mirror of
https://github.com/timescale/timescaledb.git
synced 2025-05-16 18:43:18 +08:00
Revert "Pushdown of gapfill to data nodes"
This reverts commit eaf3a38fe9553659e515fac72aaad86cf1a06d1e.
This commit is contained in:
Fabrízio de Royes Mello
parent
4083e48a1c
commit
047d6b175b
@ -52,7 +52,6 @@ typedef struct Hypertable
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Oid chunk_sizing_func;
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Hyperspace *space;
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SubspaceStore *chunk_cache;
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bool push_gapfill;
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/*
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* Allows restricting the data nodes to use for the hypertable. Default is to
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* use all available data nodes.
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@ -40,8 +40,6 @@
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#include "data_node_scan_exec.h"
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#include "fdw_utils.h"
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#include "nodes/gapfill/planner.h"
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/*
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* DataNodeScan is a custom scan implementation for scanning hypertables on
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* remote data nodes instead of scanning individual remote chunks.
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@ -375,7 +373,7 @@ force_group_by_push_down(PlannerInfo *root, RelOptInfo *hyper_rel)
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*/
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static void
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push_down_group_bys(PlannerInfo *root, RelOptInfo *hyper_rel, Hyperspace *hs,
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DataNodeChunkAssignments *scas, bool gapfill_safe)
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DataNodeChunkAssignments *scas)
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{
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const Dimension *dim;
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bool overlaps;
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@ -416,9 +414,6 @@ push_down_group_bys(PlannerInfo *root, RelOptInfo *hyper_rel, Hyperspace *hs,
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Assert(NULL != dim);
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hyper_rel->partexprs[0] = ts_dimension_get_partexprs(dim, hyper_rel->relid);
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hyper_rel->part_scheme->partnatts = 1;
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if (gapfill_safe)
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force_group_by_push_down(root, hyper_rel);
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}
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}
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@ -445,7 +440,6 @@ data_node_scan_add_node_paths(PlannerInfo *root, RelOptInfo *hyper_rel)
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int ndata_node_rels;
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DataNodeChunkAssignments scas;
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int i;
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bool gapfill_safe = false;
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Assert(NULL != ht);
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@ -465,11 +459,8 @@ data_node_scan_add_node_paths(PlannerInfo *root, RelOptInfo *hyper_rel)
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/* Assign chunks to data nodes */
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data_node_chunk_assignment_assign_chunks(&scas, chunk_rels, nchunk_rels);
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/* Check if we can push down gapfill to data nodes */
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gapfill_safe = pushdown_gapfill(root, hyper_rel, ht->space, &scas);
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/* Try to push down GROUP BY expressions and bucketing, if possible */
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push_down_group_bys(root, hyper_rel, ht->space, &scas, gapfill_safe);
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push_down_group_bys(root, hyper_rel, ht->space, &scas);
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/*
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* Create estimates and paths for each data node rel based on data node chunk
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@ -496,18 +487,10 @@ data_node_scan_add_node_paths(PlannerInfo *root, RelOptInfo *hyper_rel)
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data_node_rel,
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data_node_rel->serverid,
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hyper_rte->relid,
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TS_FDW_RELINFO_HYPERTABLE_DATA_NODE,
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gapfill_safe);
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TS_FDW_RELINFO_HYPERTABLE_DATA_NODE);
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fpinfo->sca = sca;
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/*
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* Since we can not always call pushdown_gapfill where scas are not available,
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* remember if gapfill is safe to be pushed down for this relation for later
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* uses e.g. in add_foreign_grouping_paths.
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*/
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ht->push_gapfill = gapfill_safe;
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if (!bms_is_empty(sca->chunk_relids))
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{
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add_data_node_scan_paths(root, data_node_rel);
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@ -69,7 +69,6 @@
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#include <utils/typcache.h>
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#include <func_cache.h>
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#include <hypertable_cache.h>
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#include <remote/utils.h>
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#include "relinfo.h"
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@ -106,7 +105,6 @@ typedef struct deparse_expr_cxt
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StringInfo buf; /* output buffer to append to */
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List **params_list; /* exprs that will become remote Params */
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DataNodeChunkAssignment *sca;
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bool has_gapfill;
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} deparse_expr_cxt;
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#define REL_ALIAS_PREFIX "r"
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@ -418,8 +416,10 @@ is_foreign_expr(PlannerInfo *root, RelOptInfo *baserel, Expr *expr)
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if (!foreign_expr_walker((Node *) expr, &glob_cxt))
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return false;
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/* It is safe to pushdown gapfill in limited cases */
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if (gapfill_in_expression(expr) && !fpinfo->pushdown_gapfill)
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/*
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* It is not supported to execute time_bucket_gapfill on data node.
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*/
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if (gapfill_in_expression(expr))
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return false;
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/*
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@ -817,7 +817,6 @@ deparseSelectStmtForRel(StringInfo buf, PlannerInfo *root, RelOptInfo *rel, List
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context.scanrel = IS_UPPER_REL(rel) ? fpinfo->outerrel : rel;
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context.params_list = params_list;
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context.sca = sca;
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context.has_gapfill = false;
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/* Construct SELECT clause */
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deparseSelectSql(tlist, is_subquery, retrieved_attrs, &context, pathkeys);
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@ -2101,8 +2100,6 @@ deparseExpr(Expr *node, deparse_expr_cxt *context)
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deparseSubscriptingRef(castNode(SubscriptingRef, node), context);
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break;
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case T_FuncExpr:
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if (gapfill_in_expression(node))
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context->has_gapfill = true;
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deparseFuncExpr(castNode(FuncExpr, node), context);
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break;
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case T_OpExpr:
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@ -2719,7 +2716,7 @@ deparseAggref(Aggref *node, deparse_expr_cxt *context)
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use_variadic = node->aggvariadic;
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/* Find aggregate name from aggfnoid which is a pg_proc entry */
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if (!context->has_gapfill && partial_agg)
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if (partial_agg)
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appendStringInfoString(buf, INTERNAL_SCHEMA_NAME "." PARTIALIZE_FUNC_NAME "(");
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appendFunctionName(node->aggfnoid, context);
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@ -2795,7 +2792,7 @@ deparseAggref(Aggref *node, deparse_expr_cxt *context)
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deparseExpr((Expr *) node->aggfilter, context);
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}
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appendStringInfoString(buf, !context->has_gapfill && partial_agg ? "))" : ")");
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appendStringInfoString(buf, partial_agg ? "))" : ")");
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}
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/*
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@ -65,12 +65,7 @@ get_foreign_rel_size(PlannerInfo *root, RelOptInfo *baserel, Oid foreigntableid)
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* kind of regular table that will ever have this callback called on it. */
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if (RELKIND_RELATION == rte->relkind)
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{
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fdw_relinfo_create(root,
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baserel,
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InvalidOid,
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foreigntableid,
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TS_FDW_RELINFO_HYPERTABLE,
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false);
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fdw_relinfo_create(root, baserel, InvalidOid, foreigntableid, TS_FDW_RELINFO_HYPERTABLE);
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}
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else
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{
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@ -80,8 +75,7 @@ get_foreign_rel_size(PlannerInfo *root, RelOptInfo *baserel, Oid foreigntableid)
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baserel,
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table->serverid,
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foreigntableid,
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TS_FDW_RELINFO_FOREIGN_TABLE,
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false);
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TS_FDW_RELINFO_FOREIGN_TABLE);
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apply_table_options(table, fdw_relinfo_get(baserel));
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}
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@ -373,7 +373,7 @@ estimate_chunk_size(PlannerInfo *root, RelOptInfo *chunk_rel)
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TsFdwRelInfo *
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fdw_relinfo_create(PlannerInfo *root, RelOptInfo *rel, Oid server_oid, Oid local_table_id,
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TsFdwRelInfoType type, bool gapfill_safe)
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TsFdwRelInfoType type)
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{
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TsFdwRelInfo *fpinfo;
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ListCell *lc;
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@ -406,8 +406,6 @@ fdw_relinfo_create(PlannerInfo *root, RelOptInfo *rel, Oid server_oid, Oid local
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if (*refname && strcmp(refname, get_rel_name(rte->relid)) != 0)
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appendStringInfo(fpinfo->relation_name, " %s", quote_identifier(rte->eref->aliasname));
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fpinfo->pushdown_gapfill = gapfill_safe;
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if (type == TS_FDW_RELINFO_HYPERTABLE)
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{
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/* nothing more to do for hypertables */
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@ -49,7 +49,6 @@ typedef struct TsFdwRelInfo
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* foreign scan.
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*/
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bool pushdown_safe;
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bool pushdown_gapfill;
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/*
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* Restriction clauses, divided into safe and unsafe to pushdown subsets.
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@ -147,8 +146,7 @@ typedef struct TsFdwRelInfo
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} TsFdwRelInfo;
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extern TsFdwRelInfo *fdw_relinfo_create(PlannerInfo *root, RelOptInfo *rel, Oid server_oid,
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Oid local_table_id, TsFdwRelInfoType type,
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bool gapfill_safe);
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Oid local_table_id, TsFdwRelInfoType type);
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extern TsFdwRelInfo *fdw_relinfo_alloc_or_get(RelOptInfo *rel);
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extern TsFdwRelInfo *fdw_relinfo_get(RelOptInfo *rel);
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@ -905,9 +905,6 @@ add_foreign_grouping_paths(PlannerInfo *root, RelOptInfo *input_rel, RelOptInfo
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fpinfo->sca = ifpinfo->sca;
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merge_fdw_options(fpinfo, ifpinfo, NULL);
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if (ifpinfo->pushdown_gapfill)
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fpinfo->pushdown_gapfill = true;
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/*
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* Assess if it is safe to push down aggregation and grouping.
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*
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@ -926,23 +923,6 @@ add_foreign_grouping_paths(PlannerInfo *root, RelOptInfo *input_rel, RelOptInfo
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fpinfo->startup_cost = startup_cost;
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fpinfo->total_cost = total_cost;
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if (ifpinfo->pushdown_gapfill)
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{
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/*
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* If pushdown of gapfill is possible then also check if it would
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* be beneficial to actually push it down. Since, it can create
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* more tuples and they need to be transferred to the data node.
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* However, still pushing of gapfill to the data nodes could make
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* sense because aggregating over it could be then done at the data
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* nodes itself, hence ignore pushing down gapfill to data nodes
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* when it produces a "really" larger amount of tuples.
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*/
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if (10 * ifpinfo->rows > fpinfo->rows)
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{
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fpinfo->pushdown_gapfill = false;
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ifpinfo->pushdown_gapfill = false;
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}
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}
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/* Create and add path to the grouping relation. */
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grouppath = (Path *) create_path(root,
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grouped_rel,
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@ -21,8 +21,6 @@
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#include "nodes/gapfill/gapfill.h"
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#include "nodes/gapfill/planner.h"
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#include "nodes/gapfill/exec.h"
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#include "func_cache.h"
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#include "estimate.h"
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static CustomScanMethods gapfill_plan_methods = {
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.CustomName = "GapFill",
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@ -575,96 +573,3 @@ gapfill_adjust_window_targetlist(PlannerInfo *root, RelOptInfo *input_rel, RelOp
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}
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}
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}
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/*
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* Check if it is safe to push down gapfill to data nodes.
