mirror of https://github.com/citusdata/citus.git
634 lines
19 KiB
PL/PgSQL
634 lines
19 KiB
PL/PgSQL
CREATE SCHEMA intermediate_result_pruning;
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SET search_path TO intermediate_result_pruning;
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SET citus.log_intermediate_results TO TRUE;
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SET citus.shard_count TO 4;
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SET citus.next_shard_id TO 1480000;
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SET citus.shard_replication_factor = 1;
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CREATE TABLE table_1 (key int, value text);
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SELECT create_distributed_table('table_1', 'key');
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CREATE TABLE table_2 (key int, value text);
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SELECT create_distributed_table('table_2', 'key');
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CREATE TABLE table_3 (key int, value text);
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SELECT create_distributed_table('table_3', 'key');
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CREATE TABLE ref_table (key int, value text);
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SELECT create_reference_table('ref_table');
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-- prevent PG 11 - PG 12 outputs to diverge
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SET citus.enable_cte_inlining TO false;
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-- load some data
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INSERT INTO table_1 VALUES (1, '1'), (2, '2'), (3, '3'), (4, '4');
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INSERT INTO table_2 VALUES (3, '3'), (4, '4'), (5, '5'), (6, '6');
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INSERT INTO table_3 VALUES (3, '3'), (4, '4'), (5, '5'), (6, '6');
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INSERT INTO ref_table VALUES (1, '1'), (2, '2'), (3, '3'), (4, '4'), (5, '5'), (6, '6');
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-- see which workers are hit for intermediate results
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SET client_min_messages TO DEBUG1;
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-- a very basic case, where the intermediate result
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-- should go to both workers
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WITH some_values_1 AS
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(SELECT key FROM table_1 WHERE value IN ('3', '4'))
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SELECT
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count(*)
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FROM
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some_values_1 JOIN table_2 USING (key);
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-- a very basic case, where the intermediate result
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-- should only go to one worker because the final query is a router
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-- we use random() to prevent postgres inline the CTE(s)
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WITH some_values_1 AS
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(SELECT key, random() FROM table_1 WHERE value IN ('3', '4'))
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SELECT
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count(*)
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FROM
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some_values_1 JOIN table_2 USING (key) WHERE table_2.key = 1;
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-- a similar query, but with a reference table now
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-- given that reference tables are replicated to all nodes
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-- we have to broadcast to all nodes
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WITH some_values_1 AS
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(SELECT key, random() FROM table_1 WHERE value IN ('3', '4'))
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SELECT
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count(*)
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FROM
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some_values_1 JOIN ref_table USING (key);
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-- a similar query as above, but this time use the CTE inside
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-- another CTE
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WITH some_values_1 AS
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(SELECT key, random() FROM table_1 WHERE value IN ('3', '4')),
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some_values_2 AS
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(SELECT key, random() FROM some_values_1)
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SELECT
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count(*)
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FROM
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some_values_2 JOIN table_2 USING (key) WHERE table_2.key = 1;
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-- the second CTE does a join with a distributed table
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-- and the final query is a router query
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WITH some_values_1 AS
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(SELECT key, random() FROM table_1 WHERE value IN ('3', '4')),
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some_values_2 AS
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(SELECT key, random() FROM some_values_1 JOIN table_2 USING (key))
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SELECT
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count(*)
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FROM
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some_values_2 JOIN table_2 USING (key) WHERE table_2.key = 3;
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-- the first CTE is used both within second CTE and the final query
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-- the second CTE does a join with a distributed table
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-- and the final query is a router query
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WITH some_values_1 AS
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(SELECT key, random() FROM table_1 WHERE value IN ('3', '4')),
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some_values_2 AS
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(SELECT key, random() FROM some_values_1 JOIN table_2 USING (key))
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SELECT
