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dist_query-15.out
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dist_query-15.out
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-- 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.
\c :TEST_DBNAME :ROLE_CLUSTER_SUPERUSER;
\set TEST_BASE_NAME dist_query
-- Run
SELECT format('include/%s_load.sql', :'TEST_BASE_NAME') AS "TEST_LOAD_NAME",
format('include/%s_run.sql', :'TEST_BASE_NAME') AS "TEST_QUERY_NAME",
format('%s/results/%s_results_reference.out', :'TEST_OUTPUT_DIR', :'TEST_BASE_NAME') AS "TEST_RESULTS_REFERENCE",
format('%s/results/%s_results_repartitioning_reference.out', :'TEST_OUTPUT_DIR', :'TEST_BASE_NAME') AS "TEST_RESULTS_REPART_REFERENCE",
format('%s/results/%s_results_optimized.out', :'TEST_OUTPUT_DIR', :'TEST_BASE_NAME') AS "TEST_RESULTS_OPTIMIZED",
format('%s/results/%s_results_repartitioning_optimized.out', :'TEST_OUTPUT_DIR', :'TEST_BASE_NAME') AS "TEST_RESULTS_REPART_OPTIMIZED",
format('%s/results/%s_results_unoptimized.out', :'TEST_OUTPUT_DIR', :'TEST_BASE_NAME') AS "TEST_RESULTS_UNOPTIMIZED",
format('%s/results/%s_results_1dim.out', :'TEST_OUTPUT_DIR', :'TEST_BASE_NAME') AS "TEST_RESULTS_1DIM"
\gset
SELECT format('\! diff %s %s', :'TEST_RESULTS_UNOPTIMIZED', :'TEST_RESULTS_REFERENCE') AS "DIFF_CMD_UNOPT",
format('\! diff %s %s', :'TEST_RESULTS_OPTIMIZED', :'TEST_RESULTS_REFERENCE') AS "DIFF_CMD_OPT",
format('\! diff %s %s', :'TEST_RESULTS_REPART_OPTIMIZED', :'TEST_RESULTS_REPART_REFERENCE') AS "DIFF_CMD_REPART",
format('\! diff %s %s', :'TEST_RESULTS_1DIM', :'TEST_RESULTS_REPART_REFERENCE') AS "DIFF_CMD_1DIM"
\gset
-- Use a small fetch size to make sure that result are fetched across
-- multiple fetches.
--ALTER FOREIGN DATA WRAPPER timescaledb_fdw OPTIONS (ADD fetch_size '500');
SET client_min_messages TO notice;
-- Load the data
\ir :TEST_LOAD_NAME
-- 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.
\ir debugsupport.sql
-- 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.
CREATE OR REPLACE FUNCTION test.tsl_override_current_timestamptz(new_value TIMESTAMPTZ)
RETURNS VOID AS :TSL_MODULE_PATHNAME, 'ts_test_override_current_timestamptz' LANGUAGE C VOLATILE;
\set DATA_NODE_1 :TEST_DBNAME _1
\set DATA_NODE_2 :TEST_DBNAME _2
\set DATA_NODE_3 :TEST_DBNAME _3
-- Add data nodes
SET ROLE :ROLE_CLUSTER_SUPERUSER;
SELECT node_name, database, node_created, database_created, extension_created
FROM (
SELECT (add_data_node(name, host => 'localhost', DATABASE => name)).*
FROM (VALUES (:'DATA_NODE_1'), (:'DATA_NODE_2'), (:'DATA_NODE_3')) v(name)
) a;
node_name | database | node_created | database_created | extension_created
-----------------+-----------------+--------------+------------------+-------------------
db_dist_query_1 | db_dist_query_1 | t | t | t
db_dist_query_2 | db_dist_query_2 | t | t | t
db_dist_query_3 | db_dist_query_3 | t | t | t
(3 rows)
GRANT USAGE ON FOREIGN SERVER :DATA_NODE_1, :DATA_NODE_2, :DATA_NODE_3 TO :ROLE_1;
GRANT CREATE ON SCHEMA public TO :ROLE_1;
SET ROLE :ROLE_1;
-- Create a "normal" PG table as reference, one two-dimensional
-- distributed hypertable, and a one-dimensional distributed
-- hypertable
CREATE TABLE reference (time timestamptz NOT NULL, device int, location int, temp float);
CREATE TABLE hyper (LIKE reference);
CREATE TABLE hyper1d (LIKE reference);
SELECT create_distributed_hypertable('hyper', 'time', 'device', 3,
chunk_time_interval => interval '18 hours');
create_distributed_hypertable
-------------------------------
(1,public,hyper,t)
(1 row)
SELECT create_distributed_hypertable('hyper1d', 'time', chunk_time_interval => interval '36 hours');
create_distributed_hypertable
-------------------------------
(2,public,hyper1d,t)
(1 row)
SELECT setseed(1);
setseed
---------
(1 row)
INSERT INTO reference
SELECT t, (abs(timestamp_hash(t::timestamp)) % 10) + 1, (random() * 20)::int, random() * 80
FROM generate_series('2019-01-01'::timestamptz, '2019-01-04'::timestamptz, '1 minute') as t;
-- Insert the same data into the hypertable but repartition the data
-- set so that we can test the "safeness" of some push-downs across
-- the repartitioning boundary.