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* Currently, we allow only in the following cases,
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*
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* 1. when only one data node has all the chunks
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* 2. when relation has at least one closed dimension and chunks
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* do not overlap across data nodes.
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* 3. when group by matches space dimension
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* and is not an expression of space dimension.
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*/
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bool
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pushdown_gapfill(PlannerInfo *root, RelOptInfo *hyper_rel, Hyperspace *hs,
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DataNodeChunkAssignments *scas)
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{
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const Dimension *dim;
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ListCell *lc;
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TargetEntry *tle;
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bool space_dim_in_group_by = false;
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Query *parse = root->parse;
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gapfill_walker_context context = { .call.node = NULL, .count = 0 };
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if (CMD_SELECT != parse->commandType || parse->groupClause == NIL)
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return false;
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if (!enable_partitionwise_aggregate)
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return false;
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/*
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* Only check for queries with gapfill call.
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*/
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gapfill_function_walker((Node *) parse->targetList, &context);
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if (context.count == 0)
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return false;
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if (context.count > 1)
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ereport(ERROR,
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(errcode(ERRCODE_FEATURE_NOT_SUPPORTED),
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errmsg("multiple time_bucket_gapfill calls not allowed")));
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Assert(hs->num_dimensions >= 1);
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/* Avoid push down of gapfill when window funcs are present */
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if (parse->hasWindowFuncs)
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return false;
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/*
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* Check for special case when there is only one data node with chunks. This
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* can always be safely pushed down irrespective of partitioning
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*/
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if (scas->num_nodes_with_chunks == 1)
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return true;
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/*
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* Get first closed dimension that we use for assigning chunks to
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* data nodes. If there is no closed dimension, then pushing gapfill
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* to data nodes is not possible.
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*/
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dim = hyperspace_get_closed_dimension(hs, 0);
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if (dim == NULL)
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return false;
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else
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{
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if (parse->groupClause)
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{
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foreach (lc, parse->groupClause)
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{
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/*
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* Check if the group by matches dimension and
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* group by clause has exact dimension and not
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* an expression of that attribute.
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*/
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SortGroupClause *sort = (SortGroupClause *) lfirst(lc);
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tle = get_sortgroupref_tle(sort->tleSortGroupRef, parse->targetList);
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if (tle->resno == dim->column_attno)
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{
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space_dim_in_group_by = true;
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if (IsA(tle->expr, Var))
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break;
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else
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return false;
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}
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}
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}
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if (!space_dim_in_group_by)
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return false;
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}
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return !data_node_chunk_assignments_are_overlapping(scas, dim->fd.id);
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}
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@ -8,28 +8,10 @@
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#include <postgres.h>
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#include "fdw/data_node_scan_plan.h"
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#include <hypertable_cache.h>
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#include <planner/planner.h>
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#include <import/allpaths.h>
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#include <import/planner.h>
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#include <func_cache.h>
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#include <dimension.h>
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#include <compat/compat.h>
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#include <debug_guc.h>
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#include <debug.h>
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#include "fdw/data_node_chunk_assignment.h"
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#include "fdw/scan_plan.h"
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#include "fdw/data_node_scan_plan.h"
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#include "fdw/data_node_scan_exec.h"
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bool gapfill_in_expression(Expr *node);
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void plan_add_gapfill(PlannerInfo *root, RelOptInfo *group_rel);
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void gapfill_adjust_window_targetlist(PlannerInfo *root, RelOptInfo *input_rel,
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RelOptInfo *output_rel);
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bool pushdown_gapfill(PlannerInfo *root, RelOptInfo *hyper_rel, Hyperspace *hs,
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DataNodeChunkAssignments *scas);
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typedef struct GapFillPath
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{
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@ -71,11 +71,7 @@ tsl_create_upper_paths_hook(PlannerInfo *root, UpperRelationKind stage, RelOptIn
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{
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case UPPERREL_GROUP_AGG:
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if (input_reltype != TS_REL_HYPERTABLE_CHILD)
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{
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/* Avoid adding gapfill node to the access node if it is pushed to data node */
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if (!dist_ht || !ht->push_gapfill)
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plan_add_gapfill(root, output_rel);
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}
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plan_add_gapfill(root, output_rel);
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break;
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case UPPERREL_WINDOW:
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if (IsA(linitial(input_rel->pathlist), CustomPath))
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@ -132,9 +132,9 @@ select * from disttable_with_ct;
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-----------------------------------------------------------------------------------------------------------------------------------------------------------
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Custom Scan (DataNodeScan) on public.disttable_with_ct (actual rows=2 loops=1)
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Output: disttable_with_ct."time", disttable_with_ct.txn_id, disttable_with_ct.val, disttable_with_ct.info
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Data node: data_node_1
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Data node: data_node_2
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Fetcher Type: Cursor
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Chunks: _dist_hyper_X_X_chunk
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Remote SQL: SELECT "time", txn_id, val, info FROM public.disttable_with_ct WHERE _timescaledb_internal.chunks_in(public.disttable_with_ct.*, ARRAY[33])
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Remote SQL: SELECT "time", txn_id, val, info FROM public.disttable_with_ct WHERE _timescaledb_internal.chunks_in(public.disttable_with_ct.*, ARRAY[20])
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(6 rows)
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@ -36,8 +36,7 @@ SELECT time_bucket_gapfill('3 hours', time, '2017-01-01 06:00', '2017-01-01 18:0
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first(value, time),
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avg(value)
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FROM :CONDITIONS
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GROUP BY 1,2
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ORDER BY 2,1;
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GROUP BY 1,2;
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time_bucket_gapfill | device | first | avg
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------------------------------+--------+----------+----------
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Sun Jan 01 04:00:00 2017 PST | 1 | 1.2 | 1.2
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@ -87,8 +86,7 @@ SELECT time_bucket_gapfill('3 hours', time, '2017-01-01 06:00', '2017-01-01 18:0
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first(value, time),
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avg(value)
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FROM :CONDITIONS
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GROUP BY 2,1
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ORDER BY 2,1;
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GROUP BY 2,1;
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time_bucket_gapfill | device | first | avg
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------------------------------+--------+----------+----------
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Sun Jan 01 04:00:00 2017 PST | 1 | 1.2 | 1.2
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@ -1,316 +0,0 @@
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-- This file and its contents are licensed under the Timescale License.
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-- Please see the included NOTICE for copyright information and
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-- LICENSE-TIMESCALE for a copy of the license.
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\set ON_ERROR_STOP 0
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SET enable_partitionwise_aggregate = 'on';
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SET timescaledb.enable_remote_explain = true;
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-- Cases where gapfill is pushed down to data-nodes
|
||||
EXPLAIN (VERBOSE, COSTS OFF) SELECT time_bucket_gapfill('3 hours', time, '2017-01-01 06:00', '2017-01-01 18:00'),
|
||||
name,
|
||||
first(value, time),
|
||||
avg(value)
|
||||
FROM test_gapfill
|
||||
GROUP BY 1,2;
|
||||
QUERY PLAN
|
||||
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Custom Scan (AsyncAppend)