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count(*)
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FROM
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(some_values_2 JOIN table_2 USING (key)) JOIN some_values_1 USING (key) WHERE table_2.key = 3;
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-- the first CTE is used both within second CTE and the final query
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-- the second CTE does a join with a distributed table but a router query on a worker
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-- and the final query is another router query on another worker
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WITH some_values_1 AS
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(SELECT key, random() FROM table_1 WHERE value IN ('3', '4')),
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some_values_2 AS
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(SELECT key, random() FROM some_values_1 JOIN table_2 USING (key) WHERE table_2.key = 1)
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SELECT
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count(*)
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FROM
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(some_values_2 JOIN table_2 USING (key)) JOIN some_values_1 USING (key) WHERE table_2.key = 3;
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-- the first CTE is used both within second CTE and the final query
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-- the second CTE does a join with a distributed table but a router query on a worker
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-- and the final query is a router query on the same worker, so the first result is only
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-- broadcasted to a single node
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WITH some_values_1 AS
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(SELECT key, random() FROM table_1 WHERE value IN ('3', '4')),
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some_values_2 AS
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(SELECT key, random() FROM some_values_1 JOIN table_2 USING (key) WHERE table_2.key = 1)
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SELECT
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count(*)
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FROM
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(some_values_2 JOIN table_2 USING (key)) JOIN some_values_1 USING (key) WHERE table_2.key = 1;
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-- the same query with the above, but the final query is hitting all shards
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WITH some_values_1 AS
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(SELECT key, random() FROM table_1 WHERE value IN ('3', '4')),
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some_values_2 AS
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(SELECT key, random() FROM some_values_1 JOIN table_2 USING (key))
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SELECT
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count(*)
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FROM
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(some_values_2 JOIN table_2 USING (key)) JOIN some_values_1 USING (key) WHERE table_2.key != 3;
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-- even if we add a filter on the first query and make it a router query,
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-- the first intermediate result still hits all workers because of the final
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-- join is hitting all workers
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WITH some_values_1 AS
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(SELECT key, random() FROM table_1 WHERE value IN ('3', '4')),
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some_values_2 AS
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(SELECT key, random() FROM some_values_1 JOIN table_2 USING (key) WHERE table_2.key = 3)
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SELECT
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count(*)
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FROM
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(some_values_2 JOIN table_2 USING (key)) JOIN some_values_1 USING (key) WHERE table_2.key != 3;
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-- the reference table is joined with a distributed table and an intermediate
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-- result, but the distributed table hits all shards, so the intermediate
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-- result is sent to all nodes
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WITH some_values_1 AS
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(SELECT key, random() FROM ref_table WHERE value IN ('3', '4'))
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SELECT
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count(*)
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FROM
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(some_values_1 JOIN ref_table USING (key)) JOIN table_2 USING (key);
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-- similar query as above, but this time the whole query is a router
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-- query, so no intermediate results
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WITH some_values_1 AS
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(SELECT key, random() FROM ref_table WHERE value IN ('3', '4'))
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SELECT
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count(*)
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FROM
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(some_values_1 JOIN ref_table USING (key)) JOIN table_2 USING (key) WHERE table_2.key = 1;
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-- now, the second CTE has a single shard join with a distributed table
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-- so the first CTE should only be broadcasted to that node
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-- since the final query doesn't have a join, it should simply be broadcasted
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-- to one node
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WITH some_values_1 AS
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(SELECT key, random() FROM table_1 WHERE value IN ('3', '4')),
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some_values_2 AS
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(SELECT key, random() FROM some_values_1 JOIN table_2 USING (key) WHERE key = 1)
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SELECT
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count(*)
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FROM
