From 5e45211a64149b3c659b90ff2de6fa982a5a93ed Mon Sep 17 00:00:00 2001 From: Daniel Baumann Date: Sat, 4 May 2024 14:17:33 +0200 Subject: Adding upstream version 15.5. Signed-off-by: Daniel Baumann --- src/test/regress/sql/join_hash.sql | 577 +++++++++++++++++++++++++++++++++++++ 1 file changed, 577 insertions(+) create mode 100644 src/test/regress/sql/join_hash.sql (limited to 'src/test/regress/sql/join_hash.sql') diff --git a/src/test/regress/sql/join_hash.sql b/src/test/regress/sql/join_hash.sql new file mode 100644 index 0000000..e1707cd --- /dev/null +++ b/src/test/regress/sql/join_hash.sql @@ -0,0 +1,577 @@ +-- +-- exercises for the hash join code +-- + +begin; + +set local min_parallel_table_scan_size = 0; +set local parallel_setup_cost = 0; +set local enable_hashjoin = on; + +-- Extract bucket and batch counts from an explain analyze plan. In +-- general we can't make assertions about how many batches (or +-- buckets) will be required because it can vary, but we can in some +-- special cases and we can check for growth. +create or replace function find_hash(node json) +returns json language plpgsql +as +$$ +declare + x json; + child json; +begin + if node->>'Node Type' = 'Hash' then + return node; + else + for child in select json_array_elements(node->'Plans') + loop + x := find_hash(child); + if x is not null then + return x; + end if; + end loop; + return null; + end if; +end; +$$; +create or replace function hash_join_batches(query text) +returns table (original int, final int) language plpgsql +as +$$ +declare + whole_plan json; + hash_node json; +begin + for whole_plan in + execute 'explain (analyze, format ''json'') ' || query + loop + hash_node := find_hash(json_extract_path(whole_plan, '0', 'Plan')); + original := hash_node->>'Original Hash Batches'; + final := hash_node->>'Hash Batches'; + return next; + end loop; +end; +$$; + +-- Make a simple relation with well distributed keys and correctly +-- estimated size. +create table simple as + select generate_series(1, 20000) AS id, 'aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa'; +alter table simple set (parallel_workers = 2); +analyze simple; + +-- Make a relation whose size we will under-estimate. We want stats +-- to say 1000 rows, but actually there are 20,000 rows. +create table bigger_than_it_looks as + select generate_series(1, 20000) as id, 'aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa'; +alter table bigger_than_it_looks set (autovacuum_enabled = 'false'); +alter table bigger_than_it_looks set (parallel_workers = 2); +analyze bigger_than_it_looks; +update pg_class set reltuples = 1000 where relname = 'bigger_than_it_looks'; + +-- Make a relation whose size we underestimate and that also has a +-- kind of skew that breaks our batching scheme. We want stats to say +-- 2 rows, but actