 5), round(stddev_samp((temperature)::integer), 5), round(variance((temperature)::integer), 5), round(var_pop((temperature)::integer), 5), round(var_samp((temperature)::integer), 5), last(temperature, timec), histogram(temperature, '0'::double precision, '100'::double precision, 1), timec
|
||||
Group Key: region, temperature, timec
|
||||
-> Custom Scan (AsyncAppend)
|
||||
Output: region, temperature, timec, (PARTIAL min(allnull)), (PARTIAL max(temperature)), (PARTIAL sum(temperature)), (PARTIAL sum(humidity)), (PARTIAL avg(humidity)), (PARTIAL stddev((humidity)::integer)), (PARTIAL bit_and(bit_int)), (PARTIAL bit_or(bit_int)), (PARTIAL bool_and(good_life)), (PARTIAL every((temperature > '0'::double precision))), (PARTIAL bool_or(good_life)), (PARTIAL count(*)), (PARTIAL count(temperature)), (PARTIAL count(allnull)), (PARTIAL corr(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL covar_pop(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL covar_samp(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_avgx(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_avgy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_count(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_intercept(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_r2(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_slope(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_sxx(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_sxy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_syy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL stddev((temperature)::integer)), (PARTIAL stddev_pop((temperature)::integer)), (PARTIAL stddev_samp((temperature)::integer)), (PARTIAL variance((temperature)::integer)), (PARTIAL var_pop((temperature)::integer)), (PARTIAL var_samp((temperature)::integer)), (PARTIAL last(temperature, timec)), (PARTIAL histogram(temperature, '0'::double precision, '100'::double precision, 1))
|
||||
-> Merge Append
|
||||
Sort Key: conditions.region, conditions.temperature, conditions.timec
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: conditions.region, conditions.temperature, conditions.timec, (PARTIAL min(conditions.allnull)), (PARTIAL max(conditions.temperature)), (PARTIAL sum(conditions.temperature)), (PARTIAL sum(conditions.humidity)), (PARTIAL avg(conditions.humidity)), (PARTIAL stddev((conditions.humidity)::integer)), (PARTIAL bit_and(conditions.bit_int)), (PARTIAL bit_or(conditions.bit_int)), (PARTIAL bool_and(conditions.good_life)), (PARTIAL every((conditions.temperature > '0'::double precision))), (PARTIAL bool_or(conditions.good_life)), (PARTIAL count(*)), (PARTIAL count(conditions.temperature)), (PARTIAL count(conditions.allnull)), (PARTIAL corr(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL covar_pop(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL covar_samp(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL regr_avgx(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL regr_avgy(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL regr_count(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL regr_intercept(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL regr_r2(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL regr_slope(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL regr_sxx(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL regr_sxy(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL regr_syy(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL stddev((conditions.temperature)::integer)), (PARTIAL stddev_pop((conditions.temperature)::integer)), (PARTIAL stddev_samp((conditions.temperature)::integer)), (PARTIAL variance((conditions.temperature)::integer)), (PARTIAL var_pop((conditions.temperature)::integer)), (PARTIAL var_samp((conditions.temperature)::integer)), (PARTIAL last(conditions.temperature, conditions.timec)), (PARTIAL histogram(conditions.temperature, '0'::double precision, '100'::double precision, 1))
|
||||
Relations: Aggregate on (public.conditions)
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_1_chunk, _dist_hyper_1_2_chunk, _dist_hyper_1_3_chunk, _dist_hyper_1_4_chunk
|
||||
Remote SQL: SELECT region, temperature, timec, _timescaledb_internal.partialize_agg(min(allnull)), _timescaledb_internal.partialize_agg(max(temperature)), _timescaledb_internal.partialize_agg(sum(temperature)), _timescaledb_internal.partialize_agg(sum(humidity)), _timescaledb_internal.partialize_agg(avg(humidity)), _timescaledb_internal.partialize_agg(stddev(humidity::integer)), _timescaledb_internal.partialize_agg(bit_and(bit_int)), _timescaledb_internal.partialize_agg(bit_or(bit_int)), _timescaledb_internal.partialize_agg(bool_and(good_life)), _timescaledb_internal.partialize_agg(every((temperature > 0::double precision))), _timescaledb_internal.partialize_agg(bool_or(good_life)), _timescaledb_internal.partialize_agg(count(*)), _timescaledb_internal.partialize_agg(count(temperature)), _timescaledb_internal.partialize_agg(count(allnull)), _timescaledb_internal.partialize_agg(corr(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(covar_pop(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(covar_samp(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_avgx(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_avgy(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_count(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_intercept(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_r2(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_slope(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_sxx(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_sxy(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_syy(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(stddev(temperature::integer)), _timescaledb_internal.partialize_agg(stddev_pop(temperature::integer)), _timescaledb_internal.partialize_agg(stddev_samp(temperature::integer)), _timescaledb_internal.partialize_agg(variance(temperature::integer)), _timescaledb_internal.partialize_agg(var_pop(temperature::integer)), _timescaledb_internal.partialize_agg(var_samp(temperature::integer)), _timescaledb_internal.partialize_agg(public.last(temperature, timec)), _timescaledb_internal.partialize_agg(public.histogram(temperature, 0::double precision, 100::double precision, 1)) FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) GROUP BY 1, 2, 3 ORDER BY region ASC NULLS LAST, temperature ASC NULLS LAST, timec ASC NULLS LAST
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: conditions_1.region, conditions_1.temperature, conditions_1.timec, (PARTIAL min(conditions_1.allnull)), (PARTIAL max(conditions_1.temperature)), (PARTIAL sum(conditions_1.temperature)), (PARTIAL sum(conditions_1.humidity)), (PARTIAL avg(conditions_1.humidity)), (PARTIAL stddev((conditions_1.humidity)::integer)), (PARTIAL bit_and(conditions_1.bit_int)), (PARTIAL bit_or(conditions_1.bit_int)), (PARTIAL bool_and(conditions_1.good_life)), (PARTIAL every((conditions_1.temperature > '0'::double precision))), (PARTIAL bool_or(conditions_1.good_life)), (PARTIAL count(*)), (PARTIAL count(conditions_1.temperature)), (PARTIAL count(conditions_1.allnull)), (PARTIAL corr(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL covar_pop(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL covar_samp(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL regr_avgx(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL regr_avgy(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL regr_count(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL regr_intercept(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL regr_r2(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL regr_slope(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL regr_sxx(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL regr_sxy(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL regr_syy(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL stddev((conditions_1.temperature)::integer)), (PARTIAL stddev_pop((conditions_1.temperature)::integer)), (PARTIAL stddev_samp((conditions_1.temperature)::integer)), (PARTIAL variance((conditions_1.temperature)::integer)), (PARTIAL var_pop((conditions_1.temperature)::integer)), (PARTIAL var_samp((conditions_1.temperature)::integer)), (PARTIAL last(conditions_1.temperature, conditions_1.timec)), (PARTIAL histogram(conditions_1.temperature, '0'::double precision, '100'::double precision, 1))
|
||||
Relations: Aggregate on (public.conditions)
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_9_chunk, _dist_hyper_1_10_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_12_chunk
|
||||
Remote SQL: SELECT region, temperature, timec, _timescaledb_internal.partialize_agg(min(allnull)), _timescaledb_internal.partialize_agg(max(temperature)), _timescaledb_internal.partialize_agg(sum(temperature)), _timescaledb_internal.partialize_agg(sum(humidity)), _timescaledb_internal.partialize_agg(avg(humidity)), _timescaledb_internal.partialize_agg(stddev(humidity::integer)), _timescaledb_internal.partialize_agg(bit_and(bit_int)), _timescaledb_internal.partialize_agg(bit_or(bit_int)), _timescaledb_internal.partialize_agg(bool_and(good_life)), _timescaledb_internal.partialize_agg(every((temperature > 0::double precision))), _timescaledb_internal.partialize_agg(bool_or(good_life)), _timescaledb_internal.partialize_agg(count(*)), _timescaledb_internal.partialize_agg(count(temperature)), _timescaledb_internal.partialize_agg(count(allnull)), _timescaledb_internal.partialize_agg(corr(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(covar_pop(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(covar_samp(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_avgx(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_avgy(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_count(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_intercept(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_r2(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_slope(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_sxx(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_sxy(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_syy(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(stddev(temperature::integer)), _timescaledb_internal.partialize_agg(stddev_pop(temperature::integer)), _timescaledb_internal.partialize_agg(stddev_samp(temperature::integer)), _timescaledb_internal.partialize_agg(variance(temperature::integer)), _timescaledb_internal.partialize_agg(var_pop(temperature::integer)), _timescaledb_internal.partialize_agg(var_samp(temperature::integer)), _timescaledb_internal.partialize_agg(public.last(temperature, timec)), _timescaledb_internal.partialize_agg(public.histogram(temperature, 0::double precision, 100::double precision, 1)) FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) GROUP BY 1, 2, 3 ORDER BY region ASC NULLS LAST, temperature ASC NULLS LAST, timec ASC NULLS LAST
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: conditions_2.region, conditions_2.temperature, conditions_2.timec, (PARTIAL min(conditions_2.allnull)), (PARTIAL max(conditions_2.temperature)), (PARTIAL sum(conditions_2.temperature)), (PARTIAL sum(conditions_2.humidity)), (PARTIAL avg(conditions_2.humidity)), (PARTIAL stddev((conditions_2.humidity)::integer)), (PARTIAL bit_and(conditions_2.bit_int)), (PARTIAL bit_or(conditions_2.bit_int)), (PARTIAL bool_and(conditions_2.good_life)), (PARTIAL every((conditions_2.temperature > '0'::double precision))), (PARTIAL bool_or(conditions_2.good_life)), (PARTIAL count(*)), (PARTIAL count(conditions_2.temperature)), (PARTIAL count(conditions_2.allnull)), (PARTIAL corr(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL covar_pop(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL covar_samp(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL regr_avgx(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL regr_avgy(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL regr_count(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL regr_intercept(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL regr_r2(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL regr_slope(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL regr_sxx(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL regr_sxy(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL regr_syy(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL stddev((conditions_2.temperature)::integer)), (PARTIAL stddev_pop((conditions_2.temperature)::integer)), (PARTIAL stddev_samp((conditions_2.temperature)::integer)), (PARTIAL variance((conditions_2.temperature)::integer)), (PARTIAL var_pop((conditions_2.temperature)::integer)), (PARTIAL var_samp((conditions_2.temperature)::integer)), (PARTIAL last(conditions_2.temperature, conditions_2.timec)), (PARTIAL histogram(conditions_2.temperature, '0'::double precision, '100'::double precision, 1))
|
||||
Relations: Aggregate on (public.conditions)
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_5_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_7_chunk, _dist_hyper_1_8_chunk
|
||||
Remote SQL: SELECT region, temperature, timec, _timescaledb_internal.partialize_agg(min(allnull)), _timescaledb_internal.partialize_agg(max(temperature)), _timescaledb_internal.partialize_agg(sum(temperature)), _timescaledb_internal.partialize_agg(sum(humidity)), _timescaledb_internal.partialize_agg(avg(humidity)), _timescaledb_internal.partialize_agg(stddev(humidity::integer)), _timescaledb_internal.partialize_agg(bit_and(bit_int)), _timescaledb_internal.partialize_agg(bit_or(bit_int)), _timescaledb_internal.partialize_agg(bool_and(good_life)), _timescaledb_internal.partialize_agg(every((temperature > 0::double precision))), _timescaledb_internal.partialize_agg(bool_or(good_life)), _timescaledb_internal.partialize_agg(count(*)), _timescaledb_internal.partialize_agg(count(temperature)), _timescaledb_internal.partialize_agg(count(allnull)), _timescaledb_internal.partialize_agg(corr(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(covar_pop(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(covar_samp(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_avgx(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_avgy(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_count(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_intercept(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_r2(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_slope(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_sxx(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_sxy(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_syy(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(stddev(temperature::integer)), _timescaledb_internal.partialize_agg(stddev_pop(temperature::integer)), _timescaledb_internal.partialize_agg(stddev_samp(temperature::integer)), _timescaledb_internal.partialize_agg(variance(temperature::integer)), _timescaledb_internal.partialize_agg(var_pop(temperature::integer)), _timescaledb_internal.partialize_agg(var_samp(temperature::integer)), _timescaledb_internal.partialize_agg(public.last(temperature, timec)), _timescaledb_internal.partialize_agg(public.histogram(temperature, 0::double precision, 100::double precision, 1)) FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) GROUP BY 1, 2, 3 ORDER BY region ASC NULLS LAST, temperature ASC NULLS LAST, timec ASC NULLS LAST
|
||||
(25 rows)
|
||||
|
||||
-- Aggregates on custom types are not yet pushed down
|
||||
:PREFIX SELECT :GROUPING,
|
||||
last(highlow, timec) as last_hl,
|
||||
first(highlow, timec) as first_hl
|
||||
FROM :TEST_TABLE
|
||||
GROUP BY :GROUPING
|
||||
ORDER BY :GROUPING;
|
||||
QUERY PLAN
|
||||
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
GROUP BY :GROUPING, timec
|
||||
ORDER BY :GROUPING, timec;
|
||||
QUERY PLAN
|
||||
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Finalize GroupAggregate
|
||||
Output: region, last(highlow, timec), first(highlow, timec)
|
||||
Group Key: region
|
||||
-> Sort
|
||||
Output: region, (PARTIAL last(highlow, timec)), (PARTIAL first(highlow, timec))
|
||||
Sort Key: region
|
||||
-> Custom Scan (AsyncAppend)
|
||||
Output: region, (PARTIAL last(highlow, timec)), (PARTIAL first(highlow, timec))
|
||||
-> Append
|
||||
-> Partial HashAggregate
|
||||
Output: conditions.region, PARTIAL last(conditions.highlow, conditions.timec), PARTIAL first(conditions.highlow, conditions.timec)
|
||||
Group Key: conditions.region
|
||||
-> Custom Scan (DataNodeScan) on public.conditions
|
||||
Output: conditions.region, conditions.highlow, conditions.timec
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_1_chunk, _dist_hyper_1_2_chunk, _dist_hyper_1_3_chunk, _dist_hyper_1_4_chunk
|
||||
Remote SQL: SELECT timec, region, highlow FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4])
|
||||
-> Partial HashAggregate
|
||||
Output: conditions_1.region, PARTIAL last(conditions_1.highlow, conditions_1.timec), PARTIAL first(conditions_1.highlow, conditions_1.timec)
|
||||
Group Key: conditions_1.region
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_1
|
||||
Output: conditions_1.region, conditions_1.highlow, conditions_1.timec
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_9_chunk, _dist_hyper_1_10_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_12_chunk
|
||||
Remote SQL: SELECT timec, region, highlow FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4])
|
||||
-> Partial HashAggregate
|
||||
Output: conditions_2.region, PARTIAL last(conditions_2.highlow, conditions_2.timec), PARTIAL first(conditions_2.highlow, conditions_2.timec)
|
||||
Group Key: conditions_2.region
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_2
|
||||
Output: conditions_2.region, conditions_2.highlow, conditions_2.timec
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_5_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_7_chunk, _dist_hyper_1_8_chunk
|
||||
Remote SQL: SELECT timec, region, highlow FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4])
|
||||
(33 rows)
|
||||
Output: conditions.region, conditions.temperature, last(conditions.highlow, conditions.timec), first(conditions.highlow, conditions.timec), conditions.timec
|
||||
Group Key: conditions.region, conditions.temperature, conditions.timec
|
||||
-> Merge Append
|
||||
Sort Key: conditions.region, conditions.temperature, conditions.timec
|
||||
-> Partial GroupAggregate
|
||||
Output: conditions.region, conditions.temperature, conditions.timec, PARTIAL last(conditions.highlow, conditions.timec), PARTIAL first(conditions.highlow, conditions.timec)
|
||||
Group Key: conditions.region, conditions.temperature, conditions.timec
|
||||
-> Custom Scan (DataNodeScan) on public.conditions
|
||||
Output: conditions.region, conditions.temperature, conditions.timec, conditions.highlow
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_1_chunk, _dist_hyper_1_2_chunk, _dist_hyper_1_3_chunk, _dist_hyper_1_4_chunk
|
||||
Remote SQL: SELECT timec, region, temperature, highlow FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) ORDER BY region ASC NULLS LAST, temperature ASC NULLS LAST, timec ASC NULLS LAST
|
||||
-> Partial GroupAggregate
|
||||
Output: conditions_1.region, conditions_1.temperature, conditions_1.timec, PARTIAL last(conditions_1.highlow, conditions_1.timec), PARTIAL first(conditions_1.highlow, conditions_1.timec)
|
||||
Group Key: conditions_1.region, conditions_1.temperature, conditions_1.timec
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_1
|
||||
Output: conditions_1.region, conditions_1.temperature, conditions_1.timec, conditions_1.highlow
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_9_chunk, _dist_hyper_1_10_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_12_chunk
|
||||
Remote SQL: SELECT timec, region, temperature, highlow FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) ORDER BY region ASC NULLS LAST, temperature ASC NULLS LAST, timec ASC NULLS LAST
|
||||
-> Partial GroupAggregate
|
||||
Output: conditions_2.region, conditions_2.temperature, conditions_2.timec, PARTIAL last(conditions_2.highlow, conditions_2.timec), PARTIAL first(conditions_2.highlow, conditions_2.timec)
|
||||
Group Key: conditions_2.region, conditions_2.temperature, conditions_2.timec
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_2
|
||||
Output: conditions_2.region, conditions_2.temperature, conditions_2.timec, conditions_2.highlow
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_5_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_7_chunk, _dist_hyper_1_8_chunk
|
||||
Remote SQL: SELECT timec, region, temperature, highlow FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) ORDER BY region ASC NULLS LAST, temperature ASC NULLS LAST, timec ASC NULLS LAST
|
||||
(29 rows)
|
||||
|
||||
-- Mix of aggregates that push down and those that don't
|
||||
:PREFIX SELECT :GROUPING,
|
||||
@ -419,44 +403,40 @@ SET enable_partitionwise_aggregate = ON;
|
||||
bool_or(good_life),
|
||||
first(highlow, timec) as first_hl
|
||||
FROM :TEST_TABLE
|
||||
GROUP BY :GROUPING
|
||||
ORDER BY :GROUPING;
|
||||
QUERY PLAN
|
||||
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
GROUP BY :GROUPING, timec
|
||||
ORDER BY :GROUPING, timec;
|
||||
QUERY PLAN
|
||||
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Finalize GroupAggregate
|
||||
Output: region, min(allnull), max(temperature), (sum(temperature) + sum(humidity)), avg(humidity), round(stddev((humidity)::integer), 5), bit_and(bit_int), bit_or(bit_int), bool_and(good_life), every((temperature > '0'::double precision)), bool_or(good_life), first(highlow, timec)
|
||||
Group Key: region
|
||||
-> Sort
|
||||
Output: region, (PARTIAL min(allnull)), (PARTIAL max(temperature)), (PARTIAL sum(temperature)), (PARTIAL sum(humidity)), (PARTIAL avg(humidity)), (PARTIAL stddev((humidity)::integer)), (PARTIAL bit_and(bit_int)), (PARTIAL bit_or(bit_int)), (PARTIAL bool_and(good_life)), (PARTIAL every((temperature > '0'::double precision))), (PARTIAL bool_or(good_life)), (PARTIAL first(highlow, timec))