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, "time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone)), name, (first(value, "time")), (avg(value))
|
||||
-> Append
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone)), test_gapfill.name, (first(test_gapfill.value, test_gapfill."time")), (avg(test_gapfill.value))
|
||||
Relations: Aggregate on (public.test_gapfill)
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_X_X_chunk
|
||||
Remote SQL: SELECT public.time_bucket_gapfill('@ 3 hours'::interval, "time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone), name, public.first(value, "time"), avg(value) FROM public.test_gapfill WHERE _timescaledb_internal.chunks_in(public.test_gapfill.*, ARRAY[28]) GROUP BY 1, 2
|
||||
Remote EXPLAIN:
|
||||
Custom Scan (GapFill)
|
||||
Output: (public.time_bucket_gapfill('03:00:00'::interval, "time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone)), name, (public.first(value, "time")), (avg(value))
|
||||
-> Sort
|
||||
Output: (public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone)), _dist_hyper_X_X_chunk.name, (public.first(_dist_hyper_X_X_chunk.value, _dist_hyper_X_X_chunk."time")), (avg(_dist_hyper_X_X_chunk.value))
|
||||
Sort Key: _dist_hyper_X_X_chunk.name, (public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone))
|
||||
-> HashAggregate
|
||||
Output: (public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone)), _dist_hyper_X_X_chunk.name, public.first(_dist_hyper_X_X_chunk.value, _dist_hyper_X_X_chunk."time"), avg(_dist_hyper_X_X_chunk.value)
|
||||
Group Key: public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone), _dist_hyper_X_X_chunk.name
|
||||
-> Result
|
||||
Output: public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone), _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value, _dist_hyper_X_X_chunk."time"
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_1."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone)), test_gapfill_1.name, (first(test_gapfill_1.value, test_gapfill_1."time")), (avg(test_gapfill_1.value))
|
||||
Relations: Aggregate on (public.test_gapfill)
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk
|
||||
Remote SQL: SELECT public.time_bucket_gapfill('@ 3 hours'::interval, "time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone), name, public.first(value, "time"), avg(value) FROM public.test_gapfill WHERE _timescaledb_internal.chunks_in(public.test_gapfill.*, ARRAY[23, 24, 25]) GROUP BY 1, 2
|
||||
Remote EXPLAIN:
|
||||
Custom Scan (GapFill)
|
||||
Output: (public.time_bucket_gapfill('03:00:00'::interval, "time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone)), name, (public.first(value, "time")), (avg(value))
|
||||
-> Sort
|
||||
Output: (public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone)), _dist_hyper_X_X_chunk.name, (public.first(_dist_hyper_X_X_chunk.value, _dist_hyper_X_X_chunk."time")), (avg(_dist_hyper_X_X_chunk.value))
|
||||
Sort Key: _dist_hyper_X_X_chunk.name, (public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone))
|
||||
-> HashAggregate
|
||||
Output: (public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone)), _dist_hyper_X_X_chunk.name, public.first(_dist_hyper_X_X_chunk.value, _dist_hyper_X_X_chunk."time"), avg(_dist_hyper_X_X_chunk.value)
|
||||
Group Key: public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone), _dist_hyper_X_X_chunk.name
|
||||
-> Result
|
||||
Output: public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone), _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value, _dist_hyper_X_X_chunk."time"
|
||||
-> Append
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
|
||||
(48 rows)
|
||||
|
||||
EXPLAIN (VERBOSE, COSTS OFF) SELECT time_bucket_gapfill('3 hours', time, '2017-01-01 06:00', '2017-01-01 18:00'),
|
||||
name,
|
||||
first(value, time),
|
||||
avg(value)
|
||||
FROM test_gapfill
|
||||
GROUP BY 2,1;
|
||||
QUERY PLAN
|
||||
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Custom Scan (AsyncAppend)
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, "time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone)), name, (first(value, "time")), (avg(value))
|
||||
-> Append
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone)), test_gapfill.name, (first(test_gapfill.value, test_gapfill."time")), (avg(test_gapfill.value))
|
||||
Relations: Aggregate on (public.test_gapfill)
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_X_X_chunk
|
||||
Remote SQL: SELECT public.time_bucket_gapfill('@ 3 hours'::interval, "time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone), name, public.first(value, "time"), avg(value) FROM public.test_gapfill WHERE _timescaledb_internal.chunks_in(public.test_gapfill.*, ARRAY[28]) GROUP BY 2, 1
|
||||
Remote EXPLAIN:
|
||||
Custom Scan (GapFill)
|
||||
Output: (public.time_bucket_gapfill('03:00:00'::interval, "time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone)), name, (public.first(value, "time")), (avg(value))
|
||||
-> Sort
|
||||
Output: (public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone)), _dist_hyper_X_X_chunk.name, (public.first(_dist_hyper_X_X_chunk.value, _dist_hyper_X_X_chunk."time")), (avg(_dist_hyper_X_X_chunk.value))
|
||||
Sort Key: _dist_hyper_X_X_chunk.name, (public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone))
|
||||
-> HashAggregate
|
||||
Output: (public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone)), _dist_hyper_X_X_chunk.name, public.first(_dist_hyper_X_X_chunk.value, _dist_hyper_X_X_chunk."time"), avg(_dist_hyper_X_X_chunk.value)
|
||||
Group Key: _dist_hyper_X_X_chunk.name, public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone)
|
||||
-> Result
|
||||
Output: public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone), _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value, _dist_hyper_X_X_chunk."time"
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_1."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone)), test_gapfill_1.name, (first(test_gapfill_1.value, test_gapfill_1."time")), (avg(test_gapfill_1.value))
|
||||
Relations: Aggregate on (public.test_gapfill)
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk
|
||||
Remote SQL: SELECT public.time_bucket_gapfill('@ 3 hours'::interval, "time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone), name, public.first(value, "time"), avg(value) FROM public.test_gapfill WHERE _timescaledb_internal.chunks_in(public.test_gapfill.*, ARRAY[23, 24, 25]) GROUP BY 2, 1
|
||||
Remote EXPLAIN:
|
||||
Custom Scan (GapFill)
|
||||
Output: (public.time_bucket_gapfill('03:00:00'::interval, "time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone)), name, (public.first(value, "time")), (avg(value))
|
||||
-> Sort
|
||||
Output: (public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone)), _dist_hyper_X_X_chunk.name, (public.first(_dist_hyper_X_X_chunk.value, _dist_hyper_X_X_chunk."time")), (avg(_dist_hyper_X_X_chunk.value))
|
||||
Sort Key: _dist_hyper_X_X_chunk.name, (public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone))
|
||||
-> HashAggregate
|
||||
Output: (public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone)), _dist_hyper_X_X_chunk.name, public.first(_dist_hyper_X_X_chunk.value, _dist_hyper_X_X_chunk."time"), avg(_dist_hyper_X_X_chunk.value)
|
||||
Group Key: _dist_hyper_X_X_chunk.name, public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone)
|
||||
-> Result
|
||||
Output: public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone), _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value, _dist_hyper_X_X_chunk."time"
|
||||
-> Append
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
|
||||
(48 rows)
|
||||
|
||||
-- Check for multiple gapfill calls
|
||||
SELECT time_bucket_gapfill('3 hours', time, '2017-01-01 06:00', '2017-01-01 18:00'),
|
||||
time_bucket_gapfill('6 hours', time, '2017-01-01 08:00', '2017-01-01 18:00'),
|
||||
name,
|
||||
first(value, time),
|
||||
avg(value)
|
||||
FROM test_gapfill
|
||||
GROUP BY 2,1,3;
|
||||
ERROR: multiple time_bucket_gapfill calls not allowed
|
||||
-- Cases where gapfill is not pushed down to data-nodes
|
||||
-- Space dimension is not in group by clause
|
||||
EXPLAIN (VERBOSE, COSTS OFF) SELECT time_bucket_gapfill('3 hours', time, '2017-01-01 06:00', '2017-01-02 18:00'),
|
||||
first(value, time),
|
||||
avg(value)
|
||||
FROM test_gapfill
|
||||
GROUP BY 1;
|
||||
QUERY PLAN
|
||||
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Custom Scan (GapFill)
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, "time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Mon Jan 02 18:00:00 2017'::timestamp without time zone)), (first(value, "time")), (avg(value))
|
||||
-> Finalize GroupAggregate
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Mon Jan 02 18:00:00 2017'::timestamp without time zone)), first(test_gapfill.value, test_gapfill."time"), avg(test_gapfill.value)
|
||||
Group Key: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Mon Jan 02 18:00:00 2017'::timestamp without time zone))
|
||||
-> Sort
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Mon Jan 02 18:00:00 2017'::timestamp without time zone)), (PARTIAL first(test_gapfill.value, test_gapfill."time")), (PARTIAL avg(test_gapfill.value))
|
||||
Sort Key: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Mon Jan 02 18:00:00 2017'::timestamp without time zone))
|
||||
-> Append
|
||||
-> Partial HashAggregate
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Mon Jan 02 18:00:00 2017'::timestamp without time zone)), PARTIAL first(test_gapfill.value, test_gapfill."time"), PARTIAL avg(test_gapfill.value)
|
||||
Group Key: time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Mon Jan 02 18:00:00 2017'::timestamp without time zone)
|
||||
-> Custom Scan (DataNodeScan) on public.test_gapfill
|
||||
Output: time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Mon Jan 02 18:00:00 2017'::timestamp without time zone), test_gapfill.value, test_gapfill."time"
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_X_X_chunk
|
||||
Remote SQL: SELECT "time", value FROM public.test_gapfill WHERE _timescaledb_internal.chunks_in(public.test_gapfill.*, ARRAY[28])
|
||||
Remote EXPLAIN:
|
||||
Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.value
|
||||
|
||||
-> Partial HashAggregate
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_1."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Mon Jan 02 18:00:00 2017'::timestamp without time zone)), PARTIAL first(test_gapfill_1.value, test_gapfill_1."time"), PARTIAL avg(test_gapfill_1.value)
|
||||
Group Key: time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_1."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Mon Jan 02 18:00:00 2017'::timestamp without time zone)
|
||||
-> Custom Scan (DataNodeScan) on public.test_gapfill test_gapfill_1
|
||||
Output: time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_1."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Mon Jan 02 18:00:00 2017'::timestamp without time zone), test_gapfill_1.value, test_gapfill_1."time"
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk
|
||||
Remote SQL: SELECT "time", value FROM public.test_gapfill WHERE _timescaledb_internal.chunks_in(public.test_gapfill.*, ARRAY[23, 24, 25])
|
||||
Remote EXPLAIN:
|
||||
Append
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.value
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.value
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.value
|
||||
|
||||
(38 rows)
|
||||
|
||||
-- Window functions
|
||||
EXPLAIN (VERBOSE, COSTS OFF) SELECT
|
||||
time_bucket_gapfill('3 hours', time, '2017-01-01 06:00', '2017-01-01 18:00'),
|
||||
lag(min(time)) OVER ()
|
||||
FROM test_gapfill
|
||||
GROUP BY 1;
|
||||
QUERY PLAN
|
||||
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
WindowAgg
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, "time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone)), lag((min("time"))) OVER (?)
|
||||
-> Custom Scan (GapFill)
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, "time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone)), (min("time"))
|
||||
-> Finalize GroupAggregate
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone)), min(test_gapfill."time")
|
||||
Group Key: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone))
|
||||
-> Sort
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone)), (PARTIAL min(test_gapfill."time"))
|
||||
Sort Key: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone))
|
||||
-> Append
|
||||
-> Partial HashAggregate
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone)), PARTIAL min(test_gapfill."time")
|
||||
Group Key: time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone)
|
||||
-> Custom Scan (DataNodeScan) on public.test_gapfill
|
||||
Output: time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone), test_gapfill."time"
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_X_X_chunk
|
||||
Remote SQL: SELECT "time" FROM public.test_gapfill WHERE _timescaledb_internal.chunks_in(public.test_gapfill.*, ARRAY[28])
|
||||
Remote EXPLAIN:
|
||||
Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time"
|
||||
|
||||
-> Partial HashAggregate
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_1."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone)), PARTIAL min(test_gapfill_1."time")
|
||||
Group Key: time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_1."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone)
|
||||
-> Custom Scan (DataNodeScan) on public.test_gapfill test_gapfill_1
|
||||