INSERT INTO hyper
SELECT * FROM reference
WHERE time < '2019-01-02 05:10'::timestamptz
ORDER BY time;
SELECT * FROM set_number_partitions('hyper', 2);
psql:include/dist_query_load.sql:47: WARNING: insufficient number of partitions for dimension "device"
set_number_partitions
-----------------------
(1 row)
INSERT INTO hyper
SELECT * FROM reference
WHERE time >= '2019-01-02 05:10'::timestamptz
AND time < '2019-01-03 01:22'::timestamptz
ORDER BY time;
SELECT * FROM set_number_partitions('hyper', 5);
set_number_partitions
-----------------------
(1 row)
INSERT INTO hyper
SELECT * FROM reference
WHERE time >= '2019-01-03 01:22'::timestamptz
ORDER BY time;
INSERT INTO hyper1d
SELECT * FROM reference ORDER BY time;
SELECT d.hypertable_id, d.id, ds.range_start, ds.range_end
FROM _timescaledb_catalog.dimension d, _timescaledb_catalog.dimension_slice ds
WHERE num_slices IS NOT NULL
AND d.id = ds.dimension_id
ORDER BY 1, 2, 3, 4;
hypertable_id | id | range_start | range_end
---------------+----+----------------------+---------------------
1 | 2 | -9223372036854775808 | 429496729
1 | 2 | -9223372036854775808 | 715827882
1 | 2 | -9223372036854775808 | 1073741823
1 | 2 | 429496729 | 858993458
1 | 2 | 715827882 | 1431655764
1 | 2 | 858993458 | 1288490187
1 | 2 | 1073741823 | 9223372036854775807
1 | 2 | 1288490187 | 1717986916
1 | 2 | 1431655764 | 9223372036854775807
1 | 2 | 1717986916 | 9223372036854775807
(10 rows)
-- Set the max time we can query without hitting the repartitioned
-- chunks. Note that this is before the given repartitioning time
-- above because chunk boundaries do not align exactly with the given
-- timestamp
\set REPARTITIONED_TIME_RANGE 'time >= ''2019-01-01'''
\set CLEAN_PARTITIONING_TIME_RANGE 'time BETWEEN ''2019-01-01'' AND ''2019-01-01 15:00'''
-- Custom agg func for push down tests
CREATE AGGREGATE custom_sum(int4) (
SFUNC = int4_sum,
STYPE = int8
);
-- Set seed on all data nodes for ANALYZE to sample consistently
CALL distributed_exec($$ SELECT setseed(1); $$);
ANALYZE reference;
ANALYZE hyper;
ANALYZE hyper1d;
SELECT hypertable_schema, hypertable_name, num_dimensions, num_chunks
FROM timescaledb_information.hypertables
ORDER BY 1,2;
hypertable_schema | hypertable_name | num_dimensions | num_chunks
-------------------+-----------------+----------------+------------
public | hyper | 2 | 18
public | hyper1d | 1 | 3
(2 rows)
SELECT count(*) FROM hyper;
count
-------
4321
(1 row)
SELECT count(*) FROM hyper WHERE :CLEAN_PARTITIONING_TIME_RANGE;
count
-------
901
(1 row)
SET enable_partitionwise_aggregate = ON;
\set ECHO errors
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%% RUNNING TESTS on table: hyper
%%% PREFIX: EXPLAIN (verbose, costs off)
%%% WHERE_CLAUSE: :CLEAN_PARTITIONING_TIME_RANGE
%%% ORDER_BY_1:
%%% ORDER_BY_1_2:
%%% LIMIT:
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
setseed
---------
(1 row)
######### Grouping on time only (partial aggregation)
EXPLAIN (verbose, costs off)
SELECT time, avg(temp)
FROM hyper
WHERE time BETWEEN '2019-01-01' AND '2019-01-01 15:00'
GROUP BY 1
QUERY PLAN
---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Finalize HashAggregate
Output: "time", avg(temp)
Group Key: "time"
-> Custom Scan (AsyncAppend)
Output: "time", (PARTIAL avg(temp))
-> Append
-> Custom Scan (DataNodeScan)
Output: hyper."time", (PARTIAL avg(hyper.temp))
Relations: Aggregate on (public.hyper)
Data node: db_dist_query_1
Chunks: _dist_hyper_1_1_chunk
Remote SQL: SELECT "time", _timescaledb_internal.partialize_agg(avg(temp)) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) GROUP BY 1
-> Custom Scan (DataNodeScan)
Output: hyper_1."time", (PARTIAL avg(hyper_1.temp))
Relations: Aggregate on (public.hyper)
Data node: db_dist_query_2
Chunks: _dist_hyper_1_2_chunk
Remote SQL: SELECT "time", _timescaledb_internal.partialize_agg(avg(temp)) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) GROUP BY 1
-> Partial GroupAggregate
Output: hyper_2."time", PARTIAL avg(hyper_2.temp)
Group Key: hyper_2."time"
-> Custom Scan (DataNodeScan) on public.hyper hyper_2
Output: hyper_2."time", hyper_2.temp
Data node: db_dist_query_3
Chunks: _dist_hyper_1_3_chunk
Remote SQL: SELECT "time", temp FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) ORDER BY "time" ASC NULLS LAST
(26 rows)
######### Grouping on time only (partial aggregation)
EXPLAIN (verbose, costs off)
SELECT time_bucket('2 days', time) AS time, avg(temp)
FROM hyper
WHERE time BETWEEN '2019-01-01' AND '2019-01-01 15:00'
GROUP BY 1
QUERY PLAN
---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Finalize HashAggregate
Output: (time_bucket('@ 2 days'::interval, "time")), avg(temp)
Group Key: (time_bucket('@ 2 days'::interval, "time"))
-> Custom Scan (AsyncAppend)
Output: (time_bucket('@ 2 days'::interval, "time")), (PARTIAL avg(temp))
-> Append
-> Custom Scan (DataNodeScan)
Output: (time_bucket('@ 2 days'::interval, hyper."time")), (PARTIAL avg(hyper.temp))
Relations: Aggregate on (public.hyper)
Data node: db_dist_query_1
Chunks: _dist_hyper_1_1_chunk
Remote SQL: SELECT public.time_bucket('@ 2 days'::interval, "time"), _timescaledb_internal.partialize_agg(avg(temp)) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) GROUP BY 1
-> Custom Scan (DataNodeScan)
Output: (time_bucket('@ 2 days'::interval, hyper_1."time")), (PARTIAL avg(hyper_1.temp))
Relations: Aggregate on (public.hyper)
Data node: db_dist_query_2
Chunks: _dist_hyper_1_2_chunk
Remote SQL: SELECT public.time_bucket('@ 2 days'::interval, "time"), _timescaledb_internal.partialize_agg(avg(temp)) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) GROUP BY 1