|
||||
Sort Key: region
|
||||
-> Custom Scan (AsyncAppend)
|
||||
Output: region, (PARTIAL min(allnull)), (PARTIAL max(temperature)), (PARTIAL sum(temperature)), (PARTIAL sum(humidity)), (PARTIAL avg(humidity)), (PARTIAL stddev((humidity)::integer)), (PARTIAL bit_and(bit_int)), (PARTIAL bit_or(bit_int)), (PARTIAL bool_and(good_life)), (PARTIAL every((temperature > '0'::double precision))), (PARTIAL bool_or(good_life)), (PARTIAL first(highlow, timec))
|
||||
-> Append
|
||||
-> Partial HashAggregate
|
||||
Output: conditions.region, PARTIAL min(conditions.allnull), PARTIAL max(conditions.temperature), PARTIAL sum(conditions.temperature), PARTIAL sum(conditions.humidity), PARTIAL avg(conditions.humidity), PARTIAL stddev((conditions.humidity)::integer), PARTIAL bit_and(conditions.bit_int), PARTIAL bit_or(conditions.bit_int), PARTIAL bool_and(conditions.good_life), PARTIAL every((conditions.temperature > '0'::double precision)), PARTIAL bool_or(conditions.good_life), PARTIAL first(conditions.highlow, conditions.timec)
|
||||
Group Key: conditions.region
|
||||
-> Custom Scan (DataNodeScan) on public.conditions
|
||||
Output: conditions.region, conditions.allnull, conditions.temperature, conditions.humidity, conditions.bit_int, conditions.good_life, conditions.highlow, conditions.timec
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_1_chunk, _dist_hyper_1_2_chunk, _dist_hyper_1_3_chunk, _dist_hyper_1_4_chunk
|
||||
Remote SQL: SELECT timec, region, temperature, humidity, allnull, highlow, bit_int, good_life FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4])
|
||||
-> Partial HashAggregate
|
||||
Output: conditions_1.region, PARTIAL min(conditions_1.allnull), PARTIAL max(conditions_1.temperature), PARTIAL sum(conditions_1.temperature), PARTIAL sum(conditions_1.humidity), PARTIAL avg(conditions_1.humidity), PARTIAL stddev((conditions_1.humidity)::integer), PARTIAL bit_and(conditions_1.bit_int), PARTIAL bit_or(conditions_1.bit_int), PARTIAL bool_and(conditions_1.good_life), PARTIAL every((conditions_1.temperature > '0'::double precision)), PARTIAL bool_or(conditions_1.good_life), PARTIAL first(conditions_1.highlow, conditions_1.timec)
|
||||
Group Key: conditions_1.region
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_1
|
||||
Output: conditions_1.region, conditions_1.allnull, conditions_1.temperature, conditions_1.humidity, conditions_1.bit_int, conditions_1.good_life, conditions_1.highlow, conditions_1.timec
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_9_chunk, _dist_hyper_1_10_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_12_chunk
|
||||
Remote SQL: SELECT timec, region, temperature, humidity, allnull, highlow, bit_int, good_life FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4])
|
||||
-> Partial HashAggregate
|
||||
Output: conditions_2.region, PARTIAL min(conditions_2.allnull), PARTIAL max(conditions_2.temperature), PARTIAL sum(conditions_2.temperature), PARTIAL sum(conditions_2.humidity), PARTIAL avg(conditions_2.humidity), PARTIAL stddev((conditions_2.humidity)::integer), PARTIAL bit_and(conditions_2.bit_int), PARTIAL bit_or(conditions_2.bit_int), PARTIAL bool_and(conditions_2.good_life), PARTIAL every((conditions_2.temperature > '0'::double precision)), PARTIAL bool_or(conditions_2.good_life), PARTIAL first(conditions_2.highlow, conditions_2.timec)
|
||||
Group Key: conditions_2.region
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_2
|
||||
Output: conditions_2.region, conditions_2.allnull, conditions_2.temperature, conditions_2.humidity, conditions_2.bit_int, conditions_2.good_life, conditions_2.highlow, conditions_2.timec
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_5_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_7_chunk, _dist_hyper_1_8_chunk
|
||||
Remote SQL: SELECT timec, region, temperature, humidity, allnull, highlow, bit_int, good_life FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4])
|
||||
(33 rows)
|
||||
Output: conditions.region, conditions.temperature, min(conditions.allnull), max(conditions.temperature), (sum(conditions.temperature) + sum(conditions.humidity)), avg(conditions.humidity), round(stddev((conditions.humidity)::integer), 5), bit_and(conditions.bit_int), bit_or(conditions.bit_int), bool_and(conditions.good_life), every((conditions.temperature > '0'::double precision)), bool_or(conditions.good_life), first(conditions.highlow, conditions.timec), conditions.timec
|
||||
Group Key: conditions.region, conditions.temperature, conditions.timec
|
||||
-> Merge Append
|
||||
Sort Key: conditions.region, conditions.temperature, conditions.timec
|
||||
-> Partial GroupAggregate
|
||||
Output: conditions.region, conditions.temperature, conditions.timec, PARTIAL min(conditions.allnull), PARTIAL max(conditions.temperature), PARTIAL sum(conditions.temperature), PARTIAL sum(conditions.humidity), PARTIAL avg(conditions.humidity), PARTIAL stddev((conditions.humidity)::integer), PARTIAL bit_and(conditions.bit_int), PARTIAL bit_or(conditions.bit_int), PARTIAL bool_and(conditions.good_life), PARTIAL every((conditions.temperature > '0'::double precision)), PARTIAL bool_or(conditions.good_life), PARTIAL first(conditions.highlow, conditions.timec)
|
||||
Group Key: conditions.region, conditions.temperature, conditions.timec
|
||||
-> Custom Scan (DataNodeScan) on public.conditions
|
||||
Output: conditions.region, conditions.temperature, conditions.timec, conditions.allnull, conditions.humidity, conditions.bit_int, conditions.good_life, conditions.highlow
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_1_chunk, _dist_hyper_1_2_chunk, _dist_hyper_1_3_chunk, _dist_hyper_1_4_chunk
|
||||
Remote SQL: SELECT timec, region, temperature, humidity, allnull, highlow, bit_int, good_life FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) ORDER BY region ASC NULLS LAST, temperature ASC NULLS LAST, timec ASC NULLS LAST
|
||||
-> Partial GroupAggregate
|
||||
Output: conditions_1.region, conditions_1.temperature, conditions_1.timec, PARTIAL min(conditions_1.allnull), PARTIAL max(conditions_1.temperature), PARTIAL sum(conditions_1.temperature), PARTIAL sum(conditions_1.humidity), PARTIAL avg(conditions_1.humidity), PARTIAL stddev((conditions_1.humidity)::integer), PARTIAL bit_and(conditions_1.bit_int), PARTIAL bit_or(conditions_1.bit_int), PARTIAL bool_and(conditions_1.good_life), PARTIAL every((conditions_1.temperature > '0'::double precision)), PARTIAL bool_or(conditions_1.good_life), PARTIAL first(conditions_1.highlow, conditions_1.timec)
|
||||
Group Key: conditions_1.region, conditions_1.temperature, conditions_1.timec
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_1
|
||||
Output: conditions_1.region, conditions_1.temperature, conditions_1.timec, conditions_1.allnull, conditions_1.humidity, conditions_1.bit_int, conditions_1.good_life, conditions_1.highlow
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_9_chunk, _dist_hyper_1_10_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_12_chunk
|
||||
Remote SQL: SELECT timec, region, temperature, humidity, allnull, highlow, bit_int, good_life FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) ORDER BY region ASC NULLS LAST, temperature ASC NULLS LAST, timec ASC NULLS LAST
|
||||
-> Partial GroupAggregate
|
||||
Output: conditions_2.region, conditions_2.temperature, conditions_2.timec, PARTIAL min(conditions_2.allnull), PARTIAL max(conditions_2.temperature), PARTIAL sum(conditions_2.temperature), PARTIAL sum(conditions_2.humidity), PARTIAL avg(conditions_2.humidity), PARTIAL stddev((conditions_2.humidity)::integer), PARTIAL bit_and(conditions_2.bit_int), PARTIAL bit_or(conditions_2.bit_int), PARTIAL bool_and(conditions_2.good_life), PARTIAL every((conditions_2.temperature > '0'::double precision)), PARTIAL bool_or(conditions_2.good_life), PARTIAL first(conditions_2.highlow, conditions_2.timec)
|
||||
Group Key: conditions_2.region, conditions_2.temperature, conditions_2.timec
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_2
|
||||
Output: conditions_2.region, conditions_2.temperature, conditions_2.timec, conditions_2.allnull, conditions_2.humidity, conditions_2.bit_int, conditions_2.good_life, conditions_2.highlow
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_5_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_7_chunk, _dist_hyper_1_8_chunk
|
||||
Remote SQL: SELECT timec, region, temperature, humidity, allnull, highlow, bit_int, good_life FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) ORDER BY region ASC NULLS LAST, temperature ASC NULLS LAST, timec ASC NULLS LAST
|
||||
(29 rows)
|
||||
|
||||
-- Full aggregate pushdown correctness check, compare location grouped query results with partionwise aggregates on and off
|
||||
\set GROUPING 'location'
|
||||
@ -477,10 +457,6 @@ SELECT format('\! diff %s %s', :'RESULTS_CONTROL2', :'RESULTS_TEST2') as "DIFF_C
|
||||
\gset
|
||||
--generate the results into two different files
|
||||
\set ECHO errors
|
||||
-- Note that some difference in output could happen here because
|
||||
-- queries include last(col, time) and first(col, time); there are
|
||||
-- multiple values for "col" that has the same timestamp, so the
|
||||
-- output depends on the order of arriving tuples.
|
||||
:DIFF_CMD2
|
||||
\c :TEST_DBNAME :ROLE_CLUSTER_SUPERUSER
|
||||
DROP DATABASE :DN_DBNAME_1;
|
||||
|
||||
@ -165,80 +165,70 @@ SET enable_partitionwise_aggregate = ON;
|
||||
last(temperature, timec) as last_temp,
|
||||
histogram(temperature, 0, 100, 1)
|
||||
FROM :TEST_TABLE
|
||||
GROUP BY :GROUPING
|
||||
ORDER BY :GROUPING;
|
||||
QUERY PLAN
|
||||
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
GROUP BY :GROUPING, timec
|
||||
ORDER BY :GROUPING, timec;
|
||||
QUERY PLAN
|
||||
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Custom Scan (AsyncAppend)
|
||||
Output: location, (min(allnull)), (max(temperature)), ((sum(temperature) + sum(humidity))), (avg(humidity)), (round(stddev((humidity)::integer), 5)), (bit_and(bit_int)), (bit_or(bit_int)), (bool_and(good_life)), (every((temperature > '0'::double precision))), (bool_or(good_life)), (count(*)), (count(temperature)), (count(allnull)), (round((corr(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((covar_pop(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((covar_samp(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_avgx(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_avgy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_count(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_intercept(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_r2(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_slope(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_sxx(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_sxy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_syy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round(stddev((temperature)::integer), 5)), (round(stddev_pop((temperature)::integer), 5)), (round(stddev_samp((temperature)::integer), 5)), (round(variance((temperature)::integer), 5)), (round(var_pop((temperature)::integer), 5)), (round(var_samp((temperature)::integer), 5)), (last(temperature, timec)), (histogram(temperature, '0'::double precision, '100'::double precision, 1))
|
||||
Output: location, (min(allnull)), (max(temperature)), ((sum(temperature) + sum(humidity))), (avg(humidity)), (round(stddev((humidity)::integer), 5)), (bit_and(bit_int)), (bit_or(bit_int)), (bool_and(good_life)), (every((temperature > '0'::double precision))), (bool_or(good_life)), (count(*)), (count(temperature)), (count(allnull)), (round((corr(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((covar_pop(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((covar_samp(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_avgx(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_avgy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_count(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_intercept(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_r2(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_slope(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_sxx(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_sxy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round((regr_syy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5)), (round(stddev((temperature)::integer), 5)), (round(stddev_pop((temperature)::integer), 5)), (round(stddev_samp((temperature)::integer), 5)), (round(variance((temperature)::integer), 5)), (round(var_pop((temperature)::integer), 5)), (round(var_samp((temperature)::integer), 5)), (last(temperature, timec)), (histogram(temperature, '0'::double precision, '100'::double precision, 1)), timec
|
||||
-> Merge Append
|
||||
Sort Key: conditions.location
|
||||
-> GroupAggregate
|
||||
Output: conditions.location, min(conditions.allnull), max(conditions.temperature), (sum(conditions.temperature) + sum(conditions.humidity)), avg(conditions.humidity), round(stddev((conditions.humidity)::integer), 5), bit_and(conditions.bit_int), bit_or(conditions.bit_int), bool_and(conditions.good_life), every((conditions.temperature > '0'::double precision)), bool_or(conditions.good_life), count(*), count(conditions.temperature), count(conditions.allnull), round((corr(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5), round((covar_pop(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5), round((covar_samp(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5), round((regr_avgx(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5), round((regr_avgy(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5), round((regr_count(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5), round((regr_intercept(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5), round((regr_r2(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5), round((regr_slope(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5), round((regr_sxx(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5), round((regr_sxy(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5), round((regr_syy(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5), round(stddev((conditions.temperature)::integer), 5), round(stddev_pop((conditions.temperature)::integer), 5), round(stddev_samp((conditions.temperature)::integer), 5), round(variance((conditions.temperature)::integer), 5), round(var_pop((conditions.temperature)::integer), 5), round(var_samp((conditions.temperature)::integer), 5), last(conditions.temperature, conditions.timec), histogram(conditions.temperature, '0'::double precision, '100'::double precision, 1)
|
||||
Group Key: conditions.location
|
||||
-> Custom Scan (DataNodeScan) on public.conditions
|
||||
Output: conditions.location, conditions.allnull, conditions.temperature, conditions.humidity, conditions.bit_int, conditions.good_life, conditions.timec
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_1_chunk, _dist_hyper_1_2_chunk, _dist_hyper_1_3_chunk, _dist_hyper_1_4_chunk
|
||||
Remote SQL: SELECT timec, location, temperature, humidity, allnull, bit_int, good_life FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) ORDER BY location ASC NULLS LAST
|
||||
-> GroupAggregate
|
||||
Output: conditions_1.location, min(conditions_1.allnull), max(conditions_1.temperature), (sum(conditions_1.temperature) + sum(conditions_1.humidity)), avg(conditions_1.humidity), round(stddev((conditions_1.humidity)::integer), 5), bit_and(conditions_1.bit_int), bit_or(conditions_1.bit_int), bool_and(conditions_1.good_life), every((conditions_1.temperature > '0'::double precision)), bool_or(conditions_1.good_life), count(*), count(conditions_1.temperature), count(conditions_1.allnull), round((corr(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5), round((covar_pop(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5), round((covar_samp(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5), round((regr_avgx(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5), round((regr_avgy(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5), round((regr_count(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5), round((regr_intercept(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5), round((regr_r2(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5), round((regr_slope(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5), round((regr_sxx(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5), round((regr_sxy(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5), round((regr_syy(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5), round(stddev((conditions_1.temperature)::integer), 5), round(stddev_pop((conditions_1.temperature)::integer), 5), round(stddev_samp((conditions_1.temperature)::integer), 5), round(variance((conditions_1.temperature)::integer), 5), round(var_pop((conditions_1.temperature)::integer), 5), round(var_samp((conditions_1.temperature)::integer), 5), last(conditions_1.temperature, conditions_1.timec), histogram(conditions_1.temperature, '0'::double precision, '100'::double precision, 1)
|
||||
Group Key: conditions_1.location
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_1
|
||||
Output: conditions_1.location, conditions_1.allnull, conditions_1.temperature, conditions_1.humidity, conditions_1.bit_int, conditions_1.good_life, conditions_1.timec
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_9_chunk, _dist_hyper_1_10_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_12_chunk
|
||||
Remote SQL: SELECT timec, location, temperature, humidity, allnull, bit_int, good_life FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) ORDER BY location ASC NULLS LAST
|
||||
-> GroupAggregate
|
||||
Output: conditions_2.location, min(conditions_2.allnull), max(conditions_2.temperature), (sum(conditions_2.temperature) + sum(conditions_2.humidity)), avg(conditions_2.humidity), round(stddev((conditions_2.humidity)::integer), 5), bit_and(conditions_2.bit_int), bit_or(conditions_2.bit_int), bool_and(conditions_2.good_life), every((conditions_2.temperature > '0'::double precision)), bool_or(conditions_2.good_life), count(*), count(conditions_2.temperature), count(conditions_2.allnull), round((corr(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5), round((covar_pop(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5), round((covar_samp(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5), round((regr_avgx(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5), round((regr_avgy(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5), round((regr_count(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5), round((regr_intercept(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5), round((regr_r2(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5), round((regr_slope(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5), round((regr_sxx(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5), round((regr_sxy(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5), round((regr_syy(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5), round(stddev((conditions_2.temperature)::integer), 5), round(stddev_pop((conditions_2.temperature)::integer), 5), round(stddev_samp((conditions_2.temperature)::integer), 5), round(variance((conditions_2.temperature)::integer), 5), round(var_pop((conditions_2.temperature)::integer), 5), round(var_samp((conditions_2.temperature)::integer), 5), last(conditions_2.temperature, conditions_2.timec), histogram(conditions_2.temperature, '0'::double precision, '100'::double precision, 1)
|
||||
Group Key: conditions_2.location
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_2
|
||||
Output: conditions_2.location, conditions_2.allnull, conditions_2.temperature, conditions_2.humidity, conditions_2.bit_int, conditions_2.good_life, conditions_2.timec
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_5_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_7_chunk, _dist_hyper_1_8_chunk
|
||||
Remote SQL: SELECT timec, location, temperature, humidity, allnull, bit_int, good_life FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) ORDER BY location ASC NULLS LAST
|
||||
(28 rows)
|
||||
Sort Key: conditions.location, conditions.timec
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: conditions.location, (min(conditions.allnull)), (max(conditions.temperature)), ((sum(conditions.temperature) + sum(conditions.humidity))), (avg(conditions.humidity)), (round(stddev((conditions.humidity)::integer), 5)), (bit_and(conditions.bit_int)), (bit_or(conditions.bit_int)), (bool_and(conditions.good_life)), (every((conditions.temperature > '0'::double precision))), (bool_or(conditions.good_life)), (count(*)), (count(conditions.temperature)), (count(conditions.allnull)), (round((corr(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((covar_pop(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((covar_samp(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((regr_avgx(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((regr_avgy(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((regr_count(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((regr_intercept(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((regr_r2(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((regr_slope(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((regr_sxx(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((regr_sxy(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round((regr_syy(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision))::numeric, 5)), (round(stddev((conditions.temperature)::integer), 5)), (round(stddev_pop((conditions.temperature)::integer), 5)), (round(stddev_samp((conditions.temperature)::integer), 5)), (round(variance((conditions.temperature)::integer), 5)), (round(var_pop((conditions.temperature)::integer), 5)), (round(var_samp((conditions.temperature)::integer), 5)), (last(conditions.temperature, conditions.timec)), (histogram(conditions.temperature, '0'::double precision, '100'::double precision, 1)), conditions.timec
|
||||
Relations: Aggregate on (public.conditions)
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_1_chunk, _dist_hyper_1_2_chunk, _dist_hyper_1_3_chunk, _dist_hyper_1_4_chunk
|
||||
Remote SQL: SELECT location, min(allnull), max(temperature), (sum(temperature) + sum(humidity)), avg(humidity), round(stddev(humidity::integer), 5), bit_and(bit_int), bit_or(bit_int), bool_and(good_life), every((temperature > 0::double precision)), bool_or(good_life), count(*), count(temperature), count(allnull), round(corr(temperature::integer, humidity::integer)::numeric, 5), round(covar_pop(temperature::integer, humidity::integer)::numeric, 5), round(covar_samp(temperature::integer, humidity::integer)::numeric, 5), round(regr_avgx(temperature::integer, humidity::integer)::numeric, 5), round(regr_avgy(temperature::integer, humidity::integer)::numeric, 5), round(regr_count(temperature::integer, humidity::integer)::numeric, 5), round(regr_intercept(temperature::integer, humidity::integer)::numeric, 5), round(regr_r2(temperature::integer, humidity::integer)::numeric, 5), round(regr_slope(temperature::integer, humidity::integer)::numeric, 5), round(regr_sxx(temperature::integer, humidity::integer)::numeric, 5), round(regr_sxy(temperature::integer, humidity::integer)::numeric, 5), round(regr_syy(temperature::integer, humidity::integer)::numeric, 5), round(stddev(temperature::integer), 5), round(stddev_pop(temperature::integer), 5), round(stddev_samp(temperature::integer), 5), round(variance(temperature::integer), 5), round(var_pop(temperature::integer), 5), round(var_samp(temperature::integer), 5), public.last(temperature, timec), public.histogram(temperature, 0::double precision, 100::double precision, 1), timec FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) GROUP BY 1, 35 ORDER BY location ASC NULLS LAST, timec ASC NULLS LAST
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: conditions_1.location, (min(conditions_1.allnull)), (max(conditions_1.temperature)), ((sum(conditions_1.temperature) + sum(conditions_1.humidity))), (avg(conditions_1.humidity)), (round(stddev((conditions_1.humidity)::integer), 5)), (bit_and(conditions_1.bit_int)), (bit_or(conditions_1.bit_int)), (bool_and(conditions_1.good_life)), (every((conditions_1.temperature > '0'::double precision))), (bool_or(conditions_1.good_life)), (count(*)), (count(conditions_1.temperature)), (count(conditions_1.allnull)), (round((corr(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((covar_pop(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((covar_samp(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((regr_avgx(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((regr_avgy(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((regr_count(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((regr_intercept(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((regr_r2(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((regr_slope(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((regr_sxx(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((regr_sxy(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round((regr_syy(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision))::numeric, 5)), (round(stddev((conditions_1.temperature)::integer), 5)), (round(stddev_pop((conditions_1.temperature)::integer), 5)), (round(stddev_samp((conditions_1.temperature)::integer), 5)), (round(variance((conditions_1.temperature)::integer), 5)), (round(var_pop((conditions_1.temperature)::integer), 5)), (round(var_samp((conditions_1.temperature)::integer), 5)), (last(conditions_1.temperature, conditions_1.timec)), (histogram(conditions_1.temperature, '0'::double precision, '100'::double precision, 1)), conditions_1.timec
|
||||
Relations: Aggregate on (public.conditions)
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_9_chunk, _dist_hyper_1_10_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_12_chunk
|
||||
Remote SQL: SELECT location, min(allnull), max(temperature), (sum(temperature) + sum(humidity)), avg(humidity), round(stddev(humidity::integer), 5), bit_and(bit_int), bit_or(bit_int), bool_and(good_life), every((temperature > 0::double precision)), bool_or(good_life), count(*), count(temperature), count(allnull), round(corr(temperature::integer, humidity::integer)::numeric, 5), round(covar_pop(temperature::integer, humidity::integer)::numeric, 5), round(covar_samp(temperature::integer, humidity::integer)::numeric, 5), round(regr_avgx(temperature::integer, humidity::integer)::numeric, 5), round(regr_avgy(temperature::integer, humidity::integer)::numeric, 5), round(regr_count(temperature::integer, humidity::integer)::numeric, 5), round(regr_intercept(temperature::integer, humidity::integer)::numeric, 5), round(regr_r2(temperature::integer, humidity::integer)::numeric, 5), round(regr_slope(temperature::integer, humidity::integer)::numeric, 5), round(regr_sxx(temperature::integer, humidity::integer)::numeric, 5), round(regr_sxy(temperature::integer, humidity::integer)::numeric, 5), round(regr_syy(temperature::integer, humidity::integer)::numeric, 5), round(stddev(temperature::integer), 5), round(stddev_pop(temperature::integer), 5), round(stddev_samp(temperature::integer), 5), round(variance(temperature::integer), 5), round(var_pop(temperature::integer), 5), round(var_samp(temperature::integer), 5), public.last(temperature, timec), public.histogram(temperature, 0::double precision, 100::double precision, 1), timec FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) GROUP BY 1, 35 ORDER BY location ASC NULLS LAST, timec ASC NULLS LAST
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: conditions_2.location, (min(conditions_2.allnull)), (max(conditions_2.temperature)), ((sum(conditions_2.temperature) + sum(conditions_2.humidity))), (avg(conditions_2.humidity)), (round(stddev((conditions_2.humidity)::integer), 5)), (bit_and(conditions_2.bit_int)), (bit_or(conditions_2.bit_int)), (bool_and(conditions_2.good_life)), (every((conditions_2.temperature > '0'::double precision))), (bool_or(conditions_2.good_life)), (count(*)), (count(conditions_2.temperature)), (count(conditions_2.allnull)), (round((corr(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((covar_pop(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((covar_samp(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((regr_avgx(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((regr_avgy(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((regr_count(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((regr_intercept(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((regr_r2(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((regr_slope(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((regr_sxx(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((regr_sxy(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round((regr_syy(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision))::numeric, 5)), (round(stddev((conditions_2.temperature)::integer), 5)), (round(stddev_pop((conditions_2.temperature)::integer), 5)), (round(stddev_samp((conditions_2.temperature)::integer), 5)), (round(variance((conditions_2.temperature)::integer), 5)), (round(var_pop((conditions_2.temperature)::integer), 5)), (round(var_samp((conditions_2.temperature)::integer), 5)), (last(conditions_2.temperature, conditions_2.timec)), (histogram(conditions_2.temperature, '0'::double precision, '100'::double precision, 1)), conditions_2.timec
|
||||
Relations: Aggregate on (public.conditions)
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_5_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_7_chunk, _dist_hyper_1_8_chunk
|
||||
Remote SQL: SELECT location, min(allnull), max(temperature), (sum(temperature) + sum(humidity)), avg(humidity), round(stddev(humidity::integer), 5), bit_and(bit_int), bit_or(bit_int), bool_and(good_life), every((temperature > 0::double precision)), bool_or(good_life), count(*), count(temperature), count(allnull), round(corr(temperature::integer, humidity::integer)::numeric, 5), round(covar_pop(temperature::integer, humidity::integer)::numeric, 5), round(covar_samp(temperature::integer, humidity::integer)::numeric, 5), round(regr_avgx(temperature::integer, humidity::integer)::numeric, 5), round(regr_avgy(temperature::integer, humidity::integer)::numeric, 5), round(regr_count(temperature::integer, humidity::integer)::numeric, 5), round(regr_intercept(temperature::integer, humidity::integer)::numeric, 5), round(regr_r2(temperature::integer, humidity::integer)::numeric, 5), round(regr_slope(temperature::integer, humidity::integer)::numeric, 5), round(regr_sxx(temperature::integer, humidity::integer)::numeric, 5), round(regr_sxy(temperature::integer, humidity::integer)::numeric, 5), round(regr_syy(temperature::integer, humidity::integer)::numeric, 5), round(stddev(temperature::integer), 5), round(stddev_pop(temperature::integer), 5), round(stddev_samp(temperature::integer), 5), round(variance(temperature::integer), 5), round(var_pop(temperature::integer), 5), round(var_samp(temperature::integer), 5), public.last(temperature, timec), public.histogram(temperature, 0::double precision, 100::double precision, 1), timec FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) GROUP BY 1, 35 ORDER BY location ASC NULLS LAST, timec ASC NULLS LAST
|
||||
(22 rows)
|
||||
|
||||
-- Aggregates on custom types are not yet pushed down
|
||||
:PREFIX SELECT :GROUPING,
|
||||
last(highlow, timec) as last_hl,
|
||||
first(highlow, timec) as first_hl
|
||||
FROM :TEST_TABLE
|
||||
GROUP BY :GROUPING
|
||||
ORDER BY :GROUPING;
|
||||
QUERY PLAN
|
||||
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Sort
|
||||
Output: location, (last(highlow, timec)), (first(highlow, timec))
|
||||
Sort Key: location
|
||||
-> Custom Scan (AsyncAppend)
|
||||
Output: location, (last(highlow, timec)), (first(highlow, timec))
|
||||
-> Append
|
||||
-> HashAggregate
|
||||
Output: conditions.location, last(conditions.highlow, conditions.timec), first(conditions.highlow, conditions.timec)
|
||||
Group Key: conditions.location
|
||||
-> Custom Scan (DataNodeScan) on public.conditions
|
||||
Output: conditions.location, conditions.highlow, conditions.timec
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_1_chunk, _dist_hyper_1_2_chunk, _dist_hyper_1_3_chunk, _dist_hyper_1_4_chunk
|
||||
Remote SQL: SELECT timec, location, highlow FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4])
|
||||
-> HashAggregate
|
||||
Output: conditions_1.location, last(conditions_1.highlow, conditions_1.timec), first(conditions_1.highlow, conditions_1.timec)
|
||||
Group Key: conditions_1.location
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_1
|
||||
Output: conditions_1.location, conditions_1.highlow, conditions_1.timec
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_9_chunk, _dist_hyper_1_10_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_12_chunk
|
||||
Remote SQL: SELECT timec, location, highlow FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4])
|
||||
-> HashAggregate
|
||||
Output: conditions_2.location, last(conditions_2.highlow, conditions_2.timec), first(conditions_2.highlow, conditions_2.timec)
|
||||
Group Key: conditions_2.location
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_2
|
||||
Output: conditions_2.location, conditions_2.highlow, conditions_2.timec
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_5_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_7_chunk, _dist_hyper_1_8_chunk
|
||||
Remote SQL: SELECT timec, location, highlow FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4])
|
||||
(30 rows)
|
||||
GROUP BY :GROUPING, timec
|
||||
ORDER BY :GROUPING, timec;
|
||||
QUERY PLAN
|
||||
-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Merge Append
|
||||
Sort Key: conditions.location, conditions.timec
|
||||
-> GroupAggregate
|
||||
Output: conditions.location, last(conditions.highlow, conditions.timec), first(conditions.highlow, conditions.timec), conditions.timec
|
||||
Group Key: conditions.location, conditions.timec
|
||||
-> Custom Scan (DataNodeScan) on public.conditions
|
||||
Output: conditions.location, conditions.timec, conditions.highlow
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_1_chunk, _dist_hyper_1_2_chunk, _dist_hyper_1_3_chunk, _dist_hyper_1_4_chunk
|
||||
Remote SQL: SELECT timec, location, highlow FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) ORDER BY location ASC NULLS LAST, timec ASC NULLS LAST
|
||||
-> GroupAggregate
|
||||
Output: conditions_1.location, last(conditions_1.highlow, conditions_1.timec), first(conditions_1.highlow, conditions_1.timec), conditions_1.timec
|
||||
Group Key: conditions_1.location, conditions_1.timec
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_1
|
||||
Output: conditions_1.location, conditions_1.timec, conditions_1.highlow
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_9_chunk, _dist_hyper_1_10_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_12_chunk
|
||||
Remote SQL: SELECT timec, location, highlow FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) ORDER BY location ASC NULLS LAST, timec ASC NULLS LAST
|
||||
-> GroupAggregate
|
||||
Output: conditions_2.location, last(conditions_2.highlow, conditions_2.timec), first(conditions_2.highlow, conditions_2.timec), conditions_2.timec
|
||||
Group Key: conditions_2.location, conditions_2.timec
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_2
|
||||
Output: conditions_2.location, conditions_2.timec, conditions_2.highlow
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_5_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_7_chunk, _dist_hyper_1_8_chunk
|
||||
Remote SQL: SELECT timec, location, highlow FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) ORDER BY location ASC NULLS LAST, timec ASC NULLS LAST
|
||||
(26 rows)
|
||||
|
||||
-- Mix of aggregates that push down and those that don't
|
||||
:PREFIX SELECT :GROUPING,
|
||||
@ -254,43 +244,39 @@ SET enable_partitionwise_aggregate = ON;
|
||||
bool_or(good_life),
|
||||
first(highlow, timec) as first_hl
|
||||
FROM :TEST_TABLE
|
||||
GROUP BY :GROUPING
|
||||
ORDER BY :GROUPING;
|
||||
QUERY PLAN
|
||||
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Sort
|
||||
Output: location, (min(allnull)), (max(temperature)), ((sum(temperature) + sum(humidity))), (avg(humidity)), (round(stddev((humidity)::integer), 5)), (bit_and(bit_int)), (bit_or(bit_int)), (bool_and(good_life)), (every((temperature > '0'::double precision))), (bool_or(good_life)), (first(highlow, timec))
|
||||
Sort Key: location
|
||||
-> Custom Scan (AsyncAppend)
|
||||
Output: location, (min(allnull)), (max(temperature)), ((sum(temperature) + sum(humidity))), (avg(humidity)), (round(stddev((humidity)::integer), 5)), (bit_and(bit_int)), (bit_or(bit_int)), (bool_and(good_life)), (every((temperature > '0'::double precision))), (bool_or(good_life)), (first(highlow, timec))
|
||||
-> Append
|
||||
-> HashAggregate
|
||||
Output: conditions.location, min(conditions.allnull), max(conditions.temperature), (sum(conditions.temperature) + sum(conditions.humidity)), avg(conditions.humidity), round(stddev((conditions.humidity)::integer), 5), bit_and(conditions.bit_int), bit_or(conditions.bit_int), bool_and(conditions.good_life), every((conditions.temperature > '0'::double precision)), bool_or(conditions.good_life), first(conditions.highlow, conditions.timec)
|
||||
Group Key: conditions.location
|
||||
-> Custom Scan (DataNodeScan) on public.conditions
|
||||
Output: conditions.location, conditions.allnull, conditions.temperature, conditions.humidity, conditions.bit_int, conditions.good_life, conditions.highlow, conditions.timec
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_1_chunk, _dist_hyper_1_2_chunk, _dist_hyper_1_3_chunk, _dist_hyper_1_4_chunk
|
||||
Remote SQL: SELECT timec, location, temperature, humidity, allnull, highlow, bit_int, good_life FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4])
|
||||
-> HashAggregate
|
||||
Output: conditions_1.location, min(conditions_1.allnull), max(conditions_1.temperature), (sum(conditions_1.temperature) + sum(conditions_1.humidity)), avg(conditions_1.humidity), round(stddev((conditions_1.humidity)::integer), 5), bit_and(conditions_1.bit_int), bit_or(conditions_1.bit_int), bool_and(conditions_1.good_life), every((conditions_1.temperature > '0'::double precision)), bool_or(conditions_1.good_life), first(conditions_1.highlow, conditions_1.timec)
|
||||
Group Key: conditions_1.location
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_1
|
||||
Output: conditions_1.location, conditions_1.allnull, conditions_1.temperature, conditions_1.humidity, conditions_1.bit_int, conditions_1.good_life, conditions_1.highlow, conditions_1.timec
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_9_chunk, _dist_hyper_1_10_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_12_chunk
|
||||
Remote SQL: SELECT timec, location, temperature, humidity, allnull, highlow, bit_int, good_life FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4])
|
||||
-> HashAggregate
|
||||
Output: conditions_2.location, min(conditions_2.allnull), max(conditions_2.temperature), (sum(conditions_2.temperature) + sum(conditions_2.humidity)), avg(conditions_2.humidity), round(stddev((conditions_2.humidity)::integer), 5), bit_and(conditions_2.bit_int), bit_or(conditions_2.bit_int), bool_and(conditions_2.good_life), every((conditions_2.temperature > '0'::double precision)), bool_or(conditions_2.good_life), first(conditions_2.highlow, conditions_2.timec)
|
||||
Group Key: conditions_2.location
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_2
|
||||
Output: conditions_2.location, conditions_2.allnull, conditions_2.temperature, conditions_2.humidity, conditions_2.bit_int, conditions_2.good_life, conditions_2.highlow, conditions_2.timec
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_5_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_7_chunk, _dist_hyper_1_8_chunk
|
||||
Remote SQL: SELECT timec, location, temperature, humidity, allnull, highlow, bit_int, good_life FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4])
|
||||
(30 rows)
|
||||
GROUP BY :GROUPING, timec
|
||||
ORDER BY :GROUPING, timec;
|
||||
QUERY PLAN
|
||||
---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Merge Append
|
||||
Sort Key: conditions.location, conditions.timec
|
||||
-> GroupAggregate
|
||||
Output: conditions.location, min(conditions.allnull), max(conditions.temperature), (sum(conditions.temperature) + sum(conditions.humidity)), avg(conditions.humidity), round(stddev((conditions.humidity)::integer), 5), bit_and(conditions.bit_int), bit_or(conditions.bit_int), bool_and(conditions.good_life), every((conditions.temperature > '0'::double precision)), bool_or(conditions.good_life), first(conditions.highlow, conditions.timec), conditions.timec
|
||||
Group Key: conditions.location, conditions.timec
|
||||
-> Custom Scan (DataNodeScan) on public.conditions
|
||||
Output: conditions.location, conditions.timec, conditions.allnull, conditions.temperature, conditions.humidity, conditions.bit_int, conditions.good_life, conditions.highlow
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_1_chunk, _dist_hyper_1_2_chunk, _dist_hyper_1_3_chunk, _dist_hyper_1_4_chunk
|
||||
Remote SQL: SELECT timec, location, temperature, humidity, allnull, highlow, bit_int, good_life FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) ORDER BY location ASC NULLS LAST, timec ASC NULLS LAST
|
||||
-> GroupAggregate
|
||||
Output: conditions_1.location, min(conditions_1.allnull), max(conditions_1.temperature), (sum(conditions_1.temperature) + sum(conditions_1.humidity)), avg(conditions_1.humidity), round(stddev((conditions_1.humidity)::integer), 5), bit_and(conditions_1.bit_int), bit_or(conditions_1.bit_int), bool_and(conditions_1.good_life), every((conditions_1.temperature > '0'::double precision)), bool_or(conditions_1.good_life), first(conditions_1.highlow, conditions_1.timec), conditions_1.timec
|
||||
Group Key: conditions_1.location, conditions_1.timec
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_1
|
||||
Output: conditions_1.location, conditions_1.timec, conditions_1.allnull, conditions_1.temperature, conditions_1.humidity, conditions_1.bit_int, conditions_1.good_life, conditions_1.highlow
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_9_chunk, _dist_hyper_1_10_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_12_chunk
|
||||
Remote SQL: SELECT timec, location, temperature, humidity, allnull, highlow, bit_int, good_life FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) ORDER BY location ASC NULLS LAST, timec ASC NULLS LAST
|
||||
-> GroupAggregate
|
||||
Output: conditions_2.location, min(conditions_2.allnull), max(conditions_2.temperature), (sum(conditions_2.temperature) + sum(conditions_2.humidity)), avg(conditions_2.humidity), round(stddev((conditions_2.humidity)::integer), 5), bit_and(conditions_2.bit_int), bit_or(conditions_2.bit_int), bool_and(conditions_2.good_life), every((conditions_2.temperature > '0'::double precision)), bool_or(conditions_2.good_life), first(conditions_2.highlow, conditions_2.timec), conditions_2.timec
|
||||
Group Key: conditions_2.location, conditions_2.timec
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_2
|
||||
Output: conditions_2.location, conditions_2.timec, conditions_2.allnull, conditions_2.temperature, conditions_2.humidity, conditions_2.bit_int, conditions_2.good_life, conditions_2.highlow
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_5_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_7_chunk, _dist_hyper_1_8_chunk
|
||||
Remote SQL: SELECT timec, location, temperature, humidity, allnull, highlow, bit_int, good_life FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) ORDER BY location ASC NULLS LAST, timec ASC NULLS LAST
|
||||
(26 rows)
|
||||
|
||||
\set GROUPING 'region'
|
||||
\set GROUPING 'region, temperature'
|
||||
\ir 'include/aggregate_queries.sql'
|
||||
-- This file and its contents are licensed under the Timescale License.
|
||||
-- Please see the included NOTICE for copyright information and
|
||||
@ -332,86 +318,76 @@ SET enable_partitionwise_aggregate = ON;
|
||||
last(temperature, timec) as last_temp,
|
||||
histogram(temperature, 0, 100, 1)
|
||||
FROM :TEST_TABLE
|
||||
GROUP BY :GROUPING
|
||||
ORDER BY :GROUPING;
|
||||
QUERY PLAN
|
||||
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
GROUP BY :GROUPING, timec
|
||||
ORDER BY :GROUPING, timec;
|
||||
QUERY PLAN
|
||||
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Finalize GroupAggregate
|
||||
Output: region, min(allnull), max(temperature), (sum(temperature) + sum(humidity)), avg(humidity), round(stddev((humidity)::integer), 5), bit_and(bit_int), bit_or(bit_int), bool_and(good_life), every((temperature > '0'::double precision)), bool_or(good_life), count(*), count(temperature), count(allnull), round((corr(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((covar_pop(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((covar_samp(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_avgx(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_avgy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_count(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_intercept(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_r2(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_slope(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_sxx(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_sxy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_syy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round(stddev((temperature)::integer), 5), round(stddev_pop((temperature)::integer), 5), round(stddev_samp((temperature)::integer), 5), round(variance((temperature)::integer), 5), round(var_pop((temperature)::integer), 5), round(var_samp((temperature)::integer), 5), last(temperature, timec), histogram(temperature, '0'::double precision, '100'::double precision, 1)
|
||||
Group Key: region
|
||||
Output: region, temperature, min(allnull), max(temperature), (sum(temperature) + sum(humidity)), avg(humidity), round(stddev((humidity)::integer), 5), bit_and(bit_int), bit_or(bit_int), bool_and(good_life), every((temperature > '0'::double precision)), bool_or(good_life), count(*), count(temperature), count(allnull), round((corr(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((covar_pop(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((covar_samp(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_avgx(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_avgy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_count(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_intercept(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_r2(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_slope(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_sxx(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_sxy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round((regr_syy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision))::numeric, 5), round(stddev((temperature)::integer), 5), round(stddev_pop((temperature)::integer), 5), round(stddev_samp((temperature)::integer), 5), round(variance((temperature)::integer), 5), round(var_pop((temperature)::integer), 5), round(var_samp((temperature)::integer), 5), last(temperature, timec), histogram(temperature, '0'::double precision, '100'::double precision, 1), timec
|
||||
Group Key: region, temperature, timec
|
||||
-> Custom Scan (AsyncAppend)
|
||||
Output: region, (PARTIAL min(allnull)), (PARTIAL max(temperature)), (PARTIAL sum(temperature)), (PARTIAL sum(humidity)), (PARTIAL avg(humidity)), (PARTIAL stddev((humidity)::integer)), (PARTIAL bit_and(bit_int)), (PARTIAL bit_or(bit_int)), (PARTIAL bool_and(good_life)), (PARTIAL every((temperature > '0'::double precision))), (PARTIAL bool_or(good_life)), (PARTIAL count(*)), (PARTIAL count(temperature)), (PARTIAL count(allnull)), (PARTIAL corr(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL covar_pop(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL covar_samp(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_avgx(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_avgy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_count(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_intercept(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_r2(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_slope(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_sxx(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_sxy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_syy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL stddev((temperature)::integer)), (PARTIAL stddev_pop((temperature)::integer)), (PARTIAL stddev_samp((temperature)::integer)), (PARTIAL variance((temperature)::integer)), (PARTIAL var_pop((temperature)::integer)), (PARTIAL var_samp((temperature)::integer)), (PARTIAL last(temperature, timec)), (PARTIAL histogram(temperature, '0'::double precision, '100'::double precision, 1))
|
||||
Output: region, temperature, timec, (PARTIAL min(allnull)), (PARTIAL max(temperature)), (PARTIAL sum(temperature)), (PARTIAL sum(humidity)), (PARTIAL avg(humidity)), (PARTIAL stddev((humidity)::integer)), (PARTIAL bit_and(bit_int)), (PARTIAL bit_or(bit_int)), (PARTIAL bool_and(good_life)), (PARTIAL every((temperature > '0'::double precision))), (PARTIAL bool_or(good_life)), (PARTIAL count(*)), (PARTIAL count(temperature)), (PARTIAL count(allnull)), (PARTIAL corr(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL covar_pop(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL covar_samp(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_avgx(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_avgy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_count(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_intercept(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_r2(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_slope(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_sxx(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_sxy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL regr_syy(((temperature)::integer)::double precision, ((humidity)::integer)::double precision)), (PARTIAL stddev((temperature)::integer)), (PARTIAL stddev_pop((temperature)::integer)), (PARTIAL stddev_samp((temperature)::integer)), (PARTIAL variance((temperature)::integer)), (PARTIAL var_pop((temperature)::integer)), (PARTIAL var_samp((temperature)::integer)), (PARTIAL last(temperature, timec)), (PARTIAL histogram(temperature, '0'::double precision, '100'::double precision, 1))
|
||||
-> Merge Append
|
||||
Sort Key: conditions.region
|
||||
-> Partial GroupAggregate
|
||||
Output: conditions.region, PARTIAL min(conditions.allnull), PARTIAL max(conditions.temperature), PARTIAL sum(conditions.temperature), PARTIAL sum(conditions.humidity), PARTIAL avg(conditions.humidity), PARTIAL stddev((conditions.humidity)::integer), PARTIAL bit_and(conditions.bit_int), PARTIAL bit_or(conditions.bit_int), PARTIAL bool_and(conditions.good_life), PARTIAL every((conditions.temperature > '0'::double precision)), PARTIAL bool_or(conditions.good_life), PARTIAL count(*), PARTIAL count(conditions.temperature), PARTIAL count(conditions.allnull), PARTIAL corr(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision), PARTIAL covar_pop(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision), PARTIAL covar_samp(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision), PARTIAL regr_avgx(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision), PARTIAL regr_avgy(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision), PARTIAL regr_count(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision), PARTIAL regr_intercept(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision), PARTIAL regr_r2(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision), PARTIAL regr_slope(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision), PARTIAL regr_sxx(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision), PARTIAL regr_sxy(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision), PARTIAL regr_syy(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision), PARTIAL stddev((conditions.temperature)::integer), PARTIAL stddev_pop((conditions.temperature)::integer), PARTIAL stddev_samp((conditions.temperature)::integer), PARTIAL variance((conditions.temperature)::integer), PARTIAL var_pop((conditions.temperature)::integer), PARTIAL var_samp((conditions.temperature)::integer), PARTIAL last(conditions.temperature, conditions.timec), PARTIAL histogram(conditions.temperature, '0'::double precision, '100'::double precision, 1)
|
||||
Group Key: conditions.region
|
||||
-> Custom Scan (DataNodeScan) on public.conditions
|
||||
Output: conditions.region, conditions.allnull, conditions.temperature, conditions.humidity, conditions.bit_int, conditions.good_life, conditions.timec
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_1_chunk, _dist_hyper_1_2_chunk, _dist_hyper_1_3_chunk, _dist_hyper_1_4_chunk
|
||||
Remote SQL: SELECT timec, region, temperature, humidity, allnull, bit_int, good_life FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) ORDER BY region ASC NULLS LAST
|
||||
-> Partial GroupAggregate
|
||||
Output: conditions_1.region, PARTIAL min(conditions_1.allnull), PARTIAL max(conditions_1.temperature), PARTIAL sum(conditions_1.temperature), PARTIAL sum(conditions_1.humidity), PARTIAL avg(conditions_1.humidity), PARTIAL stddev((conditions_1.humidity)::integer), PARTIAL bit_and(conditions_1.bit_int), PARTIAL bit_or(conditions_1.bit_int), PARTIAL bool_and(conditions_1.good_life), PARTIAL every((conditions_1.temperature > '0'::double precision)), PARTIAL bool_or(conditions_1.good_life), PARTIAL count(*), PARTIAL count(conditions_1.temperature), PARTIAL count(conditions_1.allnull), PARTIAL corr(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision), PARTIAL covar_pop(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision), PARTIAL covar_samp(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision), PARTIAL regr_avgx(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision), PARTIAL regr_avgy(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision), PARTIAL regr_count(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision), PARTIAL regr_intercept(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision), PARTIAL regr_r2(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision), PARTIAL regr_slope(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision), PARTIAL regr_sxx(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision), PARTIAL regr_sxy(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision), PARTIAL regr_syy(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision), PARTIAL stddev((conditions_1.temperature)::integer), PARTIAL stddev_pop((conditions_1.temperature)::integer), PARTIAL stddev_samp((conditions_1.temperature)::integer), PARTIAL variance((conditions_1.temperature)::integer), PARTIAL var_pop((conditions_1.temperature)::integer), PARTIAL var_samp((conditions_1.temperature)::integer), PARTIAL last(conditions_1.temperature, conditions_1.timec), PARTIAL histogram(conditions_1.temperature, '0'::double precision, '100'::double precision, 1)
|
||||
Group Key: conditions_1.region
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_1
|
||||
Output: conditions_1.region, conditions_1.allnull, conditions_1.temperature, conditions_1.humidity, conditions_1.bit_int, conditions_1.good_life, conditions_1.timec
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_9_chunk, _dist_hyper_1_10_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_12_chunk
|
||||
Remote SQL: SELECT timec, region, temperature, humidity, allnull, bit_int, good_life FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) ORDER BY region ASC NULLS LAST
|
||||
-> Partial GroupAggregate
|
||||
Output: conditions_2.region, PARTIAL min(conditions_2.allnull), PARTIAL max(conditions_2.temperature), PARTIAL sum(conditions_2.temperature), PARTIAL sum(conditions_2.humidity), PARTIAL avg(conditions_2.humidity), PARTIAL stddev((conditions_2.humidity)::integer), PARTIAL bit_and(conditions_2.bit_int), PARTIAL bit_or(conditions_2.bit_int), PARTIAL bool_and(conditions_2.good_life), PARTIAL every((conditions_2.temperature > '0'::double precision)), PARTIAL bool_or(conditions_2.good_life), PARTIAL count(*), PARTIAL count(conditions_2.temperature), PARTIAL count(conditions_2.allnull), PARTIAL corr(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision), PARTIAL covar_pop(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision), PARTIAL covar_samp(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision), PARTIAL regr_avgx(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision), PARTIAL regr_avgy(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision), PARTIAL regr_count(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision), PARTIAL regr_intercept(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision), PARTIAL regr_r2(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision), PARTIAL regr_slope(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision), PARTIAL regr_sxx(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision), PARTIAL regr_sxy(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision), PARTIAL regr_syy(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision), PARTIAL stddev((conditions_2.temperature)::integer), PARTIAL stddev_pop((conditions_2.temperature)::integer), PARTIAL stddev_samp((conditions_2.temperature)::integer), PARTIAL variance((conditions_2.temperature)::integer), PARTIAL var_pop((conditions_2.temperature)::integer), PARTIAL var_samp((conditions_2.temperature)::integer), PARTIAL last(conditions_2.temperature, conditions_2.timec), PARTIAL histogram(conditions_2.temperature, '0'::double precision, '100'::double precision, 1)
|
||||
Group Key: conditions_2.region
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_2
|
||||
Output: conditions_2.region, conditions_2.allnull, conditions_2.temperature, conditions_2.humidity, conditions_2.bit_int, conditions_2.good_life, conditions_2.timec
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_5_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_7_chunk, _dist_hyper_1_8_chunk
|
||||
Remote SQL: SELECT timec, region, temperature, humidity, allnull, bit_int, good_life FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) ORDER BY region ASC NULLS LAST
|
||||
(31 rows)
|
||||
Sort Key: conditions.region, conditions.temperature, conditions.timec
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: conditions.region, conditions.temperature, conditions.timec, (PARTIAL min(conditions.allnull)), (PARTIAL max(conditions.temperature)), (PARTIAL sum(conditions.temperature)), (PARTIAL sum(conditions.humidity)), (PARTIAL avg(conditions.humidity)), (PARTIAL stddev((conditions.humidity)::integer)), (PARTIAL bit_and(conditions.bit_int)), (PARTIAL bit_or(conditions.bit_int)), (PARTIAL bool_and(conditions.good_life)), (PARTIAL every((conditions.temperature > '0'::double precision))), (PARTIAL bool_or(conditions.good_life)), (PARTIAL count(*)), (PARTIAL count(conditions.temperature)), (PARTIAL count(conditions.allnull)), (PARTIAL corr(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL covar_pop(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL covar_samp(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL regr_avgx(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL regr_avgy(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL regr_count(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL regr_intercept(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL regr_r2(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL regr_slope(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL regr_sxx(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL regr_sxy(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL regr_syy(((conditions.temperature)::integer)::double precision, ((conditions.humidity)::integer)::double precision)), (PARTIAL stddev((conditions.temperature)::integer)), (PARTIAL stddev_pop((conditions.temperature)::integer)), (PARTIAL stddev_samp((conditions.temperature)::integer)), (PARTIAL variance((conditions.temperature)::integer)), (PARTIAL var_pop((conditions.temperature)::integer)), (PARTIAL var_samp((conditions.temperature)::integer)), (PARTIAL last(conditions.temperature, conditions.timec)), (PARTIAL histogram(conditions.temperature, '0'::double precision, '100'::double precision, 1))
|
||||
Relations: Aggregate on (public.conditions)
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_1_chunk, _dist_hyper_1_2_chunk, _dist_hyper_1_3_chunk, _dist_hyper_1_4_chunk
|
||||
Remote SQL: SELECT region, temperature, timec, _timescaledb_internal.partialize_agg(min(allnull)), _timescaledb_internal.partialize_agg(max(temperature)), _timescaledb_internal.partialize_agg(sum(temperature)), _timescaledb_internal.partialize_agg(sum(humidity)), _timescaledb_internal.partialize_agg(avg(humidity)), _timescaledb_internal.partialize_agg(stddev(humidity::integer)), _timescaledb_internal.partialize_agg(bit_and(bit_int)), _timescaledb_internal.partialize_agg(bit_or(bit_int)), _timescaledb_internal.partialize_agg(bool_and(good_life)), _timescaledb_internal.partialize_agg(every((temperature > 0::double precision))), _timescaledb_internal.partialize_agg(bool_or(good_life)), _timescaledb_internal.partialize_agg(count(*)), _timescaledb_internal.partialize_agg(count(temperature)), _timescaledb_internal.partialize_agg(count(allnull)), _timescaledb_internal.partialize_agg(corr(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(covar_pop(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(covar_samp(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_avgx(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_avgy(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_count(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_intercept(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_r2(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_slope(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_sxx(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_sxy(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_syy(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(stddev(temperature::integer)), _timescaledb_internal.partialize_agg(stddev_pop(temperature::integer)), _timescaledb_internal.partialize_agg(stddev_samp(temperature::integer)), _timescaledb_internal.partialize_agg(variance(temperature::integer)), _timescaledb_internal.partialize_agg(var_pop(temperature::integer)), _timescaledb_internal.partialize_agg(var_samp(temperature::integer)), _timescaledb_internal.partialize_agg(public.last(temperature, timec)), _timescaledb_internal.partialize_agg(public.histogram(temperature, 0::double precision, 100::double precision, 1)) FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) GROUP BY 1, 2, 3 ORDER BY region ASC NULLS LAST, temperature ASC NULLS LAST, timec ASC NULLS LAST
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: conditions_1.region, conditions_1.temperature, conditions_1.timec, (PARTIAL min(conditions_1.allnull)), (PARTIAL max(conditions_1.temperature)), (PARTIAL sum(conditions_1.temperature)), (PARTIAL sum(conditions_1.humidity)), (PARTIAL avg(conditions_1.humidity)), (PARTIAL stddev((conditions_1.humidity)::integer)), (PARTIAL bit_and(conditions_1.bit_int)), (PARTIAL bit_or(conditions_1.bit_int)), (PARTIAL bool_and(conditions_1.good_life)), (PARTIAL every((conditions_1.temperature > '0'::double precision))), (PARTIAL bool_or(conditions_1.good_life)), (PARTIAL count(*)), (PARTIAL count(conditions_1.temperature)), (PARTIAL count(conditions_1.allnull)), (PARTIAL corr(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL covar_pop(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL covar_samp(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL regr_avgx(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL regr_avgy(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL regr_count(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL regr_intercept(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL regr_r2(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL regr_slope(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL regr_sxx(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL regr_sxy(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL regr_syy(((conditions_1.temperature)::integer)::double precision, ((conditions_1.humidity)::integer)::double precision)), (PARTIAL stddev((conditions_1.temperature)::integer)), (PARTIAL stddev_pop((conditions_1.temperature)::integer)), (PARTIAL stddev_samp((conditions_1.temperature)::integer)), (PARTIAL variance((conditions_1.temperature)::integer)), (PARTIAL var_pop((conditions_1.temperature)::integer)), (PARTIAL var_samp((conditions_1.temperature)::integer)), (PARTIAL last(conditions_1.temperature, conditions_1.timec)), (PARTIAL histogram(conditions_1.temperature, '0'::double precision, '100'::double precision, 1))
|
||||
Relations: Aggregate on (public.conditions)
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_9_chunk, _dist_hyper_1_10_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_12_chunk
|
||||