Output: time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_1."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone), test_gapfill_1."time"
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk
|
||||
Remote SQL: SELECT "time" FROM public.test_gapfill WHERE _timescaledb_internal.chunks_in(public.test_gapfill.*, ARRAY[23, 24, 25])
|
||||
Remote EXPLAIN:
|
||||
Append
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time"
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time"
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time"
|
||||
|
||||
(40 rows)
|
||||
|
||||
-- Data nodes are overlapping
|
||||
EXPLAIN (VERBOSE, COSTS OFF) SELECT time_bucket_gapfill('3 hours', time, '2018-01-01 06:00', '2018-01-01 18:00'),
|
||||
name,
|
||||
first(value, time),
|
||||
avg(value)
|
||||
FROM test_gapfill_overlap
|
||||
GROUP BY 1,2;
|
||||
QUERY PLAN
|
||||
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Custom Scan (GapFill)
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, "time", 'Mon Jan 01 06:00:00 2018'::timestamp without time zone, 'Mon Jan 01 18:00:00 2018'::timestamp without time zone)), name, (first(value, "time")), (avg(value))
|
||||
-> Sort
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_overlap."time", 'Mon Jan 01 06:00:00 2018'::timestamp without time zone, 'Mon Jan 01 18:00:00 2018'::timestamp without time zone)), test_gapfill_overlap.name, (first(test_gapfill_overlap.value, test_gapfill_overlap."time")), (avg(test_gapfill_overlap.value))
|
||||
Sort Key: test_gapfill_overlap.name, (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_overlap."time", 'Mon Jan 01 06:00:00 2018'::timestamp without time zone, 'Mon Jan 01 18:00:00 2018'::timestamp without time zone))
|
||||
-> Finalize GroupAggregate
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_overlap."time", 'Mon Jan 01 06:00:00 2018'::timestamp without time zone, 'Mon Jan 01 18:00:00 2018'::timestamp without time zone)), test_gapfill_overlap.name, first(test_gapfill_overlap.value, test_gapfill_overlap."time"), avg(test_gapfill_overlap.value)
|
||||
Group Key: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_overlap."time", 'Mon Jan 01 06:00:00 2018'::timestamp without time zone, 'Mon Jan 01 18:00:00 2018'::timestamp without time zone)), test_gapfill_overlap.name
|
||||
-> Merge Append
|
||||
Sort Key: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_overlap."time", 'Mon Jan 01 06:00:00 2018'::timestamp without time zone, 'Mon Jan 01 18:00:00 2018'::timestamp without time zone)), test_gapfill_overlap.name
|
||||
-> Partial GroupAggregate
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_overlap."time", 'Mon Jan 01 06:00:00 2018'::timestamp without time zone, 'Mon Jan 01 18:00:00 2018'::timestamp without time zone)), test_gapfill_overlap.name, PARTIAL first(test_gapfill_overlap.value, test_gapfill_overlap."time"), PARTIAL avg(test_gapfill_overlap.value)
|
||||
Group Key: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_overlap."time", 'Mon Jan 01 06:00:00 2018'::timestamp without time zone, 'Mon Jan 01 18:00:00 2018'::timestamp without time zone)), test_gapfill_overlap.name
|
||||
-> Sort
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_overlap."time", 'Mon Jan 01 06:00:00 2018'::timestamp without time zone, 'Mon Jan 01 18:00:00 2018'::timestamp without time zone)), test_gapfill_overlap.name, test_gapfill_overlap.value, test_gapfill_overlap."time"
|
||||
Sort Key: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_overlap."time", 'Mon Jan 01 06:00:00 2018'::timestamp without time zone, 'Mon Jan 01 18:00:00 2018'::timestamp without time zone)), test_gapfill_overlap.name
|
||||
-> Custom Scan (DataNodeScan) on public.test_gapfill_overlap
|
||||
Output: time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_overlap."time", 'Mon Jan 01 06:00:00 2018'::timestamp without time zone, 'Mon Jan 01 18:00:00 2018'::timestamp without time zone), test_gapfill_overlap.name, test_gapfill_overlap.value, test_gapfill_overlap."time"
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk
|
||||
Remote SQL: SELECT "time", name, value FROM public.test_gapfill_overlap WHERE _timescaledb_internal.chunks_in(public.test_gapfill_overlap.*, ARRAY[29, 30, 31, 32])
|
||||
Remote EXPLAIN:
|
||||
Append
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
|
||||
-> Partial GroupAggregate
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_overlap_1."time", 'Mon Jan 01 06:00:00 2018'::timestamp without time zone, 'Mon Jan 01 18:00:00 2018'::timestamp without time zone)), test_gapfill_overlap_1.name, PARTIAL first(test_gapfill_overlap_1.value, test_gapfill_overlap_1."time"), PARTIAL avg(test_gapfill_overlap_1.value)
|
||||
Group Key: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_overlap_1."time", 'Mon Jan 01 06:00:00 2018'::timestamp without time zone, 'Mon Jan 01 18:00:00 2018'::timestamp without time zone)), test_gapfill_overlap_1.name
|
||||
-> Sort
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_overlap_1."time", 'Mon Jan 01 06:00:00 2018'::timestamp without time zone, 'Mon Jan 01 18:00:00 2018'::timestamp without time zone)), test_gapfill_overlap_1.name, test_gapfill_overlap_1.value, test_gapfill_overlap_1."time"
|
||||
Sort Key: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_overlap_1."time", 'Mon Jan 01 06:00:00 2018'::timestamp without time zone, 'Mon Jan 01 18:00:00 2018'::timestamp without time zone)), test_gapfill_overlap_1.name
|
||||
-> Custom Scan (DataNodeScan) on public.test_gapfill_overlap test_gapfill_overlap_1
|
||||
Output: time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_overlap_1."time", 'Mon Jan 01 06:00:00 2018'::timestamp without time zone, 'Mon Jan 01 18:00:00 2018'::timestamp without time zone), test_gapfill_overlap_1.name, test_gapfill_overlap_1.value, test_gapfill_overlap_1."time"
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_X_X_chunk
|
||||
Remote SQL: SELECT "time", name, value FROM public.test_gapfill_overlap WHERE _timescaledb_internal.chunks_in(public.test_gapfill_overlap.*, ARRAY[20])
|
||||
Remote EXPLAIN:
|
||||
Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
|
||||
-> Partial GroupAggregate
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_overlap_2."time", 'Mon Jan 01 06:00:00 2018'::timestamp without time zone, 'Mon Jan 01 18:00:00 2018'::timestamp without time zone)), test_gapfill_overlap_2.name, PARTIAL first(test_gapfill_overlap_2.value, test_gapfill_overlap_2."time"), PARTIAL avg(test_gapfill_overlap_2.value)
|
||||
Group Key: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_overlap_2."time", 'Mon Jan 01 06:00:00 2018'::timestamp without time zone, 'Mon Jan 01 18:00:00 2018'::timestamp without time zone)), test_gapfill_overlap_2.name
|
||||
-> Sort
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_overlap_2."time", 'Mon Jan 01 06:00:00 2018'::timestamp without time zone, 'Mon Jan 01 18:00:00 2018'::timestamp without time zone)), test_gapfill_overlap_2.name, test_gapfill_overlap_2.value, test_gapfill_overlap_2."time"
|
||||
Sort Key: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_overlap_2."time", 'Mon Jan 01 06:00:00 2018'::timestamp without time zone, 'Mon Jan 01 18:00:00 2018'::timestamp without time zone)), test_gapfill_overlap_2.name
|
||||
-> Custom Scan (DataNodeScan) on public.test_gapfill_overlap test_gapfill_overlap_2
|
||||
Output: time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_overlap_2."time", 'Mon Jan 01 06:00:00 2018'::timestamp without time zone, 'Mon Jan 01 18:00:00 2018'::timestamp without time zone), test_gapfill_overlap_2.name, test_gapfill_overlap_2.value, test_gapfill_overlap_2."time"
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk
|
||||
Remote SQL: SELECT "time", name, value FROM public.test_gapfill_overlap WHERE _timescaledb_internal.chunks_in(public.test_gapfill_overlap.*, ARRAY[26, 27, 28, 29, 30])
|
||||
Remote EXPLAIN:
|
||||
Append
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
|
||||
(71 rows)
|
||||
|
||||
SET timescaledb.enable_remote_explain = false;
|
||||
DROP TABLE test_gapfill;
|
||||
DROP TABLE test_gapfill_overlap;
|
||||
@ -1,297 +0,0 @@
|
||||
-- This file and its contents are licensed under the Timescale License.
|
||||
-- Please see the included NOTICE for copyright information and
|
||||
-- LICENSE-TIMESCALE for a copy of the license.
|
||||
\set ON_ERROR_STOP 0
|
||||
SET enable_partitionwise_aggregate = 'on';
|
||||
SET timescaledb.enable_remote_explain = true;
|
||||
-- Cases where gapfill is pushed down to data-nodes
|
||||
EXPLAIN (VERBOSE, COSTS OFF) SELECT time_bucket_gapfill('3 hours', time, '2017-01-01 06:00', '2017-01-01 18:00'),
|
||||
name,
|
||||
first(value, time),
|
||||
avg(value)
|
||||
FROM test_gapfill
|
||||
GROUP BY 1,2;
|
||||
QUERY PLAN
|
||||
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Custom Scan (AsyncAppend)
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, "time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone)), name, (first(value, "time")), (avg(value))
|
||||
-> Append
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone)), test_gapfill.name, (first(test_gapfill.value, test_gapfill."time")), (avg(test_gapfill.value))
|
||||
Relations: Aggregate on (public.test_gapfill)
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_X_X_chunk
|
||||
Remote SQL: SELECT public.time_bucket_gapfill('@ 3 hours'::interval, "time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone), name, public.first(value, "time"), avg(value) FROM public.test_gapfill WHERE _timescaledb_internal.chunks_in(public.test_gapfill.*, ARRAY[28]) GROUP BY 1, 2
|
||||
Remote EXPLAIN:
|
||||
Custom Scan (GapFill)
|
||||
Output: (public.time_bucket_gapfill('03:00:00'::interval, "time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone)), name, (public.first(value, "time")), (avg(value))
|
||||
-> Sort
|
||||
Output: (public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone)), _dist_hyper_X_X_chunk.name, (public.first(_dist_hyper_X_X_chunk.value, _dist_hyper_X_X_chunk."time")), (avg(_dist_hyper_X_X_chunk.value))
|
||||
Sort Key: _dist_hyper_X_X_chunk.name, (public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone))
|
||||
-> HashAggregate
|
||||
Output: (public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone)), _dist_hyper_X_X_chunk.name, public.first(_dist_hyper_X_X_chunk.value, _dist_hyper_X_X_chunk."time"), avg(_dist_hyper_X_X_chunk.value)
|
||||
Group Key: public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone), _dist_hyper_X_X_chunk.name
|
||||
-> Result
|
||||
Output: public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone), _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value, _dist_hyper_X_X_chunk."time"
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_1."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone)), test_gapfill_1.name, (first(test_gapfill_1.value, test_gapfill_1."time")), (avg(test_gapfill_1.value))
|
||||
Relations: Aggregate on (public.test_gapfill)
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk
|
||||
Remote SQL: SELECT public.time_bucket_gapfill('@ 3 hours'::interval, "time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone), name, public.first(value, "time"), avg(value) FROM public.test_gapfill WHERE _timescaledb_internal.chunks_in(public.test_gapfill.*, ARRAY[23, 24, 25]) GROUP BY 1, 2
|
||||
Remote EXPLAIN:
|
||||
Custom Scan (GapFill)
|
||||
Output: (public.time_bucket_gapfill('03:00:00'::interval, test_gapfill."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone)), test_gapfill.name, (public.first(test_gapfill.value, test_gapfill."time")), (avg(test_gapfill.value))
|
||||
-> Sort
|
||||
Output: (public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone)), _dist_hyper_X_X_chunk.name, (public.first(_dist_hyper_X_X_chunk.value, _dist_hyper_X_X_chunk."time")), (avg(_dist_hyper_X_X_chunk.value))
|
||||
Sort Key: _dist_hyper_X_X_chunk.name, (public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone))
|
||||
-> HashAggregate
|
||||
Output: (public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone)), _dist_hyper_X_X_chunk.name, public.first(_dist_hyper_X_X_chunk.value, _dist_hyper_X_X_chunk."time"), avg(_dist_hyper_X_X_chunk.value)
|
||||
Group Key: public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone), _dist_hyper_X_X_chunk.name
|
||||
-> Result
|
||||
Output: public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone), _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value, _dist_hyper_X_X_chunk."time"
|
||||
-> Append
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
|
||||
(48 rows)
|
||||
|
||||
EXPLAIN (VERBOSE, COSTS OFF) SELECT time_bucket_gapfill('3 hours', time, '2017-01-01 06:00', '2017-01-01 18:00'),
|
||||
name,
|
||||
first(value, time),
|
||||
avg(value)
|
||||
FROM test_gapfill
|
||||
GROUP BY 2,1;
|
||||
QUERY PLAN
|
||||
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Custom Scan (AsyncAppend)
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, "time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone)), name, (first(value, "time")), (avg(value))
|
||||
-> Append
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone)), test_gapfill.name, (first(test_gapfill.value, test_gapfill."time")), (avg(test_gapfill.value))
|
||||
Relations: Aggregate on (public.test_gapfill)
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_X_X_chunk
|
||||
Remote SQL: SELECT public.time_bucket_gapfill('@ 3 hours'::interval, "time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone), name, public.first(value, "time"), avg(value) FROM public.test_gapfill WHERE _timescaledb_internal.chunks_in(public.test_gapfill.*, ARRAY[28]) GROUP BY 2, 1
|
||||
Remote EXPLAIN:
