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https://github.com/timescale/timescaledb.git
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584f5d1061
This commit introduces 4 compression algorithms as well as 3 ADTs to support them. The compression algorithms are time-series optimized. The following algorithms are implemented: - DeltaDelta compresses integer and timestamp values - Gorilla compresses floats - Dictionary compression handles any data type and is optimized for low-cardinality datasets. - Array stores any data type in an array-like structure and does not actually compress it (though TOAST-based compression can be applied on top). These compression algorithms are are fully described in tsl/src/compression/README.md. The Abstract Data Types that are implemented are - Vector - A dynamic vector that can store any type. - BitArray - A dynamic vector to store bits. - SimpleHash - A hash table implementation from PG12. More information can be found in src/adts/README.md
60 lines
2.8 KiB
SQL
60 lines
2.8 KiB
SQL
-- This file and its contents are licensed under the Apache License 2.0.
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-- Please see the included NOTICE for copyright information and
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-- LICENSE-APACHE for a copy of the license.
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-- This file is meant to contain aggregate functions that need to be created only
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-- once and not recreated during updates.
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-- There is no CREATE OR REPLACE AGGREGATE which means that the only way to replace
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-- an aggregate is to DROP then CREATE which is problematic as it will fail
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-- if the previous version of the aggregate has dependencies.
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-- NOTE that WHEN CREATING NEW FUNCTIONS HERE you should also make sure they are
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-- created in an update script so that both new users and people updating from a
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-- previous version get the new function
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--This aggregate returns the "first" element of the first argument when ordered by the second argument.
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--Ex. first(temp, time) returns the temp value for the row with the lowest time
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CREATE AGGREGATE first(anyelement, "any") (
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SFUNC = _timescaledb_internal.first_sfunc,
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STYPE = internal,
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COMBINEFUNC = _timescaledb_internal.first_combinefunc,
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SERIALFUNC = _timescaledb_internal.bookend_serializefunc,
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DESERIALFUNC = _timescaledb_internal.bookend_deserializefunc,
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PARALLEL = SAFE,
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FINALFUNC = _timescaledb_internal.bookend_finalfunc,
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FINALFUNC_EXTRA
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);
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--This aggregate returns the "last" element of the first argument when ordered by the second argument.
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--Ex. last(temp, time) returns the temp value for the row with highest time
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CREATE AGGREGATE last(anyelement, "any") (
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SFUNC = _timescaledb_internal.last_sfunc,
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STYPE = internal,
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COMBINEFUNC = _timescaledb_internal.last_combinefunc,
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SERIALFUNC = _timescaledb_internal.bookend_serializefunc,
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DESERIALFUNC = _timescaledb_internal.bookend_deserializefunc,
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PARALLEL = SAFE,
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FINALFUNC = _timescaledb_internal.bookend_finalfunc,
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FINALFUNC_EXTRA
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);
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-- This aggregate partitions the dataset into a specified number of buckets (nbuckets) ranging
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-- from the inputted min to max values.
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CREATE AGGREGATE histogram (DOUBLE PRECISION, DOUBLE PRECISION, DOUBLE PRECISION, INTEGER) (
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SFUNC = _timescaledb_internal.hist_sfunc,
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STYPE = INTERNAL,
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COMBINEFUNC = _timescaledb_internal.hist_combinefunc,
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SERIALFUNC = _timescaledb_internal.hist_serializefunc,
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DESERIALFUNC = _timescaledb_internal.hist_deserializefunc,
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PARALLEL = SAFE,
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FINALFUNC = _timescaledb_internal.hist_finalfunc,
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FINALFUNC_EXTRA
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);
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CREATE AGGREGATE _timescaledb_internal.finalize_agg(agg_name TEXT, inner_agg_collation_schema NAME, inner_agg_collation_name NAME, inner_agg_input_types NAME[][], inner_agg_serialized_state BYTEA, return_type_dummy_val anyelement) (
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SFUNC = _timescaledb_internal.finalize_agg_sfunc,
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STYPE = internal,
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FINALFUNC = _timescaledb_internal.finalize_agg_ffunc,
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FINALFUNC_EXTRA
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);
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