-> Custom Scan (DataNodeScan)
Output: (time_bucket('@ 2 days'::interval, hyper_2."time")), (PARTIAL avg(hyper_2.temp))
Relations: Aggregate on (public.hyper)
Data node: db_dist_query_3
Chunks: _dist_hyper_1_3_chunk
Remote SQL: SELECT public.time_bucket('@ 2 days'::interval, "time"), _timescaledb_internal.partialize_agg(avg(temp)) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) GROUP BY 1
(24 rows)
######### Grouping on time and device (full aggregation)
EXPLAIN (verbose, costs off)
SELECT time, device, avg(temp)
FROM hyper
WHERE time BETWEEN '2019-01-01' AND '2019-01-01 15:00'
GROUP BY 1,2
QUERY PLAN
-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Custom Scan (AsyncAppend)
Output: "time", device, (avg(temp))
-> Append
-> Custom Scan (DataNodeScan)
Output: hyper."time", hyper.device, (avg(hyper.temp))
Relations: Aggregate on (public.hyper)
Data node: db_dist_query_1
Chunks: _dist_hyper_1_1_chunk
Remote SQL: SELECT "time", device, avg(temp) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) GROUP BY 1, 2
-> Custom Scan (DataNodeScan)
Output: hyper_1."time", hyper_1.device, (avg(hyper_1.temp))
Relations: Aggregate on (public.hyper)
Data node: db_dist_query_2
Chunks: _dist_hyper_1_2_chunk
Remote SQL: SELECT "time", device, avg(temp) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) GROUP BY 1, 2
-> GroupAggregate
Output: hyper_2."time", hyper_2.device, avg(hyper_2.temp)
Group Key: hyper_2."time", hyper_2.device
-> Custom Scan (DataNodeScan) on public.hyper hyper_2
Output: hyper_2."time", hyper_2.device, hyper_2.temp
Data node: db_dist_query_3
Chunks: _dist_hyper_1_3_chunk
Remote SQL: SELECT "time", device, temp FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) ORDER BY "time" ASC NULLS LAST, device ASC NULLS LAST
(23 rows)
######### Grouping on time and device (full aggregation)
EXPLAIN (verbose, costs off)
SELECT time_bucket('2 days', time) AS time, device, avg(temp)
FROM hyper
WHERE time BETWEEN '2019-01-01' AND '2019-01-01 15:00'
GROUP BY 1,2
QUERY PLAN
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Custom Scan (AsyncAppend)
Output: (time_bucket('@ 2 days'::interval, "time")), device, (avg(temp))
-> Append
-> Custom Scan (DataNodeScan)
Output: (time_bucket('@ 2 days'::interval, hyper."time")), hyper.device, (avg(hyper.temp))
Relations: Aggregate on (public.hyper)
Data node: db_dist_query_1
Chunks: _dist_hyper_1_1_chunk
Remote SQL: SELECT public.time_bucket('@ 2 days'::interval, "time"), device, avg(temp) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) GROUP BY 1, 2
-> Custom Scan (DataNodeScan)
Output: (time_bucket('@ 2 days'::interval, hyper_1."time")), hyper_1.device, (avg(hyper_1.temp))
Relations: Aggregate on (public.hyper)
Data node: db_dist_query_2
Chunks: _dist_hyper_1_2_chunk
Remote SQL: SELECT public.time_bucket('@ 2 days'::interval, "time"), device, avg(temp) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) GROUP BY 1, 2
-> Custom Scan (DataNodeScan)
Output: (time_bucket('@ 2 days'::interval, hyper_2."time")), hyper_2.device, (avg(hyper_2.temp))
Relations: Aggregate on (public.hyper)
Data node: db_dist_query_3
Chunks: _dist_hyper_1_3_chunk
Remote SQL: SELECT public.time_bucket('@ 2 days'::interval, "time"), device, avg(temp) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) GROUP BY 1, 2
(21 rows)
######### Grouping on time and device (full aggregation)
EXPLAIN (verbose, costs off)
SELECT date_trunc('month', time) AS time, device, avg(temp)
FROM hyper
WHERE time BETWEEN '2019-01-01' AND '2019-01-01 15:00'
GROUP BY 1,2
QUERY PLAN
---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Custom Scan (AsyncAppend)
Output: (date_trunc('month'::text, "time")), device, (avg(temp))
-> Append
-> Custom Scan (DataNodeScan)
Output: (date_trunc('month'::text, hyper."time")), hyper.device, (avg(hyper.temp))
Relations: Aggregate on (public.hyper)
Data node: db_dist_query_1
Chunks: _dist_hyper_1_1_chunk
Remote SQL: SELECT date_trunc('month'::text, "time"), device, avg(temp) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) GROUP BY 1, 2
-> Custom Scan (DataNodeScan)
Output: (date_trunc('month'::text, hyper_1."time")), hyper_1.device, (avg(hyper_1.temp))
Relations: Aggregate on (public.hyper)
Data node: db_dist_query_2
Chunks: _dist_hyper_1_2_chunk
Remote SQL: SELECT date_trunc('month'::text, "time"), device, avg(temp) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) GROUP BY 1, 2
-> Custom Scan (DataNodeScan)
Output: (date_trunc('month'::text, hyper_2."time")), hyper_2.device, (avg(hyper_2.temp))
Relations: Aggregate on (public.hyper)
Data node: db_dist_query_3
Chunks: _dist_hyper_1_3_chunk
Remote SQL: SELECT date_trunc('month'::text, "time"), device, avg(temp) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) GROUP BY 1, 2
(21 rows)
######### Grouping on time and device (full aggregation)
EXPLAIN (verbose, costs off)
SELECT time_bucket('2 days', time) AS time, device, avg(temp)
FROM hyper
WHERE time BETWEEN '2019-01-01' AND '2019-01-01 15:00'
GROUP BY 1,2
HAVING device > 4
QUERY PLAN
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Custom Scan (AsyncAppend)
Output: (time_bucket('@ 2 days'::interval, "time")), device, (avg(temp))
-> Append
-> Custom Scan (DataNodeScan)
Output: (time_bucket('@ 2 days'::interval, hyper."time")), hyper.device, (avg(hyper.temp))
Relations: Aggregate on (public.hyper)
Data node: db_dist_query_1
Chunks: _dist_hyper_1_1_chunk
Remote SQL: SELECT public.time_bucket('@ 2 days'::interval, "time"), device, avg(temp) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) AND ((device > 4)) GROUP BY 1, 2
-> Custom Scan (DataNodeScan)
Output: (time_bucket('@ 2 days'::interval, hyper_1."time")), hyper_1.device, (avg(hyper_1.temp))
Relations: Aggregate on (public.hyper)
Data node: db_dist_query_2
Chunks: _dist_hyper_1_2_chunk
Remote SQL: SELECT public.time_bucket('@ 2 days'::interval, "time"), device, avg(temp) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) AND ((device > 4)) GROUP BY 1, 2
-> GroupAggregate
Output: (time_bucket('@ 2 days'::interval, hyper_2."time")), hyper_2.device, avg(hyper_2.temp)
Group Key: time_bucket('@ 2 days'::interval, hyper_2."time"), hyper_2.device
-> Result
Output: time_bucket('@ 2 days'::interval, hyper_2."time"), hyper_2.device, hyper_2.temp
-> Custom Scan (DataNodeScan) on public.hyper hyper_2
Output: hyper_2."time", hyper_2.device, hyper_2.temp
Data node: db_dist_query_3
Chunks: _dist_hyper_1_3_chunk
Remote SQL: SELECT "time", device, temp FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) AND ((device > 4)) ORDER BY public.time_bucket('2 days'::interval, "time") ASC NULLS LAST, device ASC NULLS LAST
(25 rows)
EXPLAIN (verbose, costs off)
SELECT time_bucket('2 days', time) AS time, device, avg(temp)
FROM hyper
WHERE time BETWEEN '2019-01-01' AND '2019-01-01 15:00'
GROUP BY 1,2
HAVING avg(temp) > 40 AND max(temp) < 70
QUERY PLAN
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Custom Scan (AsyncAppend)
Output: (time_bucket('@ 2 days'::interval, "time")), device, (avg(temp))
-> Append
-> Custom Scan (DataNodeScan)
Output: (time_bucket('@ 2 days'::interval, hyper."time")), hyper.device, (avg(hyper.temp))
Relations: Aggregate on (public.hyper)
Data node: db_dist_query_1
Chunks: _dist_hyper_1_1_chunk
Remote SQL: SELECT public.time_bucket('@ 2 days'::interval, "time"), device, avg(temp) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) GROUP BY 1, 2 HAVING ((avg(temp) > 40::double precision)) AND ((max(temp) < 70::double precision))
-> Custom Scan (DataNodeScan)
Output: (time_bucket('@ 2 days'::interval, hyper_1."time")), hyper_1.device, (avg(hyper_1.temp))
Relations: Aggregate on (public.hyper)
Data node: db_dist_query_2
Chunks: _dist_hyper_1_2_chunk
Remote SQL: SELECT public.time_bucket('@ 2 days'::interval, "time"), device, avg(temp) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) GROUP BY 1, 2 HAVING ((avg(temp) > 40::double precision)) AND ((max(temp) < 70::double precision))
-> Custom Scan (DataNodeScan)
Output: (time_bucket('@ 2 days'::interval, hyper_2."time")), hyper_2.device, (avg(hyper_2.temp))
Relations: Aggregate on (public.hyper)
Data node: db_dist_query_3
Chunks: _dist_hyper_1_3_chunk
Remote SQL: SELECT public.time_bucket('@ 2 days'::interval, "time"), device, avg(temp) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) GROUP BY 1, 2 HAVING ((avg(temp) > 40::double precision)) AND ((max(temp) < 70::double precision))
(21 rows)
######### Grouping on device only (full aggregation)
EXPLAIN (verbose, costs off)
SELECT device, avg(temp)
FROM hyper
WHERE time BETWEEN '2019-01-01' AND '2019-01-01 15:00'
GROUP BY 1
QUERY PLAN
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Custom Scan (AsyncAppend)
Output: device, (avg(temp))
-> Append
-> Custom Scan (DataNodeScan)
Output: hyper.device, (avg(hyper.temp))
Relations: Aggregate on (public.hyper)
Data node: db_dist_query_1
Chunks: _dist_hyper_1_1_chunk
Remote SQL: SELECT device, avg(temp) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) GROUP BY 1
-> Custom Scan (DataNodeScan)
Output: hyper_1.device, (avg(hyper_1.temp))
Relations: Aggregate on (public.hyper)
Data node: db_dist_query_2
Chunks: _dist_hyper_1_2_chunk
Remote SQL: SELECT device, avg(temp) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) GROUP BY 1
-> GroupAggregate
Output: hyper_2.device, avg(hyper_2.temp)
Group Key: hyper_2.device
-> Custom Scan (DataNodeScan) on public.hyper hyper_2
Output: hyper_2.device, hyper_2.temp
Data node: db_dist_query_3
Chunks: _dist_hyper_1_3_chunk
Remote SQL: SELECT device, temp FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) ORDER BY device ASC NULLS LAST
(23 rows)
######### No push down on some functions
EXPLAIN (verbose, costs off)
SELECT location, avg(temp)
FROM hyper
WHERE time BETWEEN '2019-01-01' AND '2019-01-01 15:00' AND (temp * random() >= 0)
GROUP BY 1
QUERY PLAN
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
GroupAggregate
Output: hyper.location, avg(hyper.temp)
Group Key: hyper.location
-> Custom Scan (AsyncAppend)
Output: hyper.location, hyper.temp
-> Merge Append
Sort Key: hyper_1.location
-> Custom Scan (DataNodeScan) on public.hyper hyper_1
Output: hyper_1.location, hyper_1.temp
Filter: ((hyper_1.temp * random()) >= '0'::double precision)
Data node: db_dist_query_1
Chunks: _dist_hyper_1_1_chunk
Remote SQL: SELECT location, temp FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) ORDER BY location ASC NULLS LAST
-> Custom Scan (DataNodeScan) on public.hyper hyper_2
Output: hyper_2.location, hyper_2.temp
Filter: ((hyper_2.temp * random()) >= '0'::double precision)
Data node: db_dist_query_2
Chunks: _dist_hyper_1_2_chunk
Remote SQL: SELECT location, temp FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) ORDER BY location ASC NULLS LAST
-> Custom Scan (DataNodeScan) on public.hyper hyper_3
Output: hyper_3.location, hyper_3.temp
Filter: ((hyper_3.temp * random()) >= '0'::double precision)
Data node: db_dist_query_3
Chunks: _dist_hyper_1_3_chunk
Remote SQL: SELECT location, temp FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) ORDER BY location ASC NULLS LAST