|
||||
Custom Scan (GapFill)
|
||||
Output: (public.time_bucket_gapfill('03:00:00'::interval, "time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone)), name, (public.first(value, "time")), (avg(value))
|
||||
-> Sort
|
||||
Output: (public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone)), _dist_hyper_X_X_chunk.name, (public.first(_dist_hyper_X_X_chunk.value, _dist_hyper_X_X_chunk."time")), (avg(_dist_hyper_X_X_chunk.value))
|
||||
Sort Key: _dist_hyper_X_X_chunk.name, (public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone))
|
||||
-> HashAggregate
|
||||
Output: (public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone)), _dist_hyper_X_X_chunk.name, public.first(_dist_hyper_X_X_chunk.value, _dist_hyper_X_X_chunk."time"), avg(_dist_hyper_X_X_chunk.value)
|
||||
Group Key: _dist_hyper_X_X_chunk.name, public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone)
|
||||
-> Result
|
||||
Output: public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone), _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value, _dist_hyper_X_X_chunk."time"
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_1."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone)), test_gapfill_1.name, (first(test_gapfill_1.value, test_gapfill_1."time")), (avg(test_gapfill_1.value))
|
||||
Relations: Aggregate on (public.test_gapfill)
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk
|
||||
Remote SQL: SELECT public.time_bucket_gapfill('@ 3 hours'::interval, "time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone), name, public.first(value, "time"), avg(value) FROM public.test_gapfill WHERE _timescaledb_internal.chunks_in(public.test_gapfill.*, ARRAY[23, 24, 25]) GROUP BY 2, 1
|
||||
Remote EXPLAIN:
|
||||
Custom Scan (GapFill)
|
||||
Output: (public.time_bucket_gapfill('03:00:00'::interval, test_gapfill."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone)), test_gapfill.name, (public.first(test_gapfill.value, test_gapfill."time")), (avg(test_gapfill.value))
|
||||
-> Sort
|
||||
Output: (public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone)), _dist_hyper_X_X_chunk.name, (public.first(_dist_hyper_X_X_chunk.value, _dist_hyper_X_X_chunk."time")), (avg(_dist_hyper_X_X_chunk.value))
|
||||
Sort Key: _dist_hyper_X_X_chunk.name, (public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone))
|
||||
-> HashAggregate
|
||||
Output: (public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone)), _dist_hyper_X_X_chunk.name, public.first(_dist_hyper_X_X_chunk.value, _dist_hyper_X_X_chunk."time"), avg(_dist_hyper_X_X_chunk.value)
|
||||
Group Key: _dist_hyper_X_X_chunk.name, public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone)
|
||||
-> Result
|
||||
Output: public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone), _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value, _dist_hyper_X_X_chunk."time"
|
||||
-> Append
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
|
||||
(48 rows)
|
||||
|
||||
-- Check for multiple gapfill calls
|
||||
SELECT time_bucket_gapfill('3 hours', time, '2017-01-01 06:00', '2017-01-01 18:00'),
|
||||
time_bucket_gapfill('6 hours', time, '2017-01-01 08:00', '2017-01-01 18:00'),
|
||||
name,
|
||||
first(value, time),
|
||||
avg(value)
|
||||
FROM test_gapfill
|
||||
GROUP BY 2,1,3;
|
||||
ERROR: multiple time_bucket_gapfill calls not allowed
|
||||
-- Cases where gapfill is not pushed down to data-nodes
|
||||
-- Space dimension is not in group by clause
|
||||
EXPLAIN (VERBOSE, COSTS OFF) SELECT time_bucket_gapfill('3 hours', time, '2017-01-01 06:00', '2017-01-02 18:00'),
|
||||
first(value, time),
|
||||
avg(value)
|
||||
FROM test_gapfill
|
||||
GROUP BY 1;
|
||||
QUERY PLAN
|
||||
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Custom Scan (GapFill)
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, "time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Mon Jan 02 18:00:00 2017'::timestamp without time zone)), (first(value, "time")), (avg(value))
|
||||
-> Finalize GroupAggregate
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Mon Jan 02 18:00:00 2017'::timestamp without time zone)), first(test_gapfill.value, test_gapfill."time"), avg(test_gapfill.value)
|
||||
Group Key: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Mon Jan 02 18:00:00 2017'::timestamp without time zone))
|
||||
-> Sort
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Mon Jan 02 18:00:00 2017'::timestamp without time zone)), (PARTIAL first(test_gapfill.value, test_gapfill."time")), (PARTIAL avg(test_gapfill.value))
|
||||
Sort Key: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Mon Jan 02 18:00:00 2017'::timestamp without time zone))
|
||||
-> Append
|
||||
-> Partial HashAggregate
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Mon Jan 02 18:00:00 2017'::timestamp without time zone)), PARTIAL first(test_gapfill.value, test_gapfill."time"), PARTIAL avg(test_gapfill.value)
|
||||
Group Key: time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Mon Jan 02 18:00:00 2017'::timestamp without time zone)
|
||||
-> Custom Scan (DataNodeScan) on public.test_gapfill
|
||||
Output: time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Mon Jan 02 18:00:00 2017'::timestamp without time zone), test_gapfill.value, test_gapfill."time"
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_X_X_chunk
|
||||
Remote SQL: SELECT "time", value FROM public.test_gapfill WHERE _timescaledb_internal.chunks_in(public.test_gapfill.*, ARRAY[28])
|
||||
Remote EXPLAIN:
|
||||
Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.value
|
||||
|
||||
-> Partial HashAggregate
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_1."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Mon Jan 02 18:00:00 2017'::timestamp without time zone)), PARTIAL first(test_gapfill_1.value, test_gapfill_1."time"), PARTIAL avg(test_gapfill_1.value)
|
||||
Group Key: time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_1."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Mon Jan 02 18:00:00 2017'::timestamp without time zone)
|
||||
-> Custom Scan (DataNodeScan) on public.test_gapfill test_gapfill_1
|
||||
Output: time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_1."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Mon Jan 02 18:00:00 2017'::timestamp without time zone), test_gapfill_1.value, test_gapfill_1."time"
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk
|
||||
Remote SQL: SELECT "time", value FROM public.test_gapfill WHERE _timescaledb_internal.chunks_in(public.test_gapfill.*, ARRAY[23, 24, 25])
|
||||
Remote EXPLAIN:
|
||||
Append
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.value
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.value
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.value
|
||||
|
||||
(38 rows)
|
||||
|
||||
-- Window functions
|
||||
EXPLAIN (VERBOSE, COSTS OFF) SELECT
|
||||
time_bucket_gapfill('3 hours', time, '2017-01-01 06:00', '2017-01-01 18:00'),
|
||||
lag(min(time)) OVER ()
|
||||
FROM test_gapfill
|
||||
GROUP BY 1;
|
||||
QUERY PLAN
|
||||
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
WindowAgg
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, "time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone)), lag((min("time"))) OVER (?)
|
||||
-> Custom Scan (GapFill)
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, "time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone)), (min("time"))
|
||||
-> Finalize GroupAggregate
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone)), min(test_gapfill."time")
|
||||
Group Key: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone))
|
||||
-> Sort
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone)), (PARTIAL min(test_gapfill."time"))
|
||||
Sort Key: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone))
|
||||
-> Append
|
||||
-> Partial HashAggregate
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone)), PARTIAL min(test_gapfill."time")
|
||||
Group Key: time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone)
|
||||
-> Custom Scan (DataNodeScan) on public.test_gapfill
|
||||
Output: time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone), test_gapfill."time"
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_X_X_chunk
|
||||
Remote SQL: SELECT "time" FROM public.test_gapfill WHERE _timescaledb_internal.chunks_in(public.test_gapfill.*, ARRAY[28])
|
||||
Remote EXPLAIN:
|
||||
Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time"
|
||||
|
||||
-> Partial HashAggregate
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_1."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone)), PARTIAL min(test_gapfill_1."time")
|
||||
Group Key: time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_1."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone)
|
||||
-> Custom Scan (DataNodeScan) on public.test_gapfill test_gapfill_1
|
||||
Output: time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_1."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone), test_gapfill_1."time"
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk
|
||||
Remote SQL: SELECT "time" FROM public.test_gapfill WHERE _timescaledb_internal.chunks_in(public.test_gapfill.*, ARRAY[23, 24, 25])
|
||||
Remote EXPLAIN:
|
||||
Append
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time"
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time"
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time"
|
||||
|
||||
(40 rows)
|
||||
|
||||
-- Data nodes are overlapping
|
||||
EXPLAIN (VERBOSE, COSTS OFF) SELECT time_bucket_gapfill('3 hours', time, '2018-01-01 06:00', '2018-01-01 18:00'),
|
||||
name,
|
||||
first(value, time),
|
||||
avg(value)
|
||||
FROM test_gapfill_overlap
|
||||
GROUP BY 1,2;
|
||||
QUERY PLAN
|
||||
---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Custom Scan (GapFill)
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_overlap."time", 'Mon Jan 01 06:00:00 2018'::timestamp without time zone, 'Mon Jan 01 18:00:00 2018'::timestamp without time zone)), test_gapfill_overlap.name, (first(test_gapfill_overlap.value, test_gapfill_overlap."time")), (avg(test_gapfill_overlap.value))
|
||||
-> Sort
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_overlap_1."time", 'Mon Jan 01 06:00:00 2018'::timestamp without time zone, 'Mon Jan 01 18:00:00 2018'::timestamp without time zone)), test_gapfill_overlap_1.name, (first(test_gapfill_overlap_1.value, test_gapfill_overlap_1."time")), (avg(test_gapfill_overlap_1.value))
|
||||
Sort Key: test_gapfill_overlap_1.name, (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_overlap_1."time", 'Mon Jan 01 06:00:00 2018'::timestamp without time zone, 'Mon Jan 01 18:00:00 2018'::timestamp without time zone))
|
||||
-> HashAggregate
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_overlap_1."time", 'Mon Jan 01 06:00:00 2018'::timestamp without time zone, 'Mon Jan 01 18:00:00 2018'::timestamp without time zone)), test_gapfill_overlap_1.name, first(test_gapfill_overlap_1.value, test_gapfill_overlap_1."time"), avg(test_gapfill_overlap_1.value)
|
||||
Group Key: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_overlap_1."time", 'Mon Jan 01 06:00:00 2018'::timestamp without time zone, 'Mon Jan 01 18:00:00 2018'::timestamp without time zone)), test_gapfill_overlap_1.name
|
||||
-> Append
|
||||
-> Custom Scan (DataNodeScan) on public.test_gapfill_overlap test_gapfill_overlap_1
|
||||
Output: time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_overlap_1."time", 'Mon Jan 01 06:00:00 2018'::timestamp without time zone, 'Mon Jan 01 18:00:00 2018'::timestamp without time zone), test_gapfill_overlap_1.name, test_gapfill_overlap_1.value, test_gapfill_overlap_1."time"
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk
|
||||
Remote SQL: SELECT "time", name, value FROM public.test_gapfill_overlap WHERE _timescaledb_internal.chunks_in(public.test_gapfill_overlap.*, ARRAY[29, 30, 31, 32])
|
||||
Remote EXPLAIN:
|
||||
Append
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
|
||||
-> Custom Scan (DataNodeScan) on public.test_gapfill_overlap test_gapfill_overlap_2
|
||||
Output: time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_overlap_2."time", 'Mon Jan 01 06:00:00 2018'::timestamp without time zone, 'Mon Jan 01 18:00:00 2018'::timestamp without time zone), test_gapfill_overlap_2.name, test_gapfill_overlap_2.value, test_gapfill_overlap_2."time"
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_X_X_chunk
|
||||
Remote SQL: SELECT "time", name, value FROM public.test_gapfill_overlap WHERE _timescaledb_internal.chunks_in(public.test_gapfill_overlap.*, ARRAY[20])
|
||||
Remote EXPLAIN:
|
||||
Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
|
||||
-> Custom Scan (DataNodeScan) on public.test_gapfill_overlap test_gapfill_overlap_3
|
||||
Output: time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_overlap_3."time", 'Mon Jan 01 06:00:00 2018'::timestamp without time zone, 'Mon Jan 01 18:00:00 2018'::timestamp without time zone), test_gapfill_overlap_3.name, test_gapfill_overlap_3.value, test_gapfill_overlap_3."time"
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk
|
||||
Remote SQL: SELECT "time", name, value FROM public.test_gapfill_overlap WHERE _timescaledb_internal.chunks_in(public.test_gapfill_overlap.*, ARRAY[26, 27, 28, 29, 30])
|
||||
Remote EXPLAIN:
|
||||
Append
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
|
||||
(52 rows)
|
||||
|
||||
SET timescaledb.enable_remote_explain = false;
|
||||
DROP TABLE test_gapfill;
|
||||
DROP TABLE test_gapfill_overlap;
|
||||
@ -1,297 +0,0 @@
|
||||
-- This file and its contents are licensed under the Timescale License.