Remote SQL: SELECT region, temperature, timec, _timescaledb_internal.partialize_agg(min(allnull)), _timescaledb_internal.partialize_agg(max(temperature)), _timescaledb_internal.partialize_agg(sum(temperature)), _timescaledb_internal.partialize_agg(sum(humidity)), _timescaledb_internal.partialize_agg(avg(humidity)), _timescaledb_internal.partialize_agg(stddev(humidity::integer)), _timescaledb_internal.partialize_agg(bit_and(bit_int)), _timescaledb_internal.partialize_agg(bit_or(bit_int)), _timescaledb_internal.partialize_agg(bool_and(good_life)), _timescaledb_internal.partialize_agg(every((temperature > 0::double precision))), _timescaledb_internal.partialize_agg(bool_or(good_life)), _timescaledb_internal.partialize_agg(count(*)), _timescaledb_internal.partialize_agg(count(temperature)), _timescaledb_internal.partialize_agg(count(allnull)), _timescaledb_internal.partialize_agg(corr(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(covar_pop(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(covar_samp(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_avgx(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_avgy(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_count(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_intercept(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_r2(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_slope(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_sxx(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_sxy(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_syy(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(stddev(temperature::integer)), _timescaledb_internal.partialize_agg(stddev_pop(temperature::integer)), _timescaledb_internal.partialize_agg(stddev_samp(temperature::integer)), _timescaledb_internal.partialize_agg(variance(temperature::integer)), _timescaledb_internal.partialize_agg(var_pop(temperature::integer)), _timescaledb_internal.partialize_agg(var_samp(temperature::integer)), _timescaledb_internal.partialize_agg(public.last(temperature, timec)), _timescaledb_internal.partialize_agg(public.histogram(temperature, 0::double precision, 100::double precision, 1)) FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) GROUP BY 1, 2, 3 ORDER BY region ASC NULLS LAST, temperature ASC NULLS LAST, timec ASC NULLS LAST
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: conditions_2.region, conditions_2.temperature, conditions_2.timec, (PARTIAL min(conditions_2.allnull)), (PARTIAL max(conditions_2.temperature)), (PARTIAL sum(conditions_2.temperature)), (PARTIAL sum(conditions_2.humidity)), (PARTIAL avg(conditions_2.humidity)), (PARTIAL stddev((conditions_2.humidity)::integer)), (PARTIAL bit_and(conditions_2.bit_int)), (PARTIAL bit_or(conditions_2.bit_int)), (PARTIAL bool_and(conditions_2.good_life)), (PARTIAL every((conditions_2.temperature > '0'::double precision))), (PARTIAL bool_or(conditions_2.good_life)), (PARTIAL count(*)), (PARTIAL count(conditions_2.temperature)), (PARTIAL count(conditions_2.allnull)), (PARTIAL corr(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL covar_pop(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL covar_samp(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL regr_avgx(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL regr_avgy(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL regr_count(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL regr_intercept(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL regr_r2(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL regr_slope(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL regr_sxx(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL regr_sxy(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL regr_syy(((conditions_2.temperature)::integer)::double precision, ((conditions_2.humidity)::integer)::double precision)), (PARTIAL stddev((conditions_2.temperature)::integer)), (PARTIAL stddev_pop((conditions_2.temperature)::integer)), (PARTIAL stddev_samp((conditions_2.temperature)::integer)), (PARTIAL variance((conditions_2.temperature)::integer)), (PARTIAL var_pop((conditions_2.temperature)::integer)), (PARTIAL var_samp((conditions_2.temperature)::integer)), (PARTIAL last(conditions_2.temperature, conditions_2.timec)), (PARTIAL histogram(conditions_2.temperature, '0'::double precision, '100'::double precision, 1))
|
||||
Relations: Aggregate on (public.conditions)
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_5_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_7_chunk, _dist_hyper_1_8_chunk
|
||||
Remote SQL: SELECT region, temperature, timec, _timescaledb_internal.partialize_agg(min(allnull)), _timescaledb_internal.partialize_agg(max(temperature)), _timescaledb_internal.partialize_agg(sum(temperature)), _timescaledb_internal.partialize_agg(sum(humidity)), _timescaledb_internal.partialize_agg(avg(humidity)), _timescaledb_internal.partialize_agg(stddev(humidity::integer)), _timescaledb_internal.partialize_agg(bit_and(bit_int)), _timescaledb_internal.partialize_agg(bit_or(bit_int)), _timescaledb_internal.partialize_agg(bool_and(good_life)), _timescaledb_internal.partialize_agg(every((temperature > 0::double precision))), _timescaledb_internal.partialize_agg(bool_or(good_life)), _timescaledb_internal.partialize_agg(count(*)), _timescaledb_internal.partialize_agg(count(temperature)), _timescaledb_internal.partialize_agg(count(allnull)), _timescaledb_internal.partialize_agg(corr(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(covar_pop(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(covar_samp(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_avgx(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_avgy(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_count(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_intercept(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_r2(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_slope(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_sxx(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_sxy(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(regr_syy(temperature::integer, humidity::integer)), _timescaledb_internal.partialize_agg(stddev(temperature::integer)), _timescaledb_internal.partialize_agg(stddev_pop(temperature::integer)), _timescaledb_internal.partialize_agg(stddev_samp(temperature::integer)), _timescaledb_internal.partialize_agg(variance(temperature::integer)), _timescaledb_internal.partialize_agg(var_pop(temperature::integer)), _timescaledb_internal.partialize_agg(var_samp(temperature::integer)), _timescaledb_internal.partialize_agg(public.last(temperature, timec)), _timescaledb_internal.partialize_agg(public.histogram(temperature, 0::double precision, 100::double precision, 1)) FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) GROUP BY 1, 2, 3 ORDER BY region ASC NULLS LAST, temperature ASC NULLS LAST, timec ASC NULLS LAST
|
||||
(25 rows)
|
||||
|
||||
-- Aggregates on custom types are not yet pushed down
|
||||
:PREFIX SELECT :GROUPING,
|
||||
last(highlow, timec) as last_hl,
|
||||
first(highlow, timec) as first_hl
|
||||
FROM :TEST_TABLE
|
||||
GROUP BY :GROUPING
|
||||
ORDER BY :GROUPING;
|
||||
QUERY PLAN
|
||||
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
GROUP BY :GROUPING, timec
|
||||
ORDER BY :GROUPING, timec;
|
||||
QUERY PLAN
|
||||
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Finalize GroupAggregate
|
||||
Output: region, last(highlow, timec), first(highlow, timec)
|
||||
Group Key: region
|
||||
-> Sort
|
||||
Output: region, (PARTIAL last(highlow, timec)), (PARTIAL first(highlow, timec))
|
||||
Sort Key: region
|
||||
-> Custom Scan (AsyncAppend)
|
||||
Output: region, (PARTIAL last(highlow, timec)), (PARTIAL first(highlow, timec))
|
||||
-> Append
|
||||
-> Partial HashAggregate
|
||||
Output: conditions.region, PARTIAL last(conditions.highlow, conditions.timec), PARTIAL first(conditions.highlow, conditions.timec)
|
||||
Group Key: conditions.region
|
||||
-> Custom Scan (DataNodeScan) on public.conditions
|
||||
Output: conditions.region, conditions.highlow, conditions.timec
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_1_chunk, _dist_hyper_1_2_chunk, _dist_hyper_1_3_chunk, _dist_hyper_1_4_chunk
|
||||
Remote SQL: SELECT timec, region, highlow FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4])
|
||||
-> Partial HashAggregate
|
||||
Output: conditions_1.region, PARTIAL last(conditions_1.highlow, conditions_1.timec), PARTIAL first(conditions_1.highlow, conditions_1.timec)
|
||||
Group Key: conditions_1.region
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_1
|
||||
Output: conditions_1.region, conditions_1.highlow, conditions_1.timec
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_9_chunk, _dist_hyper_1_10_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_12_chunk
|
||||
Remote SQL: SELECT timec, region, highlow FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4])
|
||||
-> Partial HashAggregate
|
||||
Output: conditions_2.region, PARTIAL last(conditions_2.highlow, conditions_2.timec), PARTIAL first(conditions_2.highlow, conditions_2.timec)
|
||||
Group Key: conditions_2.region
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_2
|
||||
Output: conditions_2.region, conditions_2.highlow, conditions_2.timec
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_5_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_7_chunk, _dist_hyper_1_8_chunk
|
||||
Remote SQL: SELECT timec, region, highlow FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4])
|
||||
(33 rows)
|
||||
Output: conditions.region, conditions.temperature, last(conditions.highlow, conditions.timec), first(conditions.highlow, conditions.timec), conditions.timec
|
||||
Group Key: conditions.region, conditions.temperature, conditions.timec
|
||||
-> Merge Append
|
||||
Sort Key: conditions.region, conditions.temperature, conditions.timec
|
||||
-> Partial GroupAggregate
|
||||
Output: conditions.region, conditions.temperature, conditions.timec, PARTIAL last(conditions.highlow, conditions.timec), PARTIAL first(conditions.highlow, conditions.timec)
|
||||
Group Key: conditions.region, conditions.temperature, conditions.timec
|
||||
-> Custom Scan (DataNodeScan) on public.conditions
|
||||
Output: conditions.region, conditions.temperature, conditions.timec, conditions.highlow
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_1_chunk, _dist_hyper_1_2_chunk, _dist_hyper_1_3_chunk, _dist_hyper_1_4_chunk
|
||||
Remote SQL: SELECT timec, region, temperature, highlow FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) ORDER BY region ASC NULLS LAST, temperature ASC NULLS LAST, timec ASC NULLS LAST
|
||||
-> Partial GroupAggregate
|
||||
Output: conditions_1.region, conditions_1.temperature, conditions_1.timec, PARTIAL last(conditions_1.highlow, conditions_1.timec), PARTIAL first(conditions_1.highlow, conditions_1.timec)
|
||||
Group Key: conditions_1.region, conditions_1.temperature, conditions_1.timec
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_1
|
||||
Output: conditions_1.region, conditions_1.temperature, conditions_1.timec, conditions_1.highlow
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_9_chunk, _dist_hyper_1_10_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_12_chunk
|
||||
Remote SQL: SELECT timec, region, temperature, highlow FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) ORDER BY region ASC NULLS LAST, temperature ASC NULLS LAST, timec ASC NULLS LAST
|
||||
-> Partial GroupAggregate
|
||||
Output: conditions_2.region, conditions_2.temperature, conditions_2.timec, PARTIAL last(conditions_2.highlow, conditions_2.timec), PARTIAL first(conditions_2.highlow, conditions_2.timec)
|
||||
Group Key: conditions_2.region, conditions_2.temperature, conditions_2.timec
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_2
|
||||
Output: conditions_2.region, conditions_2.temperature, conditions_2.timec, conditions_2.highlow
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_5_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_7_chunk, _dist_hyper_1_8_chunk
|
||||
Remote SQL: SELECT timec, region, temperature, highlow FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) ORDER BY region ASC NULLS LAST, temperature ASC NULLS LAST, timec ASC NULLS LAST
|
||||
(29 rows)
|
||||
|
||||
-- Mix of aggregates that push down and those that don't
|
||||
:PREFIX SELECT :GROUPING,
|
||||
@ -427,44 +403,40 @@ SET enable_partitionwise_aggregate = ON;
|
||||
bool_or(good_life),
|
||||
first(highlow, timec) as first_hl
|
||||
FROM :TEST_TABLE
|
||||
GROUP BY :GROUPING
|
||||
ORDER BY :GROUPING;
|
||||
QUERY PLAN
|
||||
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
GROUP BY :GROUPING, timec
|
||||
ORDER BY :GROUPING, timec;
|
||||
QUERY PLAN
|
||||
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Finalize GroupAggregate
|
||||
Output: region, min(allnull), max(temperature), (sum(temperature) + sum(humidity)), avg(humidity), round(stddev((humidity)::integer), 5), bit_and(bit_int), bit_or(bit_int), bool_and(good_life), every((temperature > '0'::double precision)), bool_or(good_life), first(highlow, timec)
|
||||
Group Key: region
|
||||
-> Sort
|
||||
Output: region, (PARTIAL min(allnull)), (PARTIAL max(temperature)), (PARTIAL sum(temperature)), (PARTIAL sum(humidity)), (PARTIAL avg(humidity)), (PARTIAL stddev((humidity)::integer)), (PARTIAL bit_and(bit_int)), (PARTIAL bit_or(bit_int)), (PARTIAL bool_and(good_life)), (PARTIAL every((temperature > '0'::double precision))), (PARTIAL bool_or(good_life)), (PARTIAL first(highlow, timec))
|
||||
Sort Key: region
|
||||
-> Custom Scan (AsyncAppend)
|
||||
Output: region, (PARTIAL min(allnull)), (PARTIAL max(temperature)), (PARTIAL sum(temperature)), (PARTIAL sum(humidity)), (PARTIAL avg(humidity)), (PARTIAL stddev((humidity)::integer)), (PARTIAL bit_and(bit_int)), (PARTIAL bit_or(bit_int)), (PARTIAL bool_and(good_life)), (PARTIAL every((temperature > '0'::double precision))), (PARTIAL bool_or(good_life)), (PARTIAL first(highlow, timec))
|
||||
-> Append
|
||||
-> Partial HashAggregate
|
||||
Output: conditions.region, PARTIAL min(conditions.allnull), PARTIAL max(conditions.temperature), PARTIAL sum(conditions.temperature), PARTIAL sum(conditions.humidity), PARTIAL avg(conditions.humidity), PARTIAL stddev((conditions.humidity)::integer), PARTIAL bit_and(conditions.bit_int), PARTIAL bit_or(conditions.bit_int), PARTIAL bool_and(conditions.good_life), PARTIAL every((conditions.temperature > '0'::double precision)), PARTIAL bool_or(conditions.good_life), PARTIAL first(conditions.highlow, conditions.timec)
|
||||
Group Key: conditions.region
|
||||
-> Custom Scan (DataNodeScan) on public.conditions
|
||||
Output: conditions.region, conditions.allnull, conditions.temperature, conditions.humidity, conditions.bit_int, conditions.good_life, conditions.highlow, conditions.timec
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_1_chunk, _dist_hyper_1_2_chunk, _dist_hyper_1_3_chunk, _dist_hyper_1_4_chunk
|
||||
Remote SQL: SELECT timec, region, temperature, humidity, allnull, highlow, bit_int, good_life FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4])
|
||||
-> Partial HashAggregate
|
||||
Output: conditions_1.region, PARTIAL min(conditions_1.allnull), PARTIAL max(conditions_1.temperature), PARTIAL sum(conditions_1.temperature), PARTIAL sum(conditions_1.humidity), PARTIAL avg(conditions_1.humidity), PARTIAL stddev((conditions_1.humidity)::integer), PARTIAL bit_and(conditions_1.bit_int), PARTIAL bit_or(conditions_1.bit_int), PARTIAL bool_and(conditions_1.good_life), PARTIAL every((conditions_1.temperature > '0'::double precision)), PARTIAL bool_or(conditions_1.good_life), PARTIAL first(conditions_1.highlow, conditions_1.timec)
|
||||
Group Key: conditions_1.region
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_1
|
||||
Output: conditions_1.region, conditions_1.allnull, conditions_1.temperature, conditions_1.humidity, conditions_1.bit_int, conditions_1.good_life, conditions_1.highlow, conditions_1.timec
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_9_chunk, _dist_hyper_1_10_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_12_chunk
|
||||
Remote SQL: SELECT timec, region, temperature, humidity, allnull, highlow, bit_int, good_life FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4])
|
||||
-> Partial HashAggregate
|
||||
Output: conditions_2.region, PARTIAL min(conditions_2.allnull), PARTIAL max(conditions_2.temperature), PARTIAL sum(conditions_2.temperature), PARTIAL sum(conditions_2.humidity), PARTIAL avg(conditions_2.humidity), PARTIAL stddev((conditions_2.humidity)::integer), PARTIAL bit_and(conditions_2.bit_int), PARTIAL bit_or(conditions_2.bit_int), PARTIAL bool_and(conditions_2.good_life), PARTIAL every((conditions_2.temperature > '0'::double precision)), PARTIAL bool_or(conditions_2.good_life), PARTIAL first(conditions_2.highlow, conditions_2.timec)
|
||||
Group Key: conditions_2.region
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_2
|
||||
Output: conditions_2.region, conditions_2.allnull, conditions_2.temperature, conditions_2.humidity, conditions_2.bit_int, conditions_2.good_life, conditions_2.highlow, conditions_2.timec
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_5_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_7_chunk, _dist_hyper_1_8_chunk
|
||||
Remote SQL: SELECT timec, region, temperature, humidity, allnull, highlow, bit_int, good_life FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4])
|
||||
(33 rows)
|
||||
Output: conditions.region, conditions.temperature, min(conditions.allnull), max(conditions.temperature), (sum(conditions.temperature) + sum(conditions.humidity)), avg(conditions.humidity), round(stddev((conditions.humidity)::integer), 5), bit_and(conditions.bit_int), bit_or(conditions.bit_int), bool_and(conditions.good_life), every((conditions.temperature > '0'::double precision)), bool_or(conditions.good_life), first(conditions.highlow, conditions.timec), conditions.timec
|
||||
Group Key: conditions.region, conditions.temperature, conditions.timec
|
||||
-> Merge Append
|
||||
Sort Key: conditions.region, conditions.temperature, conditions.timec
|
||||
-> Partial GroupAggregate
|
||||
Output: conditions.region, conditions.temperature, conditions.timec, PARTIAL min(conditions.allnull), PARTIAL max(conditions.temperature), PARTIAL sum(conditions.temperature), PARTIAL sum(conditions.humidity), PARTIAL avg(conditions.humidity), PARTIAL stddev((conditions.humidity)::integer), PARTIAL bit_and(conditions.bit_int), PARTIAL bit_or(conditions.bit_int), PARTIAL bool_and(conditions.good_life), PARTIAL every((conditions.temperature > '0'::double precision)), PARTIAL bool_or(conditions.good_life), PARTIAL first(conditions.highlow, conditions.timec)
|
||||
Group Key: conditions.region, conditions.temperature, conditions.timec
|
||||
-> Custom Scan (DataNodeScan) on public.conditions
|
||||
Output: conditions.region, conditions.temperature, conditions.timec, conditions.allnull, conditions.humidity, conditions.bit_int, conditions.good_life, conditions.highlow
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_1_chunk, _dist_hyper_1_2_chunk, _dist_hyper_1_3_chunk, _dist_hyper_1_4_chunk
|
||||
Remote SQL: SELECT timec, region, temperature, humidity, allnull, highlow, bit_int, good_life FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) ORDER BY region ASC NULLS LAST, temperature ASC NULLS LAST, timec ASC NULLS LAST
|
||||
-> Partial GroupAggregate
|
||||
Output: conditions_1.region, conditions_1.temperature, conditions_1.timec, PARTIAL min(conditions_1.allnull), PARTIAL max(conditions_1.temperature), PARTIAL sum(conditions_1.temperature), PARTIAL sum(conditions_1.humidity), PARTIAL avg(conditions_1.humidity), PARTIAL stddev((conditions_1.humidity)::integer), PARTIAL bit_and(conditions_1.bit_int), PARTIAL bit_or(conditions_1.bit_int), PARTIAL bool_and(conditions_1.good_life), PARTIAL every((conditions_1.temperature > '0'::double precision)), PARTIAL bool_or(conditions_1.good_life), PARTIAL first(conditions_1.highlow, conditions_1.timec)
|
||||
Group Key: conditions_1.region, conditions_1.temperature, conditions_1.timec
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_1
|
||||
Output: conditions_1.region, conditions_1.temperature, conditions_1.timec, conditions_1.allnull, conditions_1.humidity, conditions_1.bit_int, conditions_1.good_life, conditions_1.highlow
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_9_chunk, _dist_hyper_1_10_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_12_chunk
|
||||
Remote SQL: SELECT timec, region, temperature, humidity, allnull, highlow, bit_int, good_life FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) ORDER BY region ASC NULLS LAST, temperature ASC NULLS LAST, timec ASC NULLS LAST
|
||||
-> Partial GroupAggregate
|
||||
Output: conditions_2.region, conditions_2.temperature, conditions_2.timec, PARTIAL min(conditions_2.allnull), PARTIAL max(conditions_2.temperature), PARTIAL sum(conditions_2.temperature), PARTIAL sum(conditions_2.humidity), PARTIAL avg(conditions_2.humidity), PARTIAL stddev((conditions_2.humidity)::integer), PARTIAL bit_and(conditions_2.bit_int), PARTIAL bit_or(conditions_2.bit_int), PARTIAL bool_and(conditions_2.good_life), PARTIAL every((conditions_2.temperature > '0'::double precision)), PARTIAL bool_or(conditions_2.good_life), PARTIAL first(conditions_2.highlow, conditions_2.timec)
|
||||
Group Key: conditions_2.region, conditions_2.temperature, conditions_2.timec
|
||||
-> Custom Scan (DataNodeScan) on public.conditions conditions_2
|
||||
Output: conditions_2.region, conditions_2.temperature, conditions_2.timec, conditions_2.allnull, conditions_2.humidity, conditions_2.bit_int, conditions_2.good_life, conditions_2.highlow
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_5_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_7_chunk, _dist_hyper_1_8_chunk
|
||||
Remote SQL: SELECT timec, region, temperature, humidity, allnull, highlow, bit_int, good_life FROM public.conditions WHERE _timescaledb_internal.chunks_in(public.conditions.*, ARRAY[1, 2, 3, 4]) ORDER BY region ASC NULLS LAST, temperature ASC NULLS LAST, timec ASC NULLS LAST
|
||||
(29 rows)
|
||||
|
||||
-- Full aggregate pushdown correctness check, compare location grouped query results with partionwise aggregates on and off
|
||||
\set GROUPING 'location'
|
||||
@ -485,10 +457,6 @@ SELECT format('\! diff %s %s', :'RESULTS_CONTROL2', :'RESULTS_TEST2') as "DIFF_C
|
||||
\gset
|
||||
--generate the results into two different files
|
||||
\set ECHO errors
|
||||
-- Note that some difference in output could happen here because
|
||||
-- queries include last(col, time) and first(col, time); there are
|
||||
-- multiple values for "col" that has the same timestamp, so the
|
||||
-- output depends on the order of arriving tuples.