(25 rows)
######### No push down on some functions
EXPLAIN (verbose, costs off)
SELECT time_bucket('2 days', time) AS time, device, avg(temp), sum(temp * (random() <= 1)::int) as sum
FROM hyper
WHERE time BETWEEN '2019-01-01' AND '2019-01-01 15:00'
GROUP BY 1,2
QUERY PLAN
---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
HashAggregate
Output: (time_bucket('@ 2 days'::interval, hyper."time")), hyper.device, avg(hyper.temp), sum((hyper.temp * (((random() <= '1'::double precision))::integer)::double precision))
Group Key: (time_bucket('@ 2 days'::interval, hyper."time")), hyper.device
-> Custom Scan (AsyncAppend)
Output: (time_bucket('@ 2 days'::interval, hyper."time")), hyper.device, hyper.temp
-> Append
-> Result
Output: time_bucket('@ 2 days'::interval, hyper_1."time"), hyper_1.device, hyper_1.temp
-> Custom Scan (DataNodeScan) on public.hyper hyper_1
Output: hyper_1."time", hyper_1.device, hyper_1.temp
Data node: db_dist_query_1
Chunks: _dist_hyper_1_1_chunk
Remote SQL: SELECT "time", device, temp FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) ORDER BY public.time_bucket('2 days'::interval, "time") ASC NULLS LAST, device ASC NULLS LAST
-> Result
Output: time_bucket('@ 2 days'::interval, hyper_2."time"), hyper_2.device, hyper_2.temp
-> Custom Scan (DataNodeScan) on public.hyper hyper_2
Output: hyper_2."time", hyper_2.device, hyper_2.temp
Data node: db_dist_query_2
Chunks: _dist_hyper_1_2_chunk
Remote SQL: SELECT "time", device, temp FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) ORDER BY public.time_bucket('2 days'::interval, "time") ASC NULLS LAST, device ASC NULLS LAST
-> Result
Output: time_bucket('@ 2 days'::interval, hyper_3."time"), hyper_3.device, hyper_3.temp
-> Custom Scan (DataNodeScan) on public.hyper hyper_3
Output: hyper_3."time", hyper_3.device, hyper_3.temp
Data node: db_dist_query_3
Chunks: _dist_hyper_1_3_chunk
Remote SQL: SELECT "time", device, temp FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) ORDER BY public.time_bucket('2 days'::interval, "time") ASC NULLS LAST, device ASC NULLS LAST
(27 rows)
######### No push down on some functions
EXPLAIN (verbose, costs off)
SELECT time, device, avg(temp)
FROM hyper
WHERE time BETWEEN '2019-01-01' AND '2019-01-01 15:00'
GROUP BY 1,2
HAVING avg(temp) * custom_sum(device) > 0.8
QUERY PLAN
-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
HashAggregate
Output: hyper."time", hyper.device, avg(hyper.temp)
Group Key: hyper."time", hyper.device
Filter: ((avg(hyper.temp) * (custom_sum(hyper.device))::double precision) > '0.8'::double precision)
-> Custom Scan (AsyncAppend)
Output: hyper."time", hyper.device, hyper.temp
-> Append
-> Custom Scan (DataNodeScan) on public.hyper hyper_1
Output: hyper_1."time", hyper_1.device, hyper_1.temp
Data node: db_dist_query_1
Chunks: _dist_hyper_1_1_chunk
Remote SQL: SELECT "time", device, temp FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) ORDER BY "time" ASC NULLS LAST, device ASC NULLS LAST
-> Custom Scan (DataNodeScan) on public.hyper hyper_2
Output: hyper_2."time", hyper_2.device, hyper_2.temp
Data node: db_dist_query_2
Chunks: _dist_hyper_1_2_chunk
Remote SQL: SELECT "time", device, temp FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) ORDER BY "time" ASC NULLS LAST, device ASC NULLS LAST
-> Custom Scan (DataNodeScan) on public.hyper hyper_3
Output: hyper_3."time", hyper_3.device, hyper_3.temp
Data node: db_dist_query_3
Chunks: _dist_hyper_1_3_chunk
Remote SQL: SELECT "time", device, temp FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) ORDER BY "time" ASC NULLS LAST, device ASC NULLS LAST
(22 rows)
######### No push down on some functions
EXPLAIN (verbose, costs off)
SELECT time, device, avg(temp), custom_sum(device)
FROM hyper
WHERE time BETWEEN '2019-01-01' AND '2019-01-01 15:00'
GROUP BY 1,2
QUERY PLAN
-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
HashAggregate
Output: hyper."time", hyper.device, avg(hyper.temp), custom_sum(hyper.device)
Group Key: hyper."time", hyper.device
-> Custom Scan (AsyncAppend)
Output: hyper."time", hyper.device, hyper.temp
-> Append
-> Custom Scan (DataNodeScan) on public.hyper hyper_1
Output: hyper_1."time", hyper_1.device, hyper_1.temp
Data node: db_dist_query_1
Chunks: _dist_hyper_1_1_chunk
Remote SQL: SELECT "time", device, temp FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) ORDER BY "time" ASC NULLS LAST, device ASC NULLS LAST
-> Custom Scan (DataNodeScan) on public.hyper hyper_2
Output: hyper_2."time", hyper_2.device, hyper_2.temp
Data node: db_dist_query_2
Chunks: _dist_hyper_1_2_chunk
Remote SQL: SELECT "time", device, temp FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) ORDER BY "time" ASC NULLS LAST, device ASC NULLS LAST
-> Custom Scan (DataNodeScan) on public.hyper hyper_3
Output: hyper_3."time", hyper_3.device, hyper_3.temp
Data node: db_dist_query_3
Chunks: _dist_hyper_1_3_chunk
Remote SQL: SELECT "time", device, temp FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) ORDER BY "time" ASC NULLS LAST, device ASC NULLS LAST
(21 rows)
######### Constification and runtime push down of time-related functions
tsl_override_current_timestamptz
----------------------------------
(1 row)
QUERY PLAN
-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Custom Scan (AsyncAppend)
Output: "time", device, (avg(temp))
-> Append
-> Custom Scan (DataNodeScan)
Output: hyper."time", hyper.device, (avg(hyper.temp))
Relations: Aggregate on (public.hyper)
Data node: db_dist_query_1
Chunks: _dist_hyper_1_1_chunk