|
||||
-- Please see the included NOTICE for copyright information and
|
||||
-- LICENSE-TIMESCALE for a copy of the license.
|
||||
\set ON_ERROR_STOP 0
|
||||
SET enable_partitionwise_aggregate = 'on';
|
||||
SET timescaledb.enable_remote_explain = true;
|
||||
-- Cases where gapfill is pushed down to data-nodes
|
||||
EXPLAIN (VERBOSE, COSTS OFF) SELECT time_bucket_gapfill('3 hours', time, '2017-01-01 06:00', '2017-01-01 18:00'),
|
||||
name,
|
||||
first(value, time),
|
||||
avg(value)
|
||||
FROM test_gapfill
|
||||
GROUP BY 1,2;
|
||||
QUERY PLAN
|
||||
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Custom Scan (AsyncAppend)
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, "time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone)), name, (first(value, "time")), (avg(value))
|
||||
-> Append
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone)), test_gapfill.name, (first(test_gapfill.value, test_gapfill."time")), (avg(test_gapfill.value))
|
||||
Relations: Aggregate on (public.test_gapfill)
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_X_X_chunk
|
||||
Remote SQL: SELECT public.time_bucket_gapfill('@ 3 hours'::interval, "time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone), name, public.first(value, "time"), avg(value) FROM public.test_gapfill WHERE _timescaledb_internal.chunks_in(public.test_gapfill.*, ARRAY[28]) GROUP BY 1, 2
|
||||
Remote EXPLAIN:
|
||||
Custom Scan (GapFill)
|
||||
Output: (public.time_bucket_gapfill('03:00:00'::interval, "time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone)), name, (public.first(value, "time")), (avg(value))
|
||||
-> Sort
|
||||
Output: (public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone)), _dist_hyper_X_X_chunk.name, (public.first(_dist_hyper_X_X_chunk.value, _dist_hyper_X_X_chunk."time")), (avg(_dist_hyper_X_X_chunk.value))
|
||||
Sort Key: _dist_hyper_X_X_chunk.name, (public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone))
|
||||
-> HashAggregate
|
||||
Output: (public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone)), _dist_hyper_X_X_chunk.name, public.first(_dist_hyper_X_X_chunk.value, _dist_hyper_X_X_chunk."time"), avg(_dist_hyper_X_X_chunk.value)
|
||||
Group Key: public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone), _dist_hyper_X_X_chunk.name
|
||||
-> Result
|
||||
Output: public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone), _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value, _dist_hyper_X_X_chunk."time"
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_1."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone)), test_gapfill_1.name, (first(test_gapfill_1.value, test_gapfill_1."time")), (avg(test_gapfill_1.value))
|
||||
Relations: Aggregate on (public.test_gapfill)
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk
|
||||
Remote SQL: SELECT public.time_bucket_gapfill('@ 3 hours'::interval, "time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone), name, public.first(value, "time"), avg(value) FROM public.test_gapfill WHERE _timescaledb_internal.chunks_in(public.test_gapfill.*, ARRAY[23, 24, 25]) GROUP BY 1, 2
|
||||
Remote EXPLAIN:
|
||||
Custom Scan (GapFill)
|
||||
Output: (public.time_bucket_gapfill('03:00:00'::interval, test_gapfill."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone)), test_gapfill.name, (public.first(test_gapfill.value, test_gapfill."time")), (avg(test_gapfill.value))
|
||||
-> Sort
|
||||
Output: (public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone)), _dist_hyper_X_X_chunk.name, (public.first(_dist_hyper_X_X_chunk.value, _dist_hyper_X_X_chunk."time")), (avg(_dist_hyper_X_X_chunk.value))
|
||||
Sort Key: _dist_hyper_X_X_chunk.name, (public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone))
|
||||
-> HashAggregate
|
||||
Output: (public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone)), _dist_hyper_X_X_chunk.name, public.first(_dist_hyper_X_X_chunk.value, _dist_hyper_X_X_chunk."time"), avg(_dist_hyper_X_X_chunk.value)
|
||||
Group Key: public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone), _dist_hyper_X_X_chunk.name
|
||||
-> Result
|
||||
Output: public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone), _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value, _dist_hyper_X_X_chunk."time"
|
||||
-> Append
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
|
||||
(48 rows)
|
||||
|
||||
EXPLAIN (VERBOSE, COSTS OFF) SELECT time_bucket_gapfill('3 hours', time, '2017-01-01 06:00', '2017-01-01 18:00'),
|
||||
name,
|
||||
first(value, time),
|
||||
avg(value)
|
||||
FROM test_gapfill
|
||||
GROUP BY 2,1;
|
||||
QUERY PLAN
|
||||
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Custom Scan (AsyncAppend)
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, "time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone)), name, (first(value, "time")), (avg(value))
|
||||
-> Append
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone)), test_gapfill.name, (first(test_gapfill.value, test_gapfill."time")), (avg(test_gapfill.value))
|
||||
Relations: Aggregate on (public.test_gapfill)
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_X_X_chunk
|
||||
Remote SQL: SELECT public.time_bucket_gapfill('@ 3 hours'::interval, "time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone), name, public.first(value, "time"), avg(value) FROM public.test_gapfill WHERE _timescaledb_internal.chunks_in(public.test_gapfill.*, ARRAY[28]) GROUP BY 2, 1
|
||||
Remote EXPLAIN:
|
||||
Custom Scan (GapFill)
|
||||
Output: (public.time_bucket_gapfill('03:00:00'::interval, "time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone)), name, (public.first(value, "time")), (avg(value))
|
||||
-> Sort
|
||||
Output: (public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone)), _dist_hyper_X_X_chunk.name, (public.first(_dist_hyper_X_X_chunk.value, _dist_hyper_X_X_chunk."time")), (avg(_dist_hyper_X_X_chunk.value))
|
||||
Sort Key: _dist_hyper_X_X_chunk.name, (public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone))
|
||||
-> HashAggregate
|
||||
Output: (public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone)), _dist_hyper_X_X_chunk.name, public.first(_dist_hyper_X_X_chunk.value, _dist_hyper_X_X_chunk."time"), avg(_dist_hyper_X_X_chunk.value)
|
||||
Group Key: _dist_hyper_X_X_chunk.name, public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone)
|
||||
-> Result
|
||||
Output: public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone), _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value, _dist_hyper_X_X_chunk."time"
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
|
||||
-> Custom Scan (DataNodeScan)
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_1."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone)), test_gapfill_1.name, (first(test_gapfill_1.value, test_gapfill_1."time")), (avg(test_gapfill_1.value))
|
||||
Relations: Aggregate on (public.test_gapfill)
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk
|
||||
Remote SQL: SELECT public.time_bucket_gapfill('@ 3 hours'::interval, "time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone), name, public.first(value, "time"), avg(value) FROM public.test_gapfill WHERE _timescaledb_internal.chunks_in(public.test_gapfill.*, ARRAY[23, 24, 25]) GROUP BY 2, 1
|
||||
Remote EXPLAIN:
|
||||
Custom Scan (GapFill)
|
||||
Output: (public.time_bucket_gapfill('03:00:00'::interval, test_gapfill."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone)), test_gapfill.name, (public.first(test_gapfill.value, test_gapfill."time")), (avg(test_gapfill.value))
|
||||
-> Sort
|
||||
Output: (public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone)), _dist_hyper_X_X_chunk.name, (public.first(_dist_hyper_X_X_chunk.value, _dist_hyper_X_X_chunk."time")), (avg(_dist_hyper_X_X_chunk.value))
|
||||
Sort Key: _dist_hyper_X_X_chunk.name, (public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone))
|
||||
-> HashAggregate
|
||||
Output: (public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone)), _dist_hyper_X_X_chunk.name, public.first(_dist_hyper_X_X_chunk.value, _dist_hyper_X_X_chunk."time"), avg(_dist_hyper_X_X_chunk.value)
|
||||
Group Key: _dist_hyper_X_X_chunk.name, public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone)
|
||||
-> Result
|
||||
Output: public.time_bucket_gapfill('03:00:00'::interval, _dist_hyper_X_X_chunk."time", '2017-01-01 06:00:00'::timestamp without time zone, '2017-01-01 18:00:00'::timestamp without time zone), _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value, _dist_hyper_X_X_chunk."time"
|
||||
-> Append
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
|
||||
(48 rows)
|
||||
|
||||
-- Check for multiple gapfill calls
|
||||
SELECT time_bucket_gapfill('3 hours', time, '2017-01-01 06:00', '2017-01-01 18:00'),
|
||||
time_bucket_gapfill('6 hours', time, '2017-01-01 08:00', '2017-01-01 18:00'),
|
||||
name,
|
||||
first(value, time),
|
||||
avg(value)
|
||||
FROM test_gapfill
|
||||
GROUP BY 2,1,3;
|
||||
ERROR: multiple time_bucket_gapfill calls not allowed
|
||||
-- Cases where gapfill is not pushed down to data-nodes
|
||||
-- Space dimension is not in group by clause
|
||||
EXPLAIN (VERBOSE, COSTS OFF) SELECT time_bucket_gapfill('3 hours', time, '2017-01-01 06:00', '2017-01-02 18:00'),
|
||||
first(value, time),
|
||||
avg(value)
|
||||
FROM test_gapfill
|
||||
GROUP BY 1;
|
||||
QUERY PLAN
|
||||
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Custom Scan (GapFill)
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, "time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Mon Jan 02 18:00:00 2017'::timestamp without time zone)), (first(value, "time")), (avg(value))
|
||||
-> Finalize GroupAggregate
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Mon Jan 02 18:00:00 2017'::timestamp without time zone)), first(test_gapfill.value, test_gapfill."time"), avg(test_gapfill.value)
|
||||
Group Key: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Mon Jan 02 18:00:00 2017'::timestamp without time zone))
|
||||
-> Sort
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Mon Jan 02 18:00:00 2017'::timestamp without time zone)), (PARTIAL first(test_gapfill.value, test_gapfill."time")), (PARTIAL avg(test_gapfill.value))
|
||||
Sort Key: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Mon Jan 02 18:00:00 2017'::timestamp without time zone))
|
||||
-> Append
|
||||
-> Partial HashAggregate
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Mon Jan 02 18:00:00 2017'::timestamp without time zone)), PARTIAL first(test_gapfill.value, test_gapfill."time"), PARTIAL avg(test_gapfill.value)
|
||||
Group Key: time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Mon Jan 02 18:00:00 2017'::timestamp without time zone)
|
||||
-> Custom Scan (DataNodeScan) on public.test_gapfill
|
||||
Output: time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Mon Jan 02 18:00:00 2017'::timestamp without time zone), test_gapfill.value, test_gapfill."time"
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_X_X_chunk
|
||||
Remote SQL: SELECT "time", value FROM public.test_gapfill WHERE _timescaledb_internal.chunks_in(public.test_gapfill.*, ARRAY[28])
|
||||
Remote EXPLAIN:
|
||||
Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.value
|
||||
|
||||
-> Partial HashAggregate
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_1."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Mon Jan 02 18:00:00 2017'::timestamp without time zone)), PARTIAL first(test_gapfill_1.value, test_gapfill_1."time"), PARTIAL avg(test_gapfill_1.value)
|
||||
Group Key: time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_1."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Mon Jan 02 18:00:00 2017'::timestamp without time zone)
|
||||
-> Custom Scan (DataNodeScan) on public.test_gapfill test_gapfill_1
|
||||
Output: time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_1."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Mon Jan 02 18:00:00 2017'::timestamp without time zone), test_gapfill_1.value, test_gapfill_1."time"
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk
|
||||
Remote SQL: SELECT "time", value FROM public.test_gapfill WHERE _timescaledb_internal.chunks_in(public.test_gapfill.*, ARRAY[23, 24, 25])
|
||||
Remote EXPLAIN:
|
||||
Append
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.value
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.value
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.value
|
||||
|
||||
(38 rows)
|
||||
|
||||
-- Window functions
|
||||
EXPLAIN (VERBOSE, COSTS OFF) SELECT
|
||||
time_bucket_gapfill('3 hours', time, '2017-01-01 06:00', '2017-01-01 18:00'),
|
||||
lag(min(time)) OVER ()
|
||||
FROM test_gapfill
|
||||
GROUP BY 1;
|
||||
QUERY PLAN
|
||||
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
WindowAgg
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, "time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone)), lag((min("time"))) OVER (?)