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some_values_2;
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-- the same query inlined inside a CTE, and the final query has a
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-- join with a distributed table
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WITH top_cte as (
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WITH some_values_1 AS
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(SELECT key, random() FROM table_1 WHERE value IN ('3', '4')),
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some_values_2 AS
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(SELECT key, random() FROM some_values_1 JOIN table_2 USING (key) WHERE key = 1)
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SELECT
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DISTINCT key
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FROM
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some_values_2
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)
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SELECT
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count(*)
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FROM
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top_cte JOIN table_2 USING (key);
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-- very much the same query, but this time the top query is also a router query
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-- on a single worker, so all intermediate results only hit a single node
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WITH top_cte as (
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WITH some_values_1 AS
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(SELECT key, random() FROM table_1 WHERE value IN ('3', '4')),
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some_values_2 AS
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(SELECT key, random() FROM some_values_1 JOIN table_2 USING (key) WHERE key = 1)
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SELECT
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DISTINCT key
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FROM
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some_values_2
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)
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SELECT
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count(*)
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FROM
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top_cte JOIN table_2 USING (key) WHERE table_2.key = 2;
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-- some_values_1 is first used by a single shard-query, and than with a multi-shard
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-- CTE, finally a cartesian product join
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WITH some_values_1 AS
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(SELECT key, random() FROM table_1 WHERE value IN ('3', '4')),
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some_values_2 AS
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(SELECT key, random() FROM some_values_1 JOIN table_2 USING (key) WHERE key = 1),
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some_values_3 AS
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(SELECT key FROM (some_values_2 JOIN table_2 USING (key)) JOIN some_values_1 USING (key))
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SELECT * FROM some_values_3 JOIN ref_table ON (true);
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-- join on intermediate results, so should only
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-- go to a single node
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WITH some_values_1 AS
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(SELECT key, random() FROM table_1 WHERE value IN ('3', '4')),
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some_values_2 AS
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(SELECT key, random() FROM table_2 WHERE value IN ('3', '4'))
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SELECT count(*) FROM some_values_2 JOIN some_values_1 USING (key);
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-- same query with WHERE false make sure that we're not broken
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-- for such edge cases
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WITH some_values_1 AS
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(SELECT key, random() FROM table_1 WHERE value IN ('3', '4')),
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some_values_2 AS
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(SELECT key, random() FROM table_2 WHERE value IN ('3', '4'))
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SELECT count(*) FROM some_values_2 JOIN some_values_1 USING (key) WHERE false;
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-- do not use some_values_2 at all, so only 2 intermediate results are
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-- broadcasted
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WITH some_values_1 AS
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(SELECT key, random() FROM table_1 WHERE value IN ('3', '4')),
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some_values_2 AS
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(SELECT key, random() FROM some_values_1),
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some_values_3 AS
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(SELECT key, random() FROM some_values_1)
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SELECT
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count(*)
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FROM
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some_values_3;
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-- lets have some deeper intermediate results
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-- the inner most two results and the final query (which contains only intermediate results)
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-- hitting single worker, others hitting all workers
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-- (see below query where all intermediate results hit a single node)
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SELECT count(*) FROM
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(
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SELECT avg(min::int) FROM
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(
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SELECT min(table_1.value) FROM
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(
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SELECT avg(value::int) as avg_ev_type FROM
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(
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SELECT max(value) as mx_val_1 FROM
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(