Remote SQL: SELECT "time", device, avg(temp) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) GROUP BY 1, 2
-> Custom Scan (DataNodeScan)
Output: hyper_1."time", hyper_1.device, (avg(hyper_1.temp))
Relations: Aggregate on (public.hyper)
Data node: db_dist_query_2
Chunks: _dist_hyper_1_2_chunk
Remote SQL: SELECT "time", device, avg(temp) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) GROUP BY 1, 2
-> GroupAggregate
Output: hyper_2."time", hyper_2.device, avg(hyper_2.temp)
Group Key: hyper_2."time", hyper_2.device
-> Custom Scan (DataNodeScan) on public.hyper hyper_2
Output: hyper_2."time", hyper_2.device, hyper_2.temp
Data node: db_dist_query_3
Chunks: _dist_hyper_1_3_chunk
Remote SQL: SELECT "time", device, temp FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) ORDER BY "time" ASC NULLS LAST, device ASC NULLS LAST
(23 rows)
QUERY PLAN
-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Custom Scan (AsyncAppend)
Output: "time", device, (avg(temp))
-> Append
-> Custom Scan (DataNodeScan)
Output: hyper."time", hyper.device, (avg(hyper.temp))
Relations: Aggregate on (public.hyper)
Data node: db_dist_query_1
Chunks: _dist_hyper_1_1_chunk
Remote SQL: SELECT "time", device, avg(temp) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) GROUP BY 1, 2
-> Custom Scan (DataNodeScan)
Output: hyper_1."time", hyper_1.device, (avg(hyper_1.temp))
Relations: Aggregate on (public.hyper)
Data node: db_dist_query_2
Chunks: _dist_hyper_1_2_chunk
Remote SQL: SELECT "time", device, avg(temp) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) GROUP BY 1, 2
-> GroupAggregate
Output: hyper_2."time", hyper_2.device, avg(hyper_2.temp)
Group Key: hyper_2."time", hyper_2.device
-> Custom Scan (DataNodeScan) on public.hyper hyper_2
Output: hyper_2."time", hyper_2.device, hyper_2.temp
Data node: db_dist_query_3
Chunks: _dist_hyper_1_3_chunk
Remote SQL: SELECT "time", device, temp FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) ORDER BY "time" ASC NULLS LAST, device ASC NULLS LAST
(23 rows)
tsl_override_current_timestamptz
----------------------------------
(1 row)
QUERY PLAN
-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Custom Scan (AsyncAppend)
Output: "time", device, (avg(temp))
-> Append
-> Custom Scan (DataNodeScan)
Output: hyper."time", hyper.device, (avg(hyper.temp))
Relations: Aggregate on (public.hyper)
Data node: db_dist_query_1
Chunks: _dist_hyper_1_1_chunk
Remote SQL: SELECT "time", device, avg(temp) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) GROUP BY 1, 2
-> Custom Scan (DataNodeScan)
Output: hyper_1."time", hyper_1.device, (avg(hyper_1.temp))
Relations: Aggregate on (public.hyper)
Data node: db_dist_query_2
Chunks: _dist_hyper_1_2_chunk
Remote SQL: SELECT "time", device, avg(temp) FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) GROUP BY 1, 2
-> GroupAggregate
Output: hyper_2."time", hyper_2.device, avg(hyper_2.temp)
Group Key: hyper_2."time", hyper_2.device
-> Custom Scan (DataNodeScan) on public.hyper hyper_2
Output: hyper_2."time", hyper_2.device, hyper_2.temp
Data node: db_dist_query_3
Chunks: _dist_hyper_1_3_chunk
Remote SQL: SELECT "time", device, temp FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1]) AND (("time" >= '2019-01-01 00:00:00-08'::timestamp with time zone)) AND (("time" <= '2019-01-01 15:00:00-08'::timestamp with time zone)) ORDER BY "time" ASC NULLS LAST, device ASC NULLS LAST
(23 rows)
######### LIMIT push down cases
EXPLAIN (verbose, costs off)
SELECT time, device
FROM hyper
LIMIT 10
QUERY PLAN
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Limit
Output: hyper."time", hyper.device
-> Custom Scan (AsyncAppend)
Output: hyper."time", hyper.device
-> Append
-> Custom Scan (DataNodeScan) on public.hyper hyper_1
Output: hyper_1."time", hyper_1.device
Data node: db_dist_query_1
Chunks: _dist_hyper_1_1_chunk, _dist_hyper_1_4_chunk, _dist_hyper_1_8_chunk, _dist_hyper_1_12_chunk, _dist_hyper_1_13_chunk, _dist_hyper_1_15_chunk, _dist_hyper_1_17_chunk
Remote SQL: SELECT "time", device FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1, 2, 3, 4, 5, 6, 7]) LIMIT 10
-> Custom Scan (DataNodeScan) on public.hyper hyper_2
Output: hyper_2."time", hyper_2.device
Data node: db_dist_query_2
Chunks: _dist_hyper_1_2_chunk, _dist_hyper_1_5_chunk, _dist_hyper_1_7_chunk, _dist_hyper_1_9_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_14_chunk, _dist_hyper_1_18_chunk
Remote SQL: SELECT "time", device FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1, 2, 3, 4, 5, 6, 7]) LIMIT 10
-> Custom Scan (DataNodeScan) on public.hyper hyper_3
Output: hyper_3."time", hyper_3.device
Data node: db_dist_query_3
Chunks: _dist_hyper_1_3_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_10_chunk, _dist_hyper_1_16_chunk
Remote SQL: SELECT "time", device FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1, 2, 3, 4]) LIMIT 10
(20 rows)
######### LIMIT push down cases
EXPLAIN (verbose, costs off)
SELECT time, device
FROM hyper
LIMIT 5
OFFSET 5
QUERY PLAN
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Limit
Output: hyper."time", hyper.device
-> Custom Scan (AsyncAppend)
Output: hyper."time", hyper.device
-> Append
-> Custom Scan (DataNodeScan) on public.hyper hyper_1
Output: hyper_1."time", hyper_1.device
Data node: db_dist_query_1
Chunks: _dist_hyper_1_1_chunk, _dist_hyper_1_4_chunk, _dist_hyper_1_8_chunk, _dist_hyper_1_12_chunk, _dist_hyper_1_13_chunk, _dist_hyper_1_15_chunk, _dist_hyper_1_17_chunk
Remote SQL: SELECT "time", device FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1, 2, 3, 4, 5, 6, 7]) LIMIT 10