|
||||
-> Custom Scan (GapFill)
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, "time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone)), (min("time"))
|
||||
-> Finalize GroupAggregate
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone)), min(test_gapfill."time")
|
||||
Group Key: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone))
|
||||
-> Sort
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone)), (PARTIAL min(test_gapfill."time"))
|
||||
Sort Key: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone))
|
||||
-> Append
|
||||
-> Partial HashAggregate
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone)), PARTIAL min(test_gapfill."time")
|
||||
Group Key: time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone)
|
||||
-> Custom Scan (DataNodeScan) on public.test_gapfill
|
||||
Output: time_bucket_gapfill('@ 3 hours'::interval, test_gapfill."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone), test_gapfill."time"
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_X_X_chunk
|
||||
Remote SQL: SELECT "time" FROM public.test_gapfill WHERE _timescaledb_internal.chunks_in(public.test_gapfill.*, ARRAY[28])
|
||||
Remote EXPLAIN:
|
||||
Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time"
|
||||
|
||||
-> Partial HashAggregate
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_1."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone)), PARTIAL min(test_gapfill_1."time")
|
||||
Group Key: time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_1."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone)
|
||||
-> Custom Scan (DataNodeScan) on public.test_gapfill test_gapfill_1
|
||||
Output: time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_1."time", 'Sun Jan 01 06:00:00 2017'::timestamp without time zone, 'Sun Jan 01 18:00:00 2017'::timestamp without time zone), test_gapfill_1."time"
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk
|
||||
Remote SQL: SELECT "time" FROM public.test_gapfill WHERE _timescaledb_internal.chunks_in(public.test_gapfill.*, ARRAY[23, 24, 25])
|
||||
Remote EXPLAIN:
|
||||
Append
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time"
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time"
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time"
|
||||
|
||||
(40 rows)
|
||||
|
||||
-- Data nodes are overlapping
|
||||
EXPLAIN (VERBOSE, COSTS OFF) SELECT time_bucket_gapfill('3 hours', time, '2018-01-01 06:00', '2018-01-01 18:00'),
|
||||
name,
|
||||
first(value, time),
|
||||
avg(value)
|
||||
FROM test_gapfill_overlap
|
||||
GROUP BY 1,2;
|
||||
QUERY PLAN
|
||||
---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
Custom Scan (GapFill)
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_overlap."time", 'Mon Jan 01 06:00:00 2018'::timestamp without time zone, 'Mon Jan 01 18:00:00 2018'::timestamp without time zone)), test_gapfill_overlap.name, (first(test_gapfill_overlap.value, test_gapfill_overlap."time")), (avg(test_gapfill_overlap.value))
|
||||
-> Sort
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_overlap_1."time", 'Mon Jan 01 06:00:00 2018'::timestamp without time zone, 'Mon Jan 01 18:00:00 2018'::timestamp without time zone)), test_gapfill_overlap_1.name, (first(test_gapfill_overlap_1.value, test_gapfill_overlap_1."time")), (avg(test_gapfill_overlap_1.value))
|
||||
Sort Key: test_gapfill_overlap_1.name, (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_overlap_1."time", 'Mon Jan 01 06:00:00 2018'::timestamp without time zone, 'Mon Jan 01 18:00:00 2018'::timestamp without time zone))
|
||||
-> HashAggregate
|
||||
Output: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_overlap_1."time", 'Mon Jan 01 06:00:00 2018'::timestamp without time zone, 'Mon Jan 01 18:00:00 2018'::timestamp without time zone)), test_gapfill_overlap_1.name, first(test_gapfill_overlap_1.value, test_gapfill_overlap_1."time"), avg(test_gapfill_overlap_1.value)
|
||||
Group Key: (time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_overlap_1."time", 'Mon Jan 01 06:00:00 2018'::timestamp without time zone, 'Mon Jan 01 18:00:00 2018'::timestamp without time zone)), test_gapfill_overlap_1.name
|
||||
-> Append
|
||||
-> Custom Scan (DataNodeScan) on public.test_gapfill_overlap test_gapfill_overlap_1
|
||||
Output: time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_overlap_1."time", 'Mon Jan 01 06:00:00 2018'::timestamp without time zone, 'Mon Jan 01 18:00:00 2018'::timestamp without time zone), test_gapfill_overlap_1.name, test_gapfill_overlap_1.value, test_gapfill_overlap_1."time"
|
||||
Data node: data_node_1
|
||||
Chunks: _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk
|
||||
Remote SQL: SELECT "time", name, value FROM public.test_gapfill_overlap WHERE _timescaledb_internal.chunks_in(public.test_gapfill_overlap.*, ARRAY[29, 30, 31, 32])
|
||||
Remote EXPLAIN:
|
||||
Append
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
|
||||
-> Custom Scan (DataNodeScan) on public.test_gapfill_overlap test_gapfill_overlap_2
|
||||
Output: time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_overlap_2."time", 'Mon Jan 01 06:00:00 2018'::timestamp without time zone, 'Mon Jan 01 18:00:00 2018'::timestamp without time zone), test_gapfill_overlap_2.name, test_gapfill_overlap_2.value, test_gapfill_overlap_2."time"
|
||||
Data node: data_node_2
|
||||
Chunks: _dist_hyper_X_X_chunk
|
||||
Remote SQL: SELECT "time", name, value FROM public.test_gapfill_overlap WHERE _timescaledb_internal.chunks_in(public.test_gapfill_overlap.*, ARRAY[20])
|
||||
Remote EXPLAIN:
|
||||
Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
|
||||
-> Custom Scan (DataNodeScan) on public.test_gapfill_overlap test_gapfill_overlap_3
|
||||
Output: time_bucket_gapfill('@ 3 hours'::interval, test_gapfill_overlap_3."time", 'Mon Jan 01 06:00:00 2018'::timestamp without time zone, 'Mon Jan 01 18:00:00 2018'::timestamp without time zone), test_gapfill_overlap_3.name, test_gapfill_overlap_3.value, test_gapfill_overlap_3."time"
|
||||
Data node: data_node_3
|
||||
Chunks: _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk
|
||||
Remote SQL: SELECT "time", name, value FROM public.test_gapfill_overlap WHERE _timescaledb_internal.chunks_in(public.test_gapfill_overlap.*, ARRAY[26, 27, 28, 29, 30])
|
||||
Remote EXPLAIN:
|
||||
Append
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
-> Seq Scan on _timescaledb_internal._dist_hyper_X_X_chunk
|
||||
Output: _dist_hyper_X_X_chunk."time", _dist_hyper_X_X_chunk.name, _dist_hyper_X_X_chunk.value
|
||||
|
||||
(52 rows)
|
||||
|
||||
SET timescaledb.enable_remote_explain = false;
|
||||
DROP TABLE test_gapfill;
|
||||
DROP TABLE test_gapfill_overlap;
|
||||
@ -37,7 +37,7 @@ select 1 from metrics_dist1 where ts_debug_shippable_error_after_n_rows(10000000
|
||||
Data node: data_node_1
|
||||
Fetcher Type: Row by row
|
||||
Chunks: _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk
|
||||
Remote SQL: SELECT NULL FROM public.metrics_dist1 WHERE _timescaledb_internal.chunks_in(public.metrics_dist1.*, ARRAY[34, 35, 36]) AND ((public.ts_debug_shippable_error_after_n_rows(10000000, device_id) <> 0))
|
||||
Remote SQL: SELECT NULL FROM public.metrics_dist1 WHERE _timescaledb_internal.chunks_in(public.metrics_dist1.*, ARRAY[28, 29, 30]) AND ((public.ts_debug_shippable_error_after_n_rows(10000000, device_id) <> 0))
|
||||
(6 rows)
|
||||
|
||||
explain (analyze, verbose, costs off, timing off, summary off)
|
||||
@ -55,7 +55,7 @@ select 1 from metrics_dist1 where ts_debug_shippable_fatal_after_n_rows(10000000
|
||||
Data node: data_node_1
|
||||
Fetcher Type: Row by row
|
||||
Chunks: _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk
|
||||
Remote SQL: SELECT NULL FROM public.metrics_dist1 WHERE _timescaledb_internal.chunks_in(public.metrics_dist1.*, ARRAY[34, 35, 36]) AND ((public.ts_debug_shippable_fatal_after_n_rows(10000000, device_id) <> 0))
|
||||
Remote SQL: SELECT NULL FROM public.metrics_dist1 WHERE _timescaledb_internal.chunks_in(public.metrics_dist1.*, ARRAY[28, 29, 30]) AND ((public.ts_debug_shippable_fatal_after_n_rows(10000000, device_id) <> 0))
|
||||
(6 rows)
|
||||
|
||||
set timescaledb.remote_data_fetcher = 'cursor';
|
||||
@ -74,7 +74,7 @@ select 1 from metrics_dist1 where ts_debug_shippable_error_after_n_rows(10000000
|
||||
Data node: data_node_1
|
||||
Fetcher Type: Cursor
|
||||
Chunks: _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk
|
||||
Remote SQL: SELECT NULL FROM public.metrics_dist1 WHERE _timescaledb_internal.chunks_in(public.metrics_dist1.*, ARRAY[34, 35, 36]) AND ((public.ts_debug_shippable_error_after_n_rows(10000000, device_id) <> 0))
|
||||
Remote SQL: SELECT NULL FROM public.metrics_dist1 WHERE _timescaledb_internal.chunks_in(public.metrics_dist1.*, ARRAY[28, 29, 30]) AND ((public.ts_debug_shippable_error_after_n_rows(10000000, device_id) <> 0))
|
||||
(6 rows)
|
||||
|
||||
explain (analyze, verbose, costs off, timing off, summary off)
|
||||
@ -92,6 +92,6 @@ select 1 from metrics_dist1 where ts_debug_shippable_fatal_after_n_rows(10000000
|
||||
Data node: data_node_1
|
||||
Fetcher Type: Cursor
|
||||
Chunks: _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk, _dist_hyper_X_X_chunk
|
||||
Remote SQL: SELECT NULL FROM public.metrics_dist1 WHERE _timescaledb_internal.chunks_in(public.metrics_dist1.*, ARRAY[34, 35, 36]) AND ((public.ts_debug_shippable_fatal_after_n_rows(10000000, device_id) <> 0))
|
||||
Remote SQL: SELECT NULL FROM public.metrics_dist1 WHERE _timescaledb_internal.chunks_in(public.metrics_dist1.*, ARRAY[28, 29, 30]) AND ((public.ts_debug_shippable_fatal_after_n_rows(10000000, device_id) <> 0))
|
||||
(6 rows)
|
||||
|
||||
|
||||
@ -23,9 +23,8 @@ if(CMAKE_BUILD_TYPE MATCHES Debug)
|
||||
endif(CMAKE_BUILD_TYPE MATCHES Debug)
|
||||
|
||||
set(TEST_TEMPLATES_SHARED
|
||||
dist_gapfill_pushdown.sql.in gapfill.sql.in generated_columns.sql.in
|
||||
ordered_append.sql.in ordered_append_join.sql.in
|
||||
transparent_decompress_chunk.sql.in)
|
||||
gapfill.sql.in generated_columns.sql.in ordered_append.sql.in
|
||||
ordered_append_join.sql.in transparent_decompress_chunk.sql.in)
|
||||
|
||||
# Regression tests that vary with PostgreSQL version. Generated test files are
|
||||
# put in the original source directory since all tests must be in the same
|
||||
|
||||
@ -1,62 +0,0 @@
|
||||
-- This file and its contents are licensed under the Timescale License.