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SELECT avg(value::int) as avg FROM
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(
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SELECT cnt FROM
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(
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SELECT count(*) as cnt, value
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FROM table_1
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WHERE key = 1
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GROUP BY value
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) as level_1, table_1
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WHERE table_1.key = level_1.cnt AND key = 3
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) as level_2, table_2
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WHERE table_2.key = level_2.cnt AND key = 5
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GROUP BY level_2.cnt
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) as level_3, table_1
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WHERE value::numeric = level_3.avg AND key = 6
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GROUP BY level_3.avg
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) as level_4, table_2
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WHERE level_4.mx_val_1::int = table_2.key
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GROUP BY level_4.mx_val_1
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) as level_5, table_1
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WHERE level_5.avg_ev_type = table_1.key AND key > 111
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GROUP BY level_5.avg_ev_type
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) as level_6, table_1 WHERE table_1.key::int = level_6.min::int
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GROUP BY table_1.value
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) as bar;
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-- the same query where all intermediate results hits one
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-- worker because each and every query is a router query -- but on different nodes
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SELECT count(*) FROM
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(
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SELECT avg(min::int) FROM
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(
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SELECT min(table_1.value) FROM
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(
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SELECT avg(value::int) as avg_ev_type FROM
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(
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SELECT max(value) as mx_val_1 FROM
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(
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SELECT avg(value::int) as avg FROM
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(
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SELECT cnt FROM
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(
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SELECT count(*) as cnt, value
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FROM table_1
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WHERE key = 1
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GROUP BY value
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) as level_1, table_1
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WHERE table_1.key = level_1.cnt AND key = 3
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) as level_2, table_2
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WHERE table_2.key = level_2.cnt AND key = 5
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GROUP BY level_2.cnt
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) as level_3, table_1
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WHERE value::numeric = level_3.avg AND key = 6
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GROUP BY level_3.avg
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) as level_4, table_2
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WHERE level_4.mx_val_1::int = table_2.key AND table_2.key = 1
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GROUP BY level_4.mx_val_1
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) as level_5, table_1
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WHERE level_5.avg_ev_type = table_1.key AND key = 111
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GROUP BY level_5.avg_ev_type
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) as level_6, table_1
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WHERE table_1.key::int = level_6.min::int AND table_1.key = 4
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GROUP BY table_1.value
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) as bar;
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-- sanity checks for set operations
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-- the intermediate results should just hit a single worker
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(SELECT key FROM table_1 WHERE key = 1)
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INTERSECT
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(SELECT key FROM table_1 WHERE key = 2);
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-- the intermediate results should just hit a single worker
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WITH cte_1 AS
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(
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(SELECT key FROM table_1 WHERE key = 1)
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INTERSECT
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(SELECT key FROM table_1 WHERE key = 2)
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),
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cte_2 AS
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(
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(SELECT key FROM table_1 WHERE key = 3)
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INTERSECT
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(SELECT key FROM table_1 WHERE key = 4)
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)
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SELECT * FROM cte_1
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UNION
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SELECT * FROM cte_2;
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-- one final test with SET operations, where
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-- we join the results with distributed tables
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-- so cte_1 should hit all workers, but still the
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-- others should hit single worker each
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WITH cte_1 AS