|
||||
:DIFF_CMD2
|
||||
\c :TEST_DBNAME :ROLE_CLUSTER_SUPERUSER
|
||||
DROP DATABASE :DN_DBNAME_1;
|
||||
|
||||
@ -92,9 +92,10 @@ FROM generate_series('2019-01-01'::timestamptz, '2019-01-04'::timestamptz, '1 mi
|
||||
-- the repartitioning boundary.
|
||||
INSERT INTO hyper
|
||||
SELECT * FROM reference
|
||||
WHERE time < '2019-01-02 05:10'::timestamptz;
|
||||
WHERE time < '2019-01-02 05:10'::timestamptz
|
||||
ORDER BY time;
|
||||
SELECT * FROM set_number_partitions('hyper', 2);
|
||||
psql:include/dist_query_load.sql:43: WARNING: insuffient number of partitions for dimension "device"
|
||||
psql:include/dist_query_load.sql:44: WARNING: insuffient number of partitions for dimension "device"
|
||||
set_number_partitions
|
||||
-----------------------
|
||||
|
||||
@ -103,7 +104,8 @@ psql:include/dist_query_load.sql:43: WARNING: insuffient number of partitions f
|
||||
INSERT INTO hyper
|
||||
SELECT * FROM reference
|
||||
WHERE time >= '2019-01-02 05:10'::timestamptz
|
||||
AND time < '2019-01-03 01:22'::timestamptz;
|
||||
AND time < '2019-01-03 01:22'::timestamptz
|
||||
ORDER BY time;
|
||||
SELECT * FROM set_number_partitions('hyper', 5);
|
||||
set_number_partitions
|
||||
-----------------------
|
||||
@ -112,19 +114,20 @@ SELECT * FROM set_number_partitions('hyper', 5);
|
||||
|
||||
INSERT INTO hyper
|
||||
SELECT * FROM reference
|
||||
WHERE time >= '2019-01-03 01:22'::timestamptz;
|
||||
WHERE time >= '2019-01-03 01:22'::timestamptz
|
||||
ORDER BY time;
|
||||
INSERT INTO hyper1d
|
||||
SELECT * FROM reference;
|
||||
SELECT * FROM reference ORDER BY time;
|
||||
SELECT d.hypertable_id, d.id, ds.range_start, ds.range_end
|
||||
FROM _timescaledb_catalog.dimension d, _timescaledb_catalog.dimension_slice ds
|
||||
WHERE num_slices IS NOT NULL
|
||||
AND d.id = ds.dimension_id
|
||||
ORDER BY 1, 2, 3;
|
||||
ORDER BY 1, 2, 3, 4;
|
||||
hypertable_id | id | range_start | range_end
|
||||
---------------+----+----------------------+---------------------
|
||||
1 | 2 | -9223372036854775808 | 1073741823
|
||||
1 | 2 | -9223372036854775808 | 429496729
|
||||
1 | 2 | -9223372036854775808 | 715827882
|
||||
1 | 2 | -9223372036854775808 | 1073741823
|
||||
1 | 2 | 429496729 | 858993458
|
||||
1 | 2 | 715827882 | 1431655764
|
||||
1 | 2 | 858993458 | 1288490187
|
||||
@ -1176,31 +1179,34 @@ WHERE time BETWEEN '2019-01-01' AND '2019-01-01 15:00'
|
||||
GROUP BY 1
|
||||
ORDER BY 1
|
||||
|
||||
QUERY PLAN
|
||||
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
GroupAggregate
|
||||
Output: hyper."time", avg(hyper.temp)
|
||||
Group Key: hyper."time"
|
||||
QUERY PLAN
|
||||
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Finalize GroupAggregate
|
||||
Output: "time", avg(temp)
|
||||
Group Key: "time"
|
||||
-> Custom Scan (AsyncAppend)
|
||||
Output: hyper."time", hyper.temp
|
||||
Output: "time", (PARTIAL avg(temp))
|
||||
-> Merge Append
|
||||
Sort Key: hyper_1."time"
|
||||
-> Custom Scan (DataNodeScan) on public.hyper hyper_1
|
||||
Output: hyper_1."time", hyper_1.temp
|
||||
Sort Key: hyper."time"
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: hyper."time", (PARTIAL avg(hyper.temp))
|
||||
Relations: Aggregate on (public.hyper)
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_1_chunk
|
||||
Remote SQL: SELECT "time", temp FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) ORDER BY "time" ASC NULLS LAST
|
||||
-> Custom Scan (DataNodeScan) on public.hyper hyper_2
|
||||
Output: hyper_2."time", hyper_2.temp
|
||||
Remote SQL: SELECT "time", _timescaledb_internal.partialize_agg(avg(temp)) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) GROUP BY 1 ORDER BY "time" ASC NULLS LAST
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: hyper_1."time", (PARTIAL avg(hyper_1.temp))
|
||||
Relations: Aggregate on (public.hyper)
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_2_chunk
|
||||
Remote SQL: SELECT "time", temp FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) ORDER BY "time" ASC NULLS LAST
|
||||
-> Custom Scan (DataNodeScan) on public.hyper hyper_3
|
||||
Output: hyper_3."time", hyper_3.temp
|
||||
Remote SQL: SELECT "time", _timescaledb_internal.partialize_agg(avg(temp)) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) GROUP BY 1 ORDER BY "time" ASC NULLS LAST
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: hyper_2."time", (PARTIAL avg(hyper_2.temp))
|
||||
Relations: Aggregate on (public.hyper)
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_3_chunk
|
||||
Remote SQL: SELECT "time", temp FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) ORDER BY "time" ASC NULLS LAST
|
||||
(22 rows)
|
||||
Remote SQL: SELECT "time", _timescaledb_internal.partialize_agg(avg(temp)) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) GROUP BY 1 ORDER BY "time" ASC NULLS LAST
|
||||
(25 rows)
|
||||
|
||||
|
||||
######### Grouping on time only (partial aggregation)
|
||||
@ -1212,31 +1218,34 @@ WHERE time BETWEEN '2019-01-01' AND '2019-01-01 15:00'
|
||||
GROUP BY 1
|
||||
ORDER BY 1
|
||||
|
||||
QUERY PLAN
|
||||
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
GroupAggregate
|
||||
Output: (time_bucket('@ 2 days'::interval, hyper."time")), avg(hyper.temp)
|
||||
Group Key: (time_bucket('@ 2 days'::interval, hyper."time"))
|
||||
QUERY PLAN
|
||||
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Finalize GroupAggregate
|
||||
Output: (time_bucket('@ 2 days'::interval, "time")), avg(temp)
|
||||
Group Key: (time_bucket('@ 2 days'::interval, "time"))
|
||||
-> Custom Scan (AsyncAppend)
|
||||
Output: (time_bucket('@ 2 days'::interval, hyper."time")), hyper.temp
|
||||
Output: (time_bucket('@ 2 days'::interval, "time")), (PARTIAL avg(temp))
|
||||
-> Merge Append
|
||||
Sort Key: (time_bucket('@ 2 days'::interval, hyper_1."time"))
|
||||
-> Custom Scan (DataNodeScan) on public.hyper hyper_1
|
||||
Output: time_bucket('@ 2 days'::interval, hyper_1."time"), hyper_1.temp
|
||||
Sort Key: (time_bucket('@ 2 days'::interval, hyper."time"))
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: (time_bucket('@ 2 days'::interval, hyper."time")), (PARTIAL avg(hyper.temp))
|
||||
Relations: Aggregate on (public.hyper)
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_1_chunk
|
||||
Remote SQL: SELECT "time", temp FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) ORDER BY public.time_bucket('2 days'::interval, "time") ASC NULLS LAST
|
||||
-> Custom Scan (DataNodeScan) on public.hyper hyper_2
|
||||
Output: time_bucket('@ 2 days'::interval, hyper_2."time"), hyper_2.temp
|
||||
Remote SQL: SELECT public.time_bucket('@ 2 days'::interval, "time"), _timescaledb_internal.partialize_agg(avg(temp)) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) GROUP BY 1 ORDER BY public.time_bucket('2 days'::interval, "time") ASC NULLS LAST
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: (time_bucket('@ 2 days'::interval, hyper_1."time")), (PARTIAL avg(hyper_1.temp))
|
||||
Relations: Aggregate on (public.hyper)
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_2_chunk
|
||||
Remote SQL: SELECT "time", temp FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) ORDER BY public.time_bucket('2 days'::interval, "time") ASC NULLS LAST
|
||||
-> Custom Scan (DataNodeScan) on public.hyper hyper_3
|
||||
Output: time_bucket('@ 2 days'::interval, hyper_3."time"), hyper_3.temp
|
||||
Remote SQL: SELECT public.time_bucket('@ 2 days'::interval, "time"), _timescaledb_internal.partialize_agg(avg(temp)) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) GROUP BY 1 ORDER BY public.time_bucket('2 days'::interval, "time") ASC NULLS LAST
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: (time_bucket('@ 2 days'::interval, hyper_2."time")), (PARTIAL avg(hyper_2.temp))
|
||||
Relations: Aggregate on (public.hyper)
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_3_chunk
|
||||
Remote SQL: SELECT "time", temp FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) ORDER BY public.time_bucket('2 days'::interval, "time") ASC NULLS LAST
|
||||
(22 rows)
|
||||
Remote SQL: SELECT public.time_bucket('@ 2 days'::interval, "time"), _timescaledb_internal.partialize_agg(avg(temp)) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) GROUP BY 1 ORDER BY public.time_bucket('2 days'::interval, "time") ASC NULLS LAST
|
||||
(25 rows)
|
||||
|
||||
|
||||
######### Grouping on time and device (full aggregation)
|
||||
@ -1363,30 +1372,30 @@ GROUP BY 1,2
|
||||
HAVING device > 4
|
||||
ORDER BY 1,2
|
||||
|
||||
QUERY PLAN
|
||||
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
GroupAggregate
|
||||
Output: (time_bucket('@ 2 days'::interval, hyper."time")), hyper.device, avg(hyper.temp)
|
||||
Group Key: (time_bucket('@ 2 days'::interval, hyper."time")), hyper.device
|
||||
-> Custom Scan (AsyncAppend)
|
||||
Output: (time_bucket('@ 2 days'::interval, hyper."time")), hyper.device, hyper.temp
|
||||
-> Merge Append
|
||||
Sort Key: (time_bucket('@ 2 days'::interval, hyper_1."time")), hyper_1.device
|
||||
-> Custom Scan (DataNodeScan) on public.hyper hyper_1
|
||||
Output: time_bucket('@ 2 days'::interval, hyper_1."time"), hyper_1.device, hyper_1.temp
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_1_chunk
|
||||
Remote SQL: SELECT "time", device, temp FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) AND ((device > 4)) ORDER BY public.time_bucket('2 days'::interval, "time") ASC NULLS LAST, device ASC NULLS LAST
|
||||
-> Custom Scan (DataNodeScan) on public.hyper hyper_2
|
||||
Output: time_bucket('@ 2 days'::interval, hyper_2."time"), hyper_2.device, hyper_2.temp
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_2_chunk
|
||||
Remote SQL: SELECT "time", device, temp FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) AND ((device > 4)) ORDER BY public.time_bucket('2 days'::interval, "time") ASC NULLS LAST, device ASC NULLS LAST
|
||||
-> Custom Scan (DataNodeScan) on public.hyper hyper_3
|
||||
Output: time_bucket('@ 2 days'::interval, hyper_3."time"), hyper_3.device, hyper_3.temp
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_3_chunk
|
||||
Remote SQL: SELECT "time", device, temp FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) AND ((device > 4)) ORDER BY public.time_bucket('2 days'::interval, "time") ASC NULLS LAST, device ASC NULLS LAST
|
||||
QUERY PLAN
|
||||
-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Custom Scan (AsyncAppend)
|
||||
Output: (time_bucket('@ 2 days'::interval, "time")), device, (avg(temp))
|
||||
-> Merge Append
|
||||
Sort Key: (time_bucket('@ 2 days'::interval, hyper."time")), hyper.device
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: (time_bucket('@ 2 days'::interval, hyper."time")), hyper.device, (avg(hyper.temp))
|
||||
Relations: Aggregate on (public.hyper)
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_1_chunk
|
||||
Remote SQL: SELECT public.time_bucket('@ 2 days'::interval, "time"), device, avg(temp) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) AND ((device > 4)) GROUP BY 1, 2 ORDER BY public.time_bucket('2 days'::interval, "time") ASC NULLS LAST, device ASC NULLS LAST
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: (time_bucket('@ 2 days'::interval, hyper_1."time")), hyper_1.device, (avg(hyper_1.temp))
|
||||
Relations: Aggregate on (public.hyper)
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_2_chunk
|
||||
Remote SQL: SELECT public.time_bucket('@ 2 days'::interval, "time"), device, avg(temp) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) AND ((device > 4)) GROUP BY 1, 2 ORDER BY public.time_bucket('2 days'::interval, "time") ASC NULLS LAST, device ASC NULLS LAST
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: (time_bucket('@ 2 days'::interval, hyper_2."time")), hyper_2.device, (avg(hyper_2.temp))
|
||||
Relations: Aggregate on (public.hyper)
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_3_chunk
|
||||
Remote SQL: SELECT public.time_bucket('@ 2 days'::interval, "time"), device, avg(temp) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) AND ((device > 4)) GROUP BY 1, 2 ORDER BY public.time_bucket('2 days'::interval, "time") ASC NULLS LAST, device ASC NULLS LAST
|
||||
(22 rows)
|
||||
|
||||
EXPLAIN (verbose, costs off)
|
||||
@ -1415,16 +1424,13 @@ ORDER BY 1,2
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_2_chunk
|
||||
Remote SQL: SELECT public.time_bucket('@ 2 days'::interval, "time"), device, avg(temp) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) GROUP BY 1, 2 HAVING ((avg(temp) > 40::double precision)) AND ((max(temp) < 70::double precision)) ORDER BY public.time_bucket('2 days'::interval, "time") ASC NULLS LAST, device ASC NULLS LAST
|
||||
-> GroupAggregate
|
||||
Output: (time_bucket('@ 2 days'::interval, hyper_2."time")), hyper_2.device, avg(hyper_2.temp)
|
||||
Group Key: time_bucket('@ 2 days'::interval, hyper_2."time"), hyper_2.device
|
||||
Filter: ((avg(hyper_2.temp) > '40'::double precision) AND (max(hyper_2.temp) < '70'::double precision))
|
||||
-> Custom Scan (DataNodeScan) on public.hyper hyper_2
|
||||
Output: time_bucket('@ 2 days'::interval, hyper_2."time"), hyper_2.device, hyper_2.temp
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_3_chunk
|
||||
Remote SQL: SELECT "time", device, temp FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) ORDER BY public.time_bucket('2 days'::interval, "time") ASC NULLS LAST, device ASC NULLS LAST
|
||||
(25 rows)
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: (time_bucket('@ 2 days'::interval, hyper_2."time")), hyper_2.device, (avg(hyper_2.temp))
|
||||
Relations: Aggregate on (public.hyper)
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_3_chunk
|
||||
Remote SQL: SELECT public.time_bucket('@ 2 days'::interval, "time"), device, avg(temp) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) GROUP BY 1, 2 HAVING ((avg(temp) > 40::double precision)) AND ((max(temp) < 70::double precision)) ORDER BY public.time_bucket('2 days'::interval, "time") ASC NULLS LAST, device ASC NULLS LAST
|
||||
(22 rows)
|
||||
|
||||
|
||||
######### Grouping on device only (full aggregation)
|
||||
@ -1454,15 +1460,13 @@ ORDER BY 1
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_2_chunk
|
||||
Remote SQL: SELECT device, avg(temp) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) GROUP BY 1 ORDER BY device ASC NULLS LAST
|
||||
-> GroupAggregate
|
||||
Output: hyper_2.device, avg(hyper_2.temp)
|
||||
Group Key: hyper_2.device
|
||||
-> Custom Scan (DataNodeScan) on public.hyper hyper_2
|
||||
Output: hyper_2.device, hyper_2.temp
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_3_chunk
|
||||
Remote SQL: SELECT device, temp FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) ORDER BY device ASC NULLS LAST
|
||||
(24 rows)
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: hyper_2.device, (avg(hyper_2.temp))
|
||||
Relations: Aggregate on (public.hyper)
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_3_chunk
|
||||
Remote SQL: SELECT device, avg(temp) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) GROUP BY 1 ORDER BY device ASC NULLS LAST
|
||||
(22 rows)
|
||||
|
||||
|
||||
######### No push down on some functions
|
||||
@ -2271,17 +2275,15 @@ GROUP BY 1,2
|
||||
HAVING device > 4
|
||||
ORDER BY 1,2
|
||||
|
||||
QUERY PLAN
|
||||
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
GroupAggregate
|
||||
Output: (time_bucket('@ 2 days'::interval, hyper."time")), hyper.device, avg(hyper.temp)
|
||||
Group Key: time_bucket('@ 2 days'::interval, hyper."time"), hyper.device
|
||||
-> Custom Scan (DataNodeScan) on public.hyper
|
||||
Output: time_bucket('@ 2 days'::interval, hyper."time"), hyper.device, hyper.temp
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_1_chunk
|
||||
Remote SQL: SELECT "time", device, temp FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) AND ((device > 4)) AND ((device = 1)) ORDER BY public.time_bucket('2 days'::interval, "time") ASC NULLS LAST
|
||||
(8 rows)
|
||||
QUERY PLAN
|
||||