|
||||
-- Please see the included NOTICE for copyright information and
|
||||
-- LICENSE-TIMESCALE for a copy of the license.
|
||||
|
||||
\set ON_ERROR_STOP 0
|
||||
|
||||
SET enable_partitionwise_aggregate = 'on';
|
||||
SET timescaledb.enable_remote_explain = true;
|
||||
|
||||
-- Cases where gapfill is pushed down to data-nodes
|
||||
EXPLAIN (VERBOSE, COSTS OFF) SELECT time_bucket_gapfill('3 hours', time, '2017-01-01 06:00', '2017-01-01 18:00'),
|
||||
name,
|
||||
first(value, time),
|
||||
avg(value)
|
||||
FROM test_gapfill
|
||||
GROUP BY 1,2;
|
||||
|
||||
EXPLAIN (VERBOSE, COSTS OFF) SELECT time_bucket_gapfill('3 hours', time, '2017-01-01 06:00', '2017-01-01 18:00'),
|
||||
name,
|
||||
first(value, time),
|
||||
avg(value)
|
||||
FROM test_gapfill
|
||||
GROUP BY 2,1;
|
||||
|
||||
-- Check for multiple gapfill calls
|
||||
SELECT time_bucket_gapfill('3 hours', time, '2017-01-01 06:00', '2017-01-01 18:00'),
|
||||
time_bucket_gapfill('6 hours', time, '2017-01-01 08:00', '2017-01-01 18:00'),
|
||||
name,
|
||||
first(value, time),
|
||||
avg(value)
|
||||
FROM test_gapfill
|
||||
GROUP BY 2,1,3;
|
||||
|
||||
-- Cases where gapfill is not pushed down to data-nodes
|
||||
|
||||
-- Space dimension is not in group by clause
|
||||
EXPLAIN (VERBOSE, COSTS OFF) SELECT time_bucket_gapfill('3 hours', time, '2017-01-01 06:00', '2017-01-02 18:00'),
|
||||
first(value, time),
|
||||
avg(value)
|
||||
FROM test_gapfill
|
||||
GROUP BY 1;
|
||||
|
||||
-- Window functions
|
||||
EXPLAIN (VERBOSE, COSTS OFF) SELECT
|
||||
time_bucket_gapfill('3 hours', time, '2017-01-01 06:00', '2017-01-01 18:00'),
|
||||
lag(min(time)) OVER ()
|
||||
FROM test_gapfill
|
||||
GROUP BY 1;
|
||||
|
||||
-- Data nodes are overlapping
|
||||
|
||||
EXPLAIN (VERBOSE, COSTS OFF) SELECT time_bucket_gapfill('3 hours', time, '2018-01-01 06:00', '2018-01-01 18:00'),
|
||||
name,
|
||||
first(value, time),
|
||||
avg(value)
|
||||
FROM test_gapfill_overlap
|
||||
GROUP BY 1,2;
|
||||
|
||||
SET timescaledb.enable_remote_explain = false;
|
||||
|
||||
DROP TABLE test_gapfill;
|
||||
DROP TABLE test_gapfill_overlap;
|
||||
@ -13,16 +13,14 @@ SELECT time_bucket_gapfill('3 hours', time, '2017-01-01 06:00', '2017-01-01 18:0
|
||||
first(value, time),
|
||||
avg(value)
|
||||
FROM :CONDITIONS
|
||||
GROUP BY 1,2
|
||||
ORDER BY 2,1;
|
||||
GROUP BY 1,2;
|
||||
|
||||
SELECT time_bucket_gapfill('3 hours', time, '2017-01-01 06:00', '2017-01-01 18:00'),
|
||||
device,
|
||||
first(value, time),
|
||||
avg(value)
|
||||
FROM :CONDITIONS
|
||||
GROUP BY 2,1
|
||||
ORDER BY 2,1;
|
||||
GROUP BY 2,1;
|
||||
|
||||
SELECT
|
||||
time_bucket_gapfill('3 hours', time, '2017-01-01 06:00', '2017-01-01 18:00'),
|
||||
|
||||
@ -156,8 +156,8 @@ INSERT INTO metrics_tstz VALUES
|
||||
;
|
||||
|
||||
CREATE TABLE conditions(
|
||||
time timestamptz NOT NULL,
|
||||
device int,
|
||||
time timestamptz NOT NULL,
|
||||
device int,
|
||||
value float
|
||||
);
|
||||
SELECT * FROM create_hypertable('conditions', 'time');
|
||||
@ -172,8 +172,8 @@ INSERT INTO conditions VALUES
|
||||
('2018-07-01 08:01', 29, 64);
|
||||
|
||||
CREATE TABLE conditions_dist(
|
||||
time timestamptz NOT NULL,
|
||||
device int,
|
||||
time timestamptz NOT NULL,
|
||||
device int,
|
||||
value float
|
||||
);
|
||||
SELECT * FROM create_distributed_hypertable('conditions_dist', 'time', 'device', 3);
|
||||
@ -202,8 +202,8 @@ INSERT INTO metrics_int_dist VALUES
|
||||
(100,1,2,-100.0);
|
||||
|
||||
CREATE TABLE conditions_dist1(
|
||||
time timestamptz NOT NULL,
|
||||
device int,
|
||||
time timestamptz NOT NULL,
|
||||
device int,
|
||||
value float
|
||||
);
|
||||
SELECT * FROM create_distributed_hypertable('conditions_dist1', 'time', 'device', 1,
|
||||
@ -244,7 +244,7 @@ SELECT create_distributed_hypertable('dist_chunk_copy', 'time', 'device', replic
|
||||
ALTER TABLE dist_chunk_copy SET (timescaledb.compress);
|
||||
|
||||
SELECT setseed(0);
|
||||
INSERT INTO dist_chunk_copy
|
||||
INSERT INTO dist_chunk_copy
|
||||
SELECT t, ceil(_timescaledb_internal.get_partition_hash(t)::int % 5), random() * 20
|
||||
FROM generate_series('2020-01-01'::timestamp, '2020-01-25'::timestamp, '1d') t;
|
||||
|
||||
@ -274,44 +274,9 @@ create table distinct_on_distributed(ts timestamp, id int, val numeric);
|
||||
select create_distributed_hypertable('distinct_on_distributed', 'ts');
|
||||
insert into distinct_on_distributed select * from distinct_on_hypertable;
|
||||
|
||||
-- Table with non-overlapping data across data-nodes to test gapfill pushdown to data nodes
|
||||
CREATE TABLE test_gapfill(time timestamp, name text, value numeric);
|
||||
|
||||
SELECT table_name from create_distributed_hypertable('test_gapfill', 'time', partitioning_column => 'name');
|
||||
|
||||
INSERT INTO test_gapfill VALUES
|
||||
('2018-01-01 06:01', 'one', 1.2),
|
||||
('2018-01-02 09:11', 'two', 4.3),
|
||||
('2018-01-03 08:01', 'three', 7.3),
|
||||
('2018-01-04 08:01', 'one', 0.23),
|
||||
('2018-07-05 08:01', 'five', 0.0),
|
||||
('2018-07-06 06:01', 'forty', 3.1),
|
||||
('2018-07-07 09:11', 'eleven', 10303.12),
|
||||
('2018-07-08 08:01', 'ten', 64);
|
||||
|
||||
-- Make table with data nodes overlapping
|
||||
|
||||
CREATE TABLE test_gapfill_overlap(time timestamp, name text, value numeric);
|
||||
|
||||
SELECT table_name from create_distributed_hypertable('test_gapfill_overlap', 'time', partitioning_column => 'name');
|
||||
|
||||
INSERT INTO test_gapfill_overlap SELECT * FROM test_gapfill;
|
||||
|
||||
SELECT set_number_partitions('test_gapfill_overlap', 4);
|
||||
|
||||
INSERT INTO test_gapfill_overlap VALUES
|
||||
('2020-01-01 06:01', 'eleven', 1.2),
|
||||
('2020-01-02 09:11', 'twenty-two', 4.3),
|
||||
('2020-01-03 08:01', 'three', 7.3),
|
||||
('2020-01-04 08:01', 'one', 0.23),
|
||||
('2020-07-05 08:01', 'five', 0.0),
|
||||
('2020-07-06 06:01', 'forty-six', 3.1),
|
||||
('2020-07-07 09:11', 'eleven', 10303.12),
|
||||
('2020-07-08 08:01', 'ten', 64);
|
||||
|
||||
-- Distributed table with custom type that has no binary output
|
||||
CREATE TABLE disttable_with_ct(time timestamptz, txn_id rxid, val float, info text);
|
||||
SELECT * FROM create_hypertable('disttable_with_ct', 'time', replication_factor => 2);
|
||||
SELECT * FROM create_hypertable('disttable_with_ct', 'time', replication_factor => 1);
|
||||
|
||||
-- Insert data with custom type
|
||||
INSERT INTO disttable_with_ct VALUES
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user