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(
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(SELECT key FROM table_1 WHERE key = 1)
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INTERSECT
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(SELECT key FROM table_1 WHERE key = 2)
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),
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cte_2 AS
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(
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SELECT count(*) FROM table_1 JOIN cte_1 USING (key)
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)
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SELECT * FROM cte_2;
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-- sanity checks for non-colocated subquery joins
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-- the recursively planned subquery (bar) should hit all
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-- nodes
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SELECT
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count(*)
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FROM
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(SELECT key, random() FROM table_1) as foo,
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(SELECT key, random() FROM table_2) as bar
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WHERE
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foo.key != bar.key;
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-- the recursively planned subquery (bar) should hit one
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-- node because foo goes to a single node
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SELECT
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count(*)
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FROM
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(SELECT key, random() FROM table_1 WHERE key = 1) as foo,
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(SELECT key, random() FROM table_2) as bar
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WHERE
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foo.key != bar.key;
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-- sanity checks for modification queries
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-- select_data goes to a single node, because it is used in another subquery
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-- raw_data is also the final router query, so hits a single shard
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-- however, the subquery in WHERE clause of the DELETE query is broadcasted to all
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-- nodes
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BEGIN;
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WITH select_data AS (
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SELECT * FROM table_1
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),
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raw_data AS (
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DELETE FROM table_2 WHERE key >= (SELECT min(key) FROM select_data WHERE key > 1) RETURNING *
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)
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SELECT * FROM raw_data;
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ROLLBACK;
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-- select_data goes to a single node, because it is used in another subquery
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-- raw_data is also the final router query, so hits a single shard
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-- however, the subquery in WHERE clause of the DELETE query is broadcasted to all
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-- nodes
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BEGIN;
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WITH select_data AS (
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SELECT * FROM table_1
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),
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raw_data AS (
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DELETE FROM table_2 WHERE value::int >= (SELECT min(key) FROM select_data WHERE key > 1 + random()) RETURNING *
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)
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SELECT * FROM raw_data;
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ROLLBACK;
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-- now, we need only two intermediate results as the subquery in WHERE clause is
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-- router plannable
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BEGIN;
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WITH select_data AS (
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SELECT * FROM table_1
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),
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raw_data AS (
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DELETE FROM table_2 WHERE value::int >= (SELECT min(key) FROM table_1 WHERE key > random()) AND key = 6 RETURNING *
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)
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SELECT * FROM raw_data;
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ROLLBACK;
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-- test with INSERT SELECT via coordinator
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-- INSERT .. SELECT via coordinator that doesn't have any intermediate results
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-- We use offset 1 to make sure the result needs to be pulled to the coordinator, offset 0 would be optimized away
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INSERT INTO table_1
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SELECT * FROM table_2 OFFSET 1;
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-- INSERT .. SELECT via coordinator which has intermediate result,
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-- and can be pruned to a single worker because the final query is on
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-- single shard via filter in key
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INSERT INTO table_1
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SELECT * FROM table_2 where value IN (SELECT value FROM table_1 WHERE random() > 1) AND key = 1;
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-- a similar query, with more complex subquery
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INSERT INTO table_1
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SELECT * FROM table_2 where key = 1 AND
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value::int IN
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(WITH cte_1 AS
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(