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Custom Scan (DataNodeScan)
|
||||
Output: (time_bucket('@ 2 days'::interval, hyper."time")), hyper.device, (avg(hyper.temp))
|
||||
Relations: Aggregate on (public.hyper)
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_1_chunk
|
||||
Remote SQL: SELECT public.time_bucket('@ 2 days'::interval, "time"), device, avg(temp) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) AND ((device > 4)) AND ((device = 1)) GROUP BY 1, 2 ORDER BY public.time_bucket('2 days'::interval, "time") ASC NULLS LAST
|
||||
(6 rows)
|
||||
|
||||
EXPLAIN (verbose, costs off)
|
||||
SELECT time_bucket('2 days', time) AS time, device, avg(temp)
|
||||
@ -2291,18 +2293,15 @@ GROUP BY 1,2
|
||||
HAVING avg(temp) > 40 AND max(temp) < 70
|
||||
ORDER BY 1,2
|
||||
|
||||
QUERY PLAN
|
||||
-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
GroupAggregate
|
||||
Output: (time_bucket('@ 2 days'::interval, hyper."time")), hyper.device, avg(hyper.temp)
|
||||
Group Key: time_bucket('@ 2 days'::interval, hyper."time"), hyper.device
|
||||
Filter: ((avg(hyper.temp) > '40'::double precision) AND (max(hyper.temp) < '70'::double precision))
|
||||
-> Custom Scan (DataNodeScan) on public.hyper
|
||||
Output: time_bucket('@ 2 days'::interval, hyper."time"), hyper.device, hyper.temp
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_1_chunk
|
||||
Remote SQL: SELECT "time", device, temp FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) AND ((device = 1)) ORDER BY public.time_bucket('2 days'::interval, "time") ASC NULLS LAST
|
||||
(9 rows)
|
||||
QUERY PLAN
|
||||
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Custom Scan (DataNodeScan)
|
||||
Output: (time_bucket('@ 2 days'::interval, hyper."time")), hyper.device, (avg(hyper.temp))
|
||||
Relations: Aggregate on (public.hyper)
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_1_chunk
|
||||
Remote SQL: SELECT public.time_bucket('@ 2 days'::interval, "time"), device, avg(temp) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) AND ((device = 1)) GROUP BY 1, 2 HAVING ((avg(temp) > 40::double precision)) AND ((max(temp) < 70::double precision)) ORDER BY public.time_bucket('2 days'::interval, "time") ASC NULLS LAST
|
||||
(6 rows)
|
||||
|
||||
|
||||
######### Grouping on device only (full aggregation)
|
||||
@ -3126,16 +3125,13 @@ LIMIT 10
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_2_chunk
|
||||
Remote SQL: SELECT public.time_bucket('@ 2 days'::interval, "time"), device, avg(temp) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) GROUP BY 1, 2 HAVING ((avg(temp) > 40::double precision)) AND ((max(temp) < 70::double precision)) ORDER BY public.time_bucket('2 days'::interval, "time") ASC NULLS LAST, device ASC NULLS LAST
|
||||
-> GroupAggregate
|
||||
Output: (time_bucket('@ 2 days'::interval, hyper_2."time")), hyper_2.device, avg(hyper_2.temp)
|
||||
Group Key: time_bucket('@ 2 days'::interval, hyper_2."time"), hyper_2.device
|
||||
Filter: ((avg(hyper_2.temp) > '40'::double precision) AND (max(hyper_2.temp) < '70'::double precision))
|
||||
-> Custom Scan (DataNodeScan) on public.hyper hyper_2
|
||||
Output: time_bucket('@ 2 days'::interval, hyper_2."time"), hyper_2.device, hyper_2.temp
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_3_chunk
|
||||
Remote SQL: SELECT "time", device, temp FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) ORDER BY public.time_bucket('2 days'::interval, "time") ASC NULLS LAST, device ASC NULLS LAST
|
||||
(27 rows)
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: (time_bucket('@ 2 days'::interval, hyper_2."time")), hyper_2.device, (avg(hyper_2.temp))
|
||||
Relations: Aggregate on (public.hyper)
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_3_chunk
|
||||
Remote SQL: SELECT public.time_bucket('@ 2 days'::interval, "time"), device, avg(temp) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) GROUP BY 1, 2 HAVING ((avg(temp) > 40::double precision)) AND ((max(temp) < 70::double precision)) ORDER BY public.time_bucket('2 days'::interval, "time") ASC NULLS LAST, device ASC NULLS LAST
|
||||
(24 rows)
|
||||
|
||||
|
||||
######### Grouping on device only (full aggregation)
|
||||
@ -4115,37 +4111,35 @@ GROUP BY 1,2
|
||||
HAVING avg(temp) > 40 AND max(temp) < 70
|
||||
ORDER BY 1,2
|
||||
|
||||
QUERY PLAN
|
||||
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Sort
|
||||
Output: (time_bucket('@ 2 days'::interval, "time")), device, (avg(temp))
|
||||
Sort Key: (time_bucket('@ 2 days'::interval, "time")), device
|
||||
-> Finalize HashAggregate
|
||||
Output: (time_bucket('@ 2 days'::interval, "time")), device, avg(temp)
|
||||
Group Key: (time_bucket('@ 2 days'::interval, "time")), device
|
||||
Filter: ((avg(temp) > '40'::double precision) AND (max(temp) < '70'::double precision))
|
||||
-> Custom Scan (AsyncAppend)
|
||||
Output: (time_bucket('@ 2 days'::interval, "time")), device, (PARTIAL avg(temp)), (PARTIAL max(temp))
|
||||
-> Append
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: (time_bucket('@ 2 days'::interval, hyper."time")), hyper.device, (PARTIAL avg(hyper.temp)), (PARTIAL max(hyper.temp))
|
||||
Relations: Aggregate on (public.hyper)
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_8_chunk, _dist_hyper_1_12_chunk, _dist_hyper_1_17_chunk, _dist_hyper_1_1_chunk, _dist_hyper_1_15_chunk, _dist_hyper_1_4_chunk, _dist_hyper_1_13_chunk
|
||||
Remote SQL: SELECT public.time_bucket('@ 2 days'::interval, "time"), device, _timescaledb_internal.partialize_agg(avg(temp)), _timescaledb_internal.partialize_agg(max(temp)) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[3, 4, 7, 1, 6, 2, 5]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) GROUP BY 1, 2
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: (time_bucket('@ 2 days'::interval, hyper_1."time")), hyper_1.device, (PARTIAL avg(hyper_1.temp)), (PARTIAL max(hyper_1.temp))
|
||||
Relations: Aggregate on (public.hyper)
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_14_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_18_chunk, _dist_hyper_1_2_chunk, _dist_hyper_1_5_chunk, _dist_hyper_1_9_chunk, _dist_hyper_1_7_chunk
|
||||
Remote SQL: SELECT public.time_bucket('@ 2 days'::interval, "time"), device, _timescaledb_internal.partialize_agg(avg(temp)), _timescaledb_internal.partialize_agg(max(temp)) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[6, 5, 7, 1, 2, 4, 3]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) GROUP BY 1, 2
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: (time_bucket('@ 2 days'::interval, hyper_2."time")), hyper_2.device, (PARTIAL avg(hyper_2.temp)), (PARTIAL max(hyper_2.temp))
|
||||
Relations: Aggregate on (public.hyper)
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_10_chunk, _dist_hyper_1_16_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_3_chunk
|
||||
Remote SQL: SELECT public.time_bucket('@ 2 days'::interval, "time"), device, _timescaledb_internal.partialize_agg(avg(temp)), _timescaledb_internal.partialize_agg(max(temp)) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[3, 4, 2, 1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) GROUP BY 1, 2
|
||||
(28 rows)
|
||||
QUERY PLAN
|
||||
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Finalize GroupAggregate
|
||||
Output: (time_bucket('@ 2 days'::interval, "time")), device, avg(temp)
|
||||
Group Key: (time_bucket('@ 2 days'::interval, "time")), device
|
||||
Filter: ((avg(temp) > '40'::double precision) AND (max(temp) < '70'::double precision))
|
||||
-> Custom Scan (AsyncAppend)
|
||||
Output: (time_bucket('@ 2 days'::interval, "time")), device, (PARTIAL avg(temp)), (PARTIAL max(temp))
|
||||
-> Merge Append
|
||||
Sort Key: (time_bucket('@ 2 days'::interval, hyper."time")), hyper.device
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: (time_bucket('@ 2 days'::interval, hyper."time")), hyper.device, (PARTIAL avg(hyper.temp)), (PARTIAL max(hyper.temp))
|
||||
Relations: Aggregate on (public.hyper)
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_8_chunk, _dist_hyper_1_12_chunk, _dist_hyper_1_17_chunk, _dist_hyper_1_1_chunk, _dist_hyper_1_15_chunk, _dist_hyper_1_4_chunk, _dist_hyper_1_13_chunk
|
||||
Remote SQL: SELECT public.time_bucket('@ 2 days'::interval, "time"), device, _timescaledb_internal.partialize_agg(avg(temp)), _timescaledb_internal.partialize_agg(max(temp)) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[3, 4, 7, 1, 6, 2, 5]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) GROUP BY 1, 2 ORDER BY public.time_bucket('2 days'::interval, "time") ASC NULLS LAST, device ASC NULLS LAST
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: (time_bucket('@ 2 days'::interval, hyper_1."time")), hyper_1.device, (PARTIAL avg(hyper_1.temp)), (PARTIAL max(hyper_1.temp))
|
||||
Relations: Aggregate on (public.hyper)
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_14_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_18_chunk, _dist_hyper_1_2_chunk, _dist_hyper_1_5_chunk, _dist_hyper_1_9_chunk, _dist_hyper_1_7_chunk
|
||||
Remote SQL: SELECT public.time_bucket('@ 2 days'::interval, "time"), device, _timescaledb_internal.partialize_agg(avg(temp)), _timescaledb_internal.partialize_agg(max(temp)) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[6, 5, 7, 1, 2, 4, 3]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) GROUP BY 1, 2 ORDER BY public.time_bucket('2 days'::interval, "time") ASC NULLS LAST, device ASC NULLS LAST
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: (time_bucket('@ 2 days'::interval, hyper_2."time")), hyper_2.device, (PARTIAL avg(hyper_2.temp)), (PARTIAL max(hyper_2.temp))
|
||||
Relations: Aggregate on (public.hyper)
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_10_chunk, _dist_hyper_1_16_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_3_chunk
|
||||
Remote SQL: SELECT public.time_bucket('@ 2 days'::interval, "time"), device, _timescaledb_internal.partialize_agg(avg(temp)), _timescaledb_internal.partialize_agg(max(temp)) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[3, 4, 2, 1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) GROUP BY 1, 2 ORDER BY public.time_bucket('2 days'::interval, "time") ASC NULLS LAST, device ASC NULLS LAST
|
||||
(26 rows)
|
||||
|
||||
|
||||
######### Grouping on device only (full aggregation)
|
||||
@ -4195,33 +4189,43 @@ WHERE time >= '2019-01-01' AND (temp * random() >= 0)
|
||||
GROUP BY 1
|
||||
|
||||
|
||||
QUERY PLAN
|
||||
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
HashAggregate
|
||||
Output: hyper.location, avg(hyper.temp)
|
||||
Group Key: hyper.location
|
||||
QUERY PLAN
|
||||
-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Finalize GroupAggregate
|
||||
Output: location, avg(temp)
|
||||
Group Key: location
|
||||
-> Custom Scan (AsyncAppend)
|
||||
Output: hyper.location, hyper.temp
|
||||
-> Append
|
||||
-> Custom Scan (DataNodeScan) on public.hyper hyper_1
|
||||
Output: hyper_1.location, hyper_1.temp
|
||||
Filter: ((hyper_1.temp * random()) >= '0'::double precision)
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_8_chunk, _dist_hyper_1_12_chunk, _dist_hyper_1_17_chunk, _dist_hyper_1_1_chunk, _dist_hyper_1_15_chunk, _dist_hyper_1_4_chunk, _dist_hyper_1_13_chunk
|
||||
Remote SQL: SELECT location, temp FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[3, 4, 7, 1, 6, 2, 5]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone))
|
||||
-> Custom Scan (DataNodeScan) on public.hyper hyper_2
|
||||
Output: hyper_2.location, hyper_2.temp
|
||||
Filter: ((hyper_2.temp * random()) >= '0'::double precision)
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_14_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_18_chunk, _dist_hyper_1_2_chunk, _dist_hyper_1_5_chunk, _dist_hyper_1_9_chunk, _dist_hyper_1_7_chunk
|
||||
Remote SQL: SELECT location, temp FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[6, 5, 7, 1, 2, 4, 3]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone))
|
||||
-> Custom Scan (DataNodeScan) on public.hyper hyper_3
|
||||
Output: hyper_3.location, hyper_3.temp
|
||||
Filter: ((hyper_3.temp * random()) >= '0'::double precision)
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_10_chunk, _dist_hyper_1_16_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_3_chunk
|
||||
Remote SQL: SELECT location, temp FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[3, 4, 2, 1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) ORDER BY location ASC NULLS LAST
|
||||
(24 rows)
|
||||
Output: location, (PARTIAL avg(temp))
|
||||
-> Merge Append
|
||||
Sort Key: hyper.location
|
||||
-> Partial GroupAggregate
|
||||
Output: hyper.location, PARTIAL avg(hyper.temp)
|
||||
Group Key: hyper.location
|
||||
-> Custom Scan (DataNodeScan) on public.hyper
|
||||
Output: hyper.location, hyper.temp
|
||||
Filter: ((hyper.temp * random()) >= '0'::double precision)
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_8_chunk, _dist_hyper_1_12_chunk, _dist_hyper_1_17_chunk, _dist_hyper_1_1_chunk, _dist_hyper_1_15_chunk, _dist_hyper_1_4_chunk, _dist_hyper_1_13_chunk
|
||||
Remote SQL: SELECT location, temp FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[3, 4, 7, 1, 6, 2, 5]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) ORDER BY location ASC NULLS LAST
|
||||
-> Partial GroupAggregate
|
||||
Output: hyper_1.location, PARTIAL avg(hyper_1.temp)
|
||||
Group Key: hyper_1.location
|
||||
-> Custom Scan (DataNodeScan) on public.hyper hyper_1
|
||||
Output: hyper_1.location, hyper_1.temp
|
||||
Filter: ((hyper_1.temp * random()) >= '0'::double precision)
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_14_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_18_chunk, _dist_hyper_1_2_chunk, _dist_hyper_1_5_chunk, _dist_hyper_1_9_chunk, _dist_hyper_1_7_chunk
|
||||
Remote SQL: SELECT location, temp FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[6, 5, 7, 1, 2, 4, 3]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) ORDER BY location ASC NULLS LAST
|
||||
-> Partial GroupAggregate
|
||||
Output: hyper_2.location, PARTIAL avg(hyper_2.temp)
|
||||
Group Key: hyper_2.location
|
||||
-> Custom Scan (DataNodeScan) on public.hyper hyper_2
|
||||
Output: hyper_2.location, hyper_2.temp
|
||||
Filter: ((hyper_2.temp * random()) >= '0'::double precision)
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_10_chunk, _dist_hyper_1_16_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_3_chunk
|
||||
Remote SQL: SELECT location, temp FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[3, 4, 2, 1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) ORDER BY location ASC NULLS LAST
|
||||
(34 rows)
|
||||
|
||||
|
||||
######### No push down on some functions
|
||||
@ -4770,8 +4774,8 @@ FROM hyper INNER JOIN top_n USING (device)
|
||||
WHERE time >= '2019-01-01'
|
||||
GROUP BY 1,2
|
||||
ORDER BY 1,2
|
||||
QUERY PLAN
|
||||
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
QUERY PLAN
|
||||
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
GroupAggregate
|
||||
Output: (time_bucket('@ 1 min'::interval, hyper."time")), hyper.device, avg(hyper.temp)
|
||||
Group Key: (time_bucket('@ 1 min'::interval, hyper."time")), hyper.device
|
||||
@ -4789,12 +4793,12 @@ ORDER BY 1,2
|
||||
Output: hyper_1."time", hyper_1.device, hyper_1.temp
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_8_chunk, _dist_hyper_1_12_chunk, _dist_hyper_1_17_chunk, _dist_hyper_1_1_chunk, _dist_hyper_1_15_chunk, _dist_hyper_1_4_chunk, _dist_hyper_1_13_chunk
|
||||
Remote SQL: SELECT "time", device, temp FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[3, 4, 7, 1, 6, 2, 5]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone))
|
||||
Remote SQL: SELECT "time", device, temp FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[3, 4, 7, 1, 6, 2, 5]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) ORDER BY public.time_bucket('00:01:00'::interval, "time") ASC NULLS LAST, device ASC NULLS LAST
|
||||
-> Custom Scan (DataNodeScan) on public.hyper hyper_2