-> Custom Scan (DataNodeScan) on public.hyper hyper_2
Output: hyper_2."time", hyper_2.device
Data node: db_dist_query_2
Chunks: _dist_hyper_1_2_chunk, _dist_hyper_1_5_chunk, _dist_hyper_1_7_chunk, _dist_hyper_1_9_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_14_chunk, _dist_hyper_1_18_chunk
Remote SQL: SELECT "time", device FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1, 2, 3, 4, 5, 6, 7]) LIMIT 10
-> Custom Scan (DataNodeScan) on public.hyper hyper_3
Output: hyper_3."time", hyper_3.device
Data node: db_dist_query_3
Chunks: _dist_hyper_1_3_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_10_chunk, _dist_hyper_1_16_chunk
Remote SQL: SELECT "time", device FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1, 2, 3, 4]) LIMIT 10
(20 rows)
######### LIMIT push down cases
EXPLAIN (verbose, costs off)
SELECT time, device
FROM hyper
LIMIT 0
QUERY PLAN
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Limit
Output: hyper."time", hyper.device
-> Custom Scan (AsyncAppend)
Output: hyper."time", hyper.device
-> Append
-> Custom Scan (DataNodeScan) on public.hyper hyper_1
Output: hyper_1."time", hyper_1.device
Data node: db_dist_query_1
Chunks: _dist_hyper_1_1_chunk, _dist_hyper_1_4_chunk, _dist_hyper_1_8_chunk, _dist_hyper_1_12_chunk, _dist_hyper_1_13_chunk, _dist_hyper_1_15_chunk, _dist_hyper_1_17_chunk
Remote SQL: SELECT "time", device FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1, 2, 3, 4, 5, 6, 7]) LIMIT 1
-> Custom Scan (DataNodeScan) on public.hyper hyper_2
Output: hyper_2."time", hyper_2.device
Data node: db_dist_query_2
Chunks: _dist_hyper_1_2_chunk, _dist_hyper_1_5_chunk, _dist_hyper_1_7_chunk, _dist_hyper_1_9_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_14_chunk, _dist_hyper_1_18_chunk
Remote SQL: SELECT "time", device FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1, 2, 3, 4, 5, 6, 7]) LIMIT 1
-> Custom Scan (DataNodeScan) on public.hyper hyper_3
Output: hyper_3."time", hyper_3.device
Data node: db_dist_query_3
Chunks: _dist_hyper_1_3_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_10_chunk, _dist_hyper_1_16_chunk
Remote SQL: SELECT "time", device FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1, 2, 3, 4]) LIMIT 1
(20 rows)
######### LIMIT push down cases
EXPLAIN (verbose, costs off)
SELECT time, device
FROM hyper
LIMIT extract(year from date '2000-01-01')
QUERY PLAN
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Limit
Output: hyper."time", hyper.device
-> Custom Scan (AsyncAppend)
Output: hyper."time", hyper.device
-> Append
-> Custom Scan (DataNodeScan) on public.hyper hyper_1
Output: hyper_1."time", hyper_1.device
Data node: db_dist_query_1
Chunks: _dist_hyper_1_1_chunk, _dist_hyper_1_4_chunk, _dist_hyper_1_8_chunk, _dist_hyper_1_12_chunk, _dist_hyper_1_13_chunk, _dist_hyper_1_15_chunk, _dist_hyper_1_17_chunk
Remote SQL: SELECT "time", device FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1, 2, 3, 4, 5, 6, 7]) LIMIT 2000
-> Custom Scan (DataNodeScan) on public.hyper hyper_2
Output: hyper_2."time", hyper_2.device
Data node: db_dist_query_2
Chunks: _dist_hyper_1_2_chunk, _dist_hyper_1_5_chunk, _dist_hyper_1_7_chunk, _dist_hyper_1_9_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_14_chunk, _dist_hyper_1_18_chunk
Remote SQL: SELECT "time", device FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1, 2, 3, 4, 5, 6, 7]) LIMIT 2000
-> Custom Scan (DataNodeScan) on public.hyper hyper_3
Output: hyper_3."time", hyper_3.device
Data node: db_dist_query_3
Chunks: _dist_hyper_1_3_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_10_chunk, _dist_hyper_1_16_chunk
Remote SQL: SELECT "time", device FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1, 2, 3, 4]) LIMIT 2000
(20 rows)
######### LIMIT push down cases
EXPLAIN (verbose, costs off)
SELECT time, device
FROM hyper
LIMIT greatest(random(), 10.0)
QUERY PLAN
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Limit
Output: hyper."time", hyper.device
-> Custom Scan (AsyncAppend)
Output: hyper."time", hyper.device
-> Append
-> Custom Scan (DataNodeScan) on public.hyper hyper_1
Output: hyper_1."time", hyper_1.device
Data node: db_dist_query_1
Chunks: _dist_hyper_1_1_chunk, _dist_hyper_1_4_chunk, _dist_hyper_1_8_chunk, _dist_hyper_1_12_chunk, _dist_hyper_1_13_chunk, _dist_hyper_1_15_chunk, _dist_hyper_1_17_chunk
Remote SQL: SELECT "time", device FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1, 2, 3, 4, 5, 6, 7])
-> Custom Scan (DataNodeScan) on public.hyper hyper_2
Output: hyper_2."time", hyper_2.device
Data node: db_dist_query_2
Chunks: _dist_hyper_1_2_chunk, _dist_hyper_1_5_chunk, _dist_hyper_1_7_chunk, _dist_hyper_1_9_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_14_chunk, _dist_hyper_1_18_chunk
Remote SQL: SELECT "time", device FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1, 2, 3, 4, 5, 6, 7])
-> Custom Scan (DataNodeScan) on public.hyper hyper_3
Output: hyper_3."time", hyper_3.device
Data node: db_dist_query_3
Chunks: _dist_hyper_1_3_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_10_chunk, _dist_hyper_1_16_chunk
Remote SQL: SELECT "time", device FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1, 2, 3, 4])
(20 rows)
######### LIMIT push down cases
EXPLAIN (verbose, costs off)
SELECT time, device, avg(temp) OVER (PARTITION BY device)
FROM hyper
LIMIT 10
QUERY PLAN
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Limit
Output: hyper."time", hyper.device, (avg(hyper.temp) OVER (?))
-> WindowAgg
Output: hyper."time", hyper.device, avg(hyper.temp) OVER (?)