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(SELECT key FROM table_1 WHERE key = 1)
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INTERSECT
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(SELECT key FROM table_1 WHERE key = 2)
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),
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cte_2 AS
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(
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(SELECT key FROM table_1 WHERE key = 3)
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INTERSECT
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(SELECT key FROM table_1 WHERE key = 4)
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)
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SELECT * FROM cte_1
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UNION
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SELECT * FROM cte_2);
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-- same query, cte is on the FROM clause
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-- and this time the final query (and top-level intermediate result)
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-- hits all the shards because table_2.key != 1
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INSERT INTO table_1
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SELECT table_2.* FROM table_2,
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(WITH cte_1 AS
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(
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(SELECT key FROM table_1 WHERE key = 1)
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INTERSECT
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(SELECT key FROM table_1 WHERE key = 2)
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),
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cte_2 AS
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(
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(SELECT key FROM table_1 WHERE key = 3)
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INTERSECT
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(SELECT key FROM table_1 WHERE key = 4)
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)
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SELECT * FROM cte_1
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UNION
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SELECT * FROM cte_2
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) foo
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where table_2.key != 1 AND
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foo.key = table_2.value::int;
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-- append partitioned/heap-type
|
|
SET citus.replication_model TO statement;
|
|
|
|
-- do not print out 'building index pg_toast_xxxxx_index' messages
|
|
SET client_min_messages TO DEFAULT;
|
|
CREATE TABLE range_partitioned(range_column text, data int);
|
|
SET client_min_messages TO DEBUG1;
|
|
|
|
SELECT create_distributed_table('range_partitioned', 'range_column', 'range');
|
|
SELECT master_create_empty_shard('range_partitioned');
|
|
SELECT master_create_empty_shard('range_partitioned');
|
|
SELECT master_create_empty_shard('range_partitioned');
|
|
SELECT master_create_empty_shard('range_partitioned');
|
|
SELECT master_create_empty_shard('range_partitioned');
|
|
|
|
|
|
UPDATE pg_dist_shard SET shardminvalue = 'A', shardmaxvalue = 'D' WHERE shardid = 1480013;
|
|
UPDATE pg_dist_shard SET shardminvalue = 'D', shardmaxvalue = 'G' WHERE shardid = 1480014;
|
|
UPDATE pg_dist_shard SET shardminvalue = 'G', shardmaxvalue = 'K' WHERE shardid = 1480015;
|
|
UPDATE pg_dist_shard SET shardminvalue = 'K', shardmaxvalue = 'O' WHERE shardid = 1480016;
|
|
UPDATE pg_dist_shard SET shardminvalue = 'O', shardmaxvalue = 'Z' WHERE shardid = 1480017;
|
|
|
|
-- final query goes to a single shard
|
|
SELECT
|
|
count(*)
|
|
FROM
|
|
range_partitioned
|
|
WHERE
|
|
range_column = 'A' AND
|
|
data IN (SELECT data FROM range_partitioned);
|
|
|
|
|
|
-- final query goes to three shards, so multiple workers
|
|
SELECT
|
|
count(*)
|
|
FROM
|
|
range_partitioned
|
|
WHERE
|
|
range_column >= 'A' AND range_column <= 'K' AND
|
|
data IN (SELECT data FROM range_partitioned);
|
|
|
|
-- two shards, both of which are on the first node
|
|
WITH some_data AS (
|
|
SELECT data FROM range_partitioned
|
|
)
|
|
SELECT
|
|
count(*)
|
|
FROM
|
|
range_partitioned
|
|
WHERE
|
|
range_column IN ('A', 'E') AND
|
|
range_partitioned.data IN (SELECT data FROM some_data);
|
|
|
|
|
|
-- test case for issue #3556
|
|
CREATE TABLE accounts (id text PRIMARY KEY);
|
|
CREATE TABLE stats (account_id text PRIMARY KEY, spent int);
|
|
|
|
SELECT create_distributed_table('accounts', 'id', colocate_with => 'none');
|
|
SELECT create_distributed_table('stats', 'account_id', colocate_with => 'accounts');
|
|
|
|
INSERT INTO accounts (id) VALUES ('foo');
|
|
INSERT INTO stats (account_id, spent) VALUES ('foo', 100);
|
|
|
|
SELECT *
|
|
FROM
|
|
(
|
|
WITH accounts_cte AS (
|
|
SELECT id AS account_id
|
|
FROM accounts
|
|
),
|
|
joined_stats_cte_1 AS (
|
|
SELECT spent, account_id
|
|
FROM stats
|
|
INNER JOIN accounts_cte USING (account_id)
|
|
),
|
|
joined_stats_cte_2 AS (
|
|
SELECT spent, account_id
|
|
FROM joined_stats_cte_1
|
|
INNER JOIN accounts_cte USING (account_id)
|
|
)
|
|
SELECT SUM(spent) OVER (PARTITION BY coalesce(account_id, NULL))
|
|
FROM accounts_cte
|
|
INNER JOIN joined_stats_cte_2 USING (account_id)
|
|
) inner_query;
|
|
|
|
-- confirm that the pruning works well when using round-robin as well
|
|
SET citus.task_assignment_policy to 'round-robin';
|
|
SELECT *
|
|
FROM
|
|
(
|
|
WITH accounts_cte AS (
|
|
SELECT id AS account_id
|
|
FROM accounts
|
|
),
|
|
joined_stats_cte_1 AS (
|
|
SELECT spent, account_id
|
|
FROM stats
|
|
INNER JOIN accounts_cte USING (account_id)
|
|
),
|
|
joined_stats_cte_2 AS (
|
|
SELECT spent, account_id
|
|
FROM joined_stats_cte_1
|
|
INNER JOIN accounts_cte USING (account_id)
|
|
)
|
|
SELECT SUM(spent) OVER (PARTITION BY coalesce(account_id, NULL))
|
|
FROM accounts_cte
|
|
INNER JOIN joined_stats_cte_2 USING (account_id)
|
|
) inner_query;
|
|
RESET citus.task_assignment_policy;
|
|
|
|
-- Insert..select is planned differently, make sure we have results everywhere.
|
|
-- We put the insert..select in a CTE here to prevent the CTE from being moved
|
|
-- into the select, which would follow the regular code path for select.
|
|
WITH stats AS (
|
|
SELECT count(key) m FROM table_3
|
|
),
|
|
inserts AS (
|
|
INSERT INTO table_2
|
|
SELECT key, count(*)
|
|
FROM table_1
|
|
WHERE key > (SELECT m FROM stats)
|
|
GROUP BY key
|
|
HAVING count(*) < (SELECT m FROM stats)
|
|
LIMIT 1
|
|
RETURNING *
|
|
) SELECT count(*) FROM inserts;
|
|
|
|
SET citus.task_assignment_policy to DEFAULT;
|
|
SET client_min_messages TO DEFAULT;
|
|
DROP TABLE table_1, table_2, table_3, ref_table, accounts, stats, range_partitioned;
|
|
DROP SCHEMA intermediate_result_pruning;
|
|
|