|
||||
Output: hyper_2."time", hyper_2.device, hyper_2.temp
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_14_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_18_chunk, _dist_hyper_1_2_chunk, _dist_hyper_1_5_chunk, _dist_hyper_1_9_chunk, _dist_hyper_1_7_chunk
|
||||
Remote SQL: SELECT "time", device, temp FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[6, 5, 7, 1, 2, 4, 3]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone))
|
||||
Remote SQL: SELECT "time", device, temp FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[6, 5, 7, 1, 2, 4, 3]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) ORDER BY public.time_bucket('00:01:00'::interval, "time") ASC NULLS LAST, device ASC NULLS LAST
|
||||
-> Custom Scan (DataNodeScan) on public.hyper hyper_3
|
||||
Output: hyper_3."time", hyper_3.device, hyper_3.temp
|
||||
Data node: data_node_3
|
||||
@ -4809,31 +4813,32 @@ ORDER BY 1,2
|
||||
-> Sort
|
||||
Output: device, (avg(temp))
|
||||
Sort Key: (avg(temp)) DESC
|
||||
-> Finalize HashAggregate
|
||||
-> Finalize GroupAggregate
|
||||
Output: device, avg(temp)
|
||||
Group Key: device
|
||||
-> Custom Scan (AsyncAppend)
|
||||
Output: device, (PARTIAL avg(temp))
|
||||
-> Append
|
||||
-> Merge Append
|
||||
Sort Key: hyper_4.device
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: hyper_4.device, (PARTIAL avg(hyper_4.temp))
|
||||
Relations: Aggregate on (public.hyper)
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_1_8_chunk, _dist_hyper_1_12_chunk, _dist_hyper_1_17_chunk, _dist_hyper_1_1_chunk, _dist_hyper_1_15_chunk, _dist_hyper_1_4_chunk, _dist_hyper_1_13_chunk
|
||||
Remote SQL: SELECT device, _timescaledb_internal.partialize_agg(avg(temp)) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[3, 4, 7, 1, 6, 2, 5]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) GROUP BY 1
|
||||
Remote SQL: SELECT device, _timescaledb_internal.partialize_agg(avg(temp)) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[3, 4, 7, 1, 6, 2, 5]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) GROUP BY 1 ORDER BY device ASC NULLS LAST
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: hyper_5.device, (PARTIAL avg(hyper_5.temp))
|
||||
Relations: Aggregate on (public.hyper)
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_1_14_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_18_chunk, _dist_hyper_1_2_chunk, _dist_hyper_1_5_chunk, _dist_hyper_1_9_chunk, _dist_hyper_1_7_chunk
|
||||
Remote SQL: SELECT device, _timescaledb_internal.partialize_agg(avg(temp)) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[6, 5, 7, 1, 2, 4, 3]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) GROUP BY 1
|
||||
Remote SQL: SELECT device, _timescaledb_internal.partialize_agg(avg(temp)) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[6, 5, 7, 1, 2, 4, 3]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) GROUP BY 1 ORDER BY device ASC NULLS LAST
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: hyper_6.device, (PARTIAL avg(hyper_6.temp))
|
||||
Relations: Aggregate on (public.hyper)
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_1_10_chunk, _dist_hyper_1_16_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_3_chunk
|
||||
Remote SQL: SELECT device, _timescaledb_internal.partialize_agg(avg(temp)) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[3, 4, 2, 1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) GROUP BY 1 ORDER BY device ASC NULLS LAST
|
||||
(61 rows)
|
||||
(62 rows)
|
||||
|
||||
|
||||
######### CTEs/Sub-queries
|
||||
@ -5127,34 +5132,37 @@ GROUP BY 1,2
|
||||
HAVING avg(temp) > 40 AND max(temp) < 70
|
||||
|
||||
|
||||
QUERY PLAN
|
||||
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Finalize HashAggregate
|
||||
QUERY PLAN
|
||||
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Finalize GroupAggregate
|
||||
Output: (time_bucket('@ 2 days'::interval, "time")), device, avg(temp)
|
||||
Group Key: (time_bucket('@ 2 days'::interval, "time")), device
|
||||
Filter: ((avg(temp) > '40'::double precision) AND (max(temp) < '70'::double precision))
|
||||
-> Custom Scan (AsyncAppend)
|
||||
-> Sort
|
||||
Output: (time_bucket('@ 2 days'::interval, "time")), device, (PARTIAL avg(temp)), (PARTIAL max(temp))
|
||||
-> Append
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: (time_bucket('@ 2 days'::interval, hyper1d."time")), hyper1d.device, (PARTIAL avg(hyper1d.temp)), (PARTIAL max(hyper1d.temp))
|
||||
Relations: Aggregate on (public.hyper1d)
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_2_20_chunk
|
||||
Remote SQL: SELECT public.time_bucket('@ 2 days'::interval, "time"), device, _timescaledb_internal.partialize_agg(avg(temp)), _timescaledb_internal.partialize_agg(max(temp)) FROM public.hyper1d WHERE _timescaledb_internal.chunks_in(public.hyper1d.*, ARRAY[8]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) GROUP BY 1, 2
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: (time_bucket('@ 2 days'::interval, hyper1d_1."time")), hyper1d_1.device, (PARTIAL avg(hyper1d_1.temp)), (PARTIAL max(hyper1d_1.temp))
|
||||
Relations: Aggregate on (public.hyper1d)
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_2_21_chunk
|
||||
Remote SQL: SELECT public.time_bucket('@ 2 days'::interval, "time"), device, _timescaledb_internal.partialize_agg(avg(temp)), _timescaledb_internal.partialize_agg(max(temp)) FROM public.hyper1d WHERE _timescaledb_internal.chunks_in(public.hyper1d.*, ARRAY[8]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) GROUP BY 1, 2
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: (time_bucket('@ 2 days'::interval, hyper1d_2."time")), hyper1d_2.device, (PARTIAL avg(hyper1d_2.temp)), (PARTIAL max(hyper1d_2.temp))
|
||||
Relations: Aggregate on (public.hyper1d)
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_2_19_chunk
|
||||
Remote SQL: SELECT public.time_bucket('@ 2 days'::interval, "time"), device, _timescaledb_internal.partialize_agg(avg(temp)), _timescaledb_internal.partialize_agg(max(temp)) FROM public.hyper1d WHERE _timescaledb_internal.chunks_in(public.hyper1d.*, ARRAY[5]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) GROUP BY 1, 2
|
||||
(25 rows)
|
||||
Sort Key: (time_bucket('@ 2 days'::interval, "time")), device
|
||||
-> Custom Scan (AsyncAppend)
|
||||
Output: (time_bucket('@ 2 days'::interval, "time")), device, (PARTIAL avg(temp)), (PARTIAL max(temp))
|
||||
-> Append
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: (time_bucket('@ 2 days'::interval, hyper1d."time")), hyper1d.device, (PARTIAL avg(hyper1d.temp)), (PARTIAL max(hyper1d.temp))
|
||||
Relations: Aggregate on (public.hyper1d)
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_2_20_chunk
|
||||
Remote SQL: SELECT public.time_bucket('@ 2 days'::interval, "time"), device, _timescaledb_internal.partialize_agg(avg(temp)), _timescaledb_internal.partialize_agg(max(temp)) FROM public.hyper1d WHERE _timescaledb_internal.chunks_in(public.hyper1d.*, ARRAY[8]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) GROUP BY 1, 2
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: (time_bucket('@ 2 days'::interval, hyper1d_1."time")), hyper1d_1.device, (PARTIAL avg(hyper1d_1.temp)), (PARTIAL max(hyper1d_1.temp))
|
||||
Relations: Aggregate on (public.hyper1d)
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_2_21_chunk
|
||||
Remote SQL: SELECT public.time_bucket('@ 2 days'::interval, "time"), device, _timescaledb_internal.partialize_agg(avg(temp)), _timescaledb_internal.partialize_agg(max(temp)) FROM public.hyper1d WHERE _timescaledb_internal.chunks_in(public.hyper1d.*, ARRAY[8]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) GROUP BY 1, 2
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: (time_bucket('@ 2 days'::interval, hyper1d_2."time")), hyper1d_2.device, (PARTIAL avg(hyper1d_2.temp)), (PARTIAL max(hyper1d_2.temp))
|
||||
Relations: Aggregate on (public.hyper1d)
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_2_19_chunk
|
||||
Remote SQL: SELECT public.time_bucket('@ 2 days'::interval, "time"), device, _timescaledb_internal.partialize_agg(avg(temp)), _timescaledb_internal.partialize_agg(max(temp)) FROM public.hyper1d WHERE _timescaledb_internal.chunks_in(public.hyper1d.*, ARRAY[5]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) GROUP BY 1, 2
|
||||
(28 rows)
|
||||
|
||||
|
||||
######### Grouping on device only (full aggregation)
|
||||
@ -5796,7 +5804,7 @@ ORDER BY 1,2
|
||||
Output: hyper1d_1."time", hyper1d_1.device, hyper1d_1.temp
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_2_20_chunk
|
||||
Remote SQL: SELECT "time", device, temp FROM public.hyper1d WHERE _timescaledb_internal.chunks_in(public.hyper1d.*, ARRAY[8]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone))
|
||||
Remote SQL: SELECT "time", device, temp FROM public.hyper1d WHERE _timescaledb_internal.chunks_in(public.hyper1d.*, ARRAY[8]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) ORDER BY public.time_bucket('00:01:00'::interval, "time") ASC NULLS LAST, device ASC NULLS LAST
|
||||
-> Custom Scan (DataNodeScan) on public.hyper1d hyper1d_2
|
||||
Output: hyper1d_2."time", hyper1d_2.device, hyper1d_2.temp
|
||||
Data node: data_node_2
|
||||
@ -5827,13 +5835,13 @@ ORDER BY 1,2
|
||||
Relations: Aggregate on (public.hyper1d)
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_2_20_chunk
|
||||
Remote SQL: SELECT device, _timescaledb_internal.partialize_agg(avg(temp)) FROM public.hyper1d WHERE _timescaledb_internal.chunks_in(public.hyper1d.*, ARRAY[8]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) GROUP BY 1
|
||||
Remote SQL: SELECT device, _timescaledb_internal.partialize_agg(avg(temp)) FROM public.hyper1d WHERE _timescaledb_internal.chunks_in(public.hyper1d.*, ARRAY[8]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) GROUP BY 1 ORDER BY device ASC NULLS LAST
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: hyper1d_5.device, (PARTIAL avg(hyper1d_5.temp))
|
||||
Relations: Aggregate on (public.hyper1d)
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_2_21_chunk
|
||||
Remote SQL: SELECT device, _timescaledb_internal.partialize_agg(avg(temp)) FROM public.hyper1d WHERE _timescaledb_internal.chunks_in(public.hyper1d.*, ARRAY[8]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) GROUP BY 1
|
||||
Remote SQL: SELECT device, _timescaledb_internal.partialize_agg(avg(temp)) FROM public.hyper1d WHERE _timescaledb_internal.chunks_in(public.hyper1d.*, ARRAY[8]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) GROUP BY 1 ORDER BY device ASC NULLS LAST
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: hyper1d_6.device, (PARTIAL avg(hyper1d_6.temp))
|
||||
Relations: Aggregate on (public.hyper1d)
|
||||
|
||||
@ -726,8 +726,8 @@ EXPLAIN (verbose, costs off)
|
||||
SELECT DISTINCT device_id, device_id
|
||||
FROM metrics_dist
|
||||
ORDER BY 1;
|
||||
QUERY PLAN
|
||||
-----------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
QUERY PLAN
|
||||
---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Sort
|
||||
Output: metrics_dist.device_id, metrics_dist.device_id
|
||||
Sort Key: metrics_dist.device_id
|
||||
@ -741,17 +741,17 @@ ORDER BY 1;
|
||||
Output: metrics_dist_1.device_id, metrics_dist_1.device_id
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk
|
||||
Remote SQL: SELECT DISTINCT device_id FROM public.metrics_dist WHERE _timescaledb_internal.chunks_in(public.metrics_dist.*, ARRAY[1, 2, 3])
|
||||
Remote SQL: SELECT DISTINCT device_id FROM public.metrics_dist WHERE _timescaledb_internal.chunks_in(public.metrics_dist.*, ARRAY[1, 2, 3]) ORDER BY device_id ASC NULLS LAST
|
||||
-> Custom Scan (DataNodeScan) on public.metrics_dist metrics_dist_2
|
||||
Output: metrics_dist_2.device_id, metrics_dist_2.device_id
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk
|
||||
Remote SQL: SELECT DISTINCT device_id FROM public.metrics_dist WHERE _timescaledb_internal.chunks_in(public.metrics_dist.*, ARRAY[1, 2, 3])
|
||||
Remote SQL: SELECT DISTINCT device_id FROM public.metrics_dist WHERE _timescaledb_internal.chunks_in(public.metrics_dist.*, ARRAY[1, 2, 3]) ORDER BY device_id ASC NULLS LAST
|
||||
-> Custom Scan (DataNodeScan) on public.metrics_dist metrics_dist_3
|
||||
Output: metrics_dist_3.device_id, metrics_dist_3.device_id
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk
|
||||
Remote SQL: SELECT DISTINCT device_id FROM public.metrics_dist WHERE _timescaledb_internal.chunks_in(public.metrics_dist.*, ARRAY[1, 2, 3])
|
||||
Remote SQL: SELECT DISTINCT device_id FROM public.metrics_dist WHERE _timescaledb_internal.chunks_in(public.metrics_dist.*, ARRAY[1, 2, 3]) ORDER BY device_id ASC NULLS LAST
|
||||
(24 rows)
|
||||
|
||||
SELECT DISTINCT handles whole row correctly
|
||||
|
||||
@ -42,7 +42,7 @@ SET enable_partitionwise_aggregate = ON;
|
||||
\set GROUPING 'location'
|
||||
\ir 'include/aggregate_queries.sql'
|
||||
|
||||
\set GROUPING 'region'
|
||||
\set GROUPING 'region, temperature'
|
||||
\ir 'include/aggregate_queries.sql'
|
||||
|
||||
-- Full aggregate pushdown correctness check, compare location grouped query results with partionwise aggregates on and off
|
||||
@ -94,10 +94,6 @@ CALL distributed_exec($$ SET enable_partitionwise_aggregate = ON $$);
|
||||
\o
|
||||
\set ECHO all
|
||||
|
||||
-- Note that some difference in output could happen here because
|
||||
-- queries include last(col, time) and first(col, time); there are
|
||||
-- multiple values for "col" that has the same timestamp, so the
|
||||
-- output depends on the order of arriving tuples.
|
||||
:DIFF_CMD2
|
||||
|
||||
\c :TEST_DBNAME :ROLE_CLUSTER_SUPERUSER
|
||||
|
||||
@ -40,16 +40,16 @@
|
||||
last(temperature, timec) as last_temp,
|
||||
histogram(temperature, 0, 100, 1)
|
||||
FROM :TEST_TABLE
|
||||
GROUP BY :GROUPING
|
||||
ORDER BY :GROUPING;
|
||||
GROUP BY :GROUPING, timec
|
||||
ORDER BY :GROUPING, timec;
|
||||
|
||||
-- Aggregates on custom types are not yet pushed down
|
||||
:PREFIX SELECT :GROUPING,
|
||||
last(highlow, timec) as last_hl,
|
||||
first(highlow, timec) as first_hl
|
||||
FROM :TEST_TABLE
|
||||
GROUP BY :GROUPING
|
||||
ORDER BY :GROUPING;
|
||||
GROUP BY :GROUPING, timec
|
||||
ORDER BY :GROUPING, timec;
|
||||
|
||||
-- Mix of aggregates that push down and those that don't
|
||||
:PREFIX SELECT :GROUPING,
|
||||
@ -65,5 +65,5 @@
|
||||
bool_or(good_life),
|
||||
first(highlow, timec) as first_hl
|
||||
FROM :TEST_TABLE
|
||||
GROUP BY :GROUPING
|
||||
ORDER BY :GROUPING;
|
||||
GROUP BY :GROUPING, timec
|
||||
ORDER BY :GROUPING, timec;
|
||||
|
||||
@ -39,25 +39,28 @@ FROM generate_series('2019-01-01'::timestamptz, '2019-01-04'::timestamptz, '1 mi
|
||||
|
||||
INSERT INTO hyper
|
||||
SELECT * FROM reference
|
||||
WHERE time < '2019-01-02 05:10'::timestamptz;
|
||||
WHERE time < '2019-01-02 05:10'::timestamptz
|
||||
ORDER BY time;
|
||||
SELECT * FROM set_number_partitions('hyper', 2);
|
||||
INSERT INTO hyper
|
||||
SELECT * FROM reference
|
||||
WHERE time >= '2019-01-02 05:10'::timestamptz
|
||||
AND time < '2019-01-03 01:22'::timestamptz;
|
||||
AND time < '2019-01-03 01:22'::timestamptz
|
||||
ORDER BY time;
|
||||
SELECT * FROM set_number_partitions('hyper', 5);
|
||||
INSERT INTO hyper
|
||||
SELECT * FROM reference
|
||||
WHERE time >= '2019-01-03 01:22'::timestamptz;
|
||||
WHERE time >= '2019-01-03 01:22'::timestamptz
|
||||
ORDER BY time;
|
||||
|
||||
INSERT INTO hyper1d
|
||||
SELECT * FROM reference;
|
||||
SELECT * FROM reference ORDER BY time;
|
||||
|
||||
SELECT d.hypertable_id, d.id, ds.range_start, ds.range_end
|
||||
FROM _timescaledb_catalog.dimension d, _timescaledb_catalog.dimension_slice ds
|
||||
WHERE num_slices IS NOT NULL
|
||||
AND d.id = ds.dimension_id
|
||||
ORDER BY 1, 2, 3;
|
||||
ORDER BY 1, 2, 3, 4;
|
||||
|
||||
-- Set the max time we can query without hitting the repartitioned
|
||||
-- chunks. Note that this is before the given repartitioning time
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user