-> Custom Scan (AsyncAppend)
Output: hyper.device, hyper."time", hyper.temp
-> Merge Append
Sort Key: hyper_1.device
-> Result
Output: hyper_1.device, hyper_1."time", hyper_1.temp
-> Custom Scan (DataNodeScan) on public.hyper hyper_1
Output: hyper_1."time", hyper_1.device, hyper_1.temp
Data node: db_dist_query_1
Chunks: _dist_hyper_1_1_chunk, _dist_hyper_1_4_chunk, _dist_hyper_1_8_chunk, _dist_hyper_1_12_chunk, _dist_hyper_1_13_chunk, _dist_hyper_1_15_chunk, _dist_hyper_1_17_chunk
Remote SQL: SELECT "time", device, temp FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1, 2, 3, 4, 5, 6, 7]) ORDER BY device ASC NULLS LAST
-> Result
Output: hyper_2.device, hyper_2."time", hyper_2.temp
-> Custom Scan (DataNodeScan) on public.hyper hyper_2
Output: hyper_2."time", hyper_2.device, hyper_2.temp
Data node: db_dist_query_2
Chunks: _dist_hyper_1_2_chunk, _dist_hyper_1_5_chunk, _dist_hyper_1_7_chunk, _dist_hyper_1_9_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_14_chunk, _dist_hyper_1_18_chunk
Remote SQL: SELECT "time", device, temp FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1, 2, 3, 4, 5, 6, 7]) ORDER BY device ASC NULLS LAST
-> Result
Output: hyper_3.device, hyper_3."time", hyper_3.temp
-> Custom Scan (DataNodeScan) on public.hyper hyper_3
Output: hyper_3."time", hyper_3.device, hyper_3.temp
Data node: db_dist_query_3
Chunks: _dist_hyper_1_3_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_10_chunk, _dist_hyper_1_16_chunk
Remote SQL: SELECT "time", device, temp FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1, 2, 3, 4]) ORDER BY device ASC NULLS LAST
(29 rows)
######### LIMIT push down cases
EXPLAIN (verbose, costs off)
SELECT DISTINCT device, time
FROM hyper
LIMIT 10
QUERY PLAN
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Limit
Output: hyper.device, hyper."time"
-> Unique
Output: hyper.device, hyper."time"
-> Custom Scan (AsyncAppend)
Output: hyper.device, hyper."time"
-> Merge Append
Sort Key: hyper_1.device, hyper_1."time"
-> Custom Scan (DataNodeScan) on public.hyper hyper_1
Output: hyper_1.device, hyper_1."time"
Data node: db_dist_query_1
Chunks: _dist_hyper_1_1_chunk, _dist_hyper_1_4_chunk, _dist_hyper_1_8_chunk, _dist_hyper_1_12_chunk, _dist_hyper_1_13_chunk, _dist_hyper_1_15_chunk, _dist_hyper_1_17_chunk
Remote SQL: SELECT DISTINCT "time", device FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1, 2, 3, 4, 5, 6, 7]) ORDER BY device ASC NULLS LAST, "time" ASC NULLS LAST
-> Custom Scan (DataNodeScan) on public.hyper hyper_2
Output: hyper_2.device, hyper_2."time"
Data node: db_dist_query_2
Chunks: _dist_hyper_1_2_chunk, _dist_hyper_1_5_chunk, _dist_hyper_1_7_chunk, _dist_hyper_1_9_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_14_chunk, _dist_hyper_1_18_chunk
Remote SQL: SELECT DISTINCT "time", device FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1, 2, 3, 4, 5, 6, 7]) ORDER BY device ASC NULLS LAST, "time" ASC NULLS LAST
-> Custom Scan (DataNodeScan) on public.hyper hyper_3
Output: hyper_3.device, hyper_3."time"
Data node: db_dist_query_3
Chunks: _dist_hyper_1_3_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_10_chunk, _dist_hyper_1_16_chunk
Remote SQL: SELECT DISTINCT "time", device FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1, 2, 3, 4]) ORDER BY device ASC NULLS LAST, "time" ASC NULLS LAST
(23 rows)
######### LIMIT push down cases
EXPLAIN (verbose, costs off)
SELECT DISTINCT ON (device) device, time
FROM hyper
LIMIT 10
QUERY PLAN
---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Limit
Output: hyper.device, hyper."time"
-> Unique
Output: hyper.device, hyper."time"
-> Custom Scan (AsyncAppend)
Output: hyper.device, hyper."time"
-> Merge Append
Sort Key: hyper_1.device
-> Custom Scan (DataNodeScan) on public.hyper hyper_1
Output: hyper_1.device, hyper_1."time"
Data node: db_dist_query_1
Chunks: _dist_hyper_1_1_chunk, _dist_hyper_1_4_chunk, _dist_hyper_1_8_chunk, _dist_hyper_1_12_chunk, _dist_hyper_1_13_chunk, _dist_hyper_1_15_chunk, _dist_hyper_1_17_chunk
Remote SQL: SELECT DISTINCT ON (device) "time", device FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1, 2, 3, 4, 5, 6, 7]) ORDER BY device ASC NULLS LAST
-> Custom Scan (DataNodeScan) on public.hyper hyper_2
Output: hyper_2.device, hyper_2."time"
Data node: db_dist_query_2
Chunks: _dist_hyper_1_2_chunk, _dist_hyper_1_5_chunk, _dist_hyper_1_7_chunk, _dist_hyper_1_9_chunk, _dist_hyper_1_11_chunk, _dist_hyper_1_14_chunk, _dist_hyper_1_18_chunk
Remote SQL: SELECT DISTINCT ON (device) "time", device FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1, 2, 3, 4, 5, 6, 7]) ORDER BY device ASC NULLS LAST
-> Custom Scan (DataNodeScan) on public.hyper hyper_3
Output: hyper_3.device, hyper_3."time"
Data node: db_dist_query_3
Chunks: _dist_hyper_1_3_chunk, _dist_hyper_1_6_chunk, _dist_hyper_1_10_chunk, _dist_hyper_1_16_chunk
Remote SQL: SELECT DISTINCT ON (device) "time", device FROM public.hyper WHERE _timescaledb_internal.chunks_in(public.hyper.*, ARRAY[1, 2, 3, 4]) ORDER BY device ASC NULLS LAST
(23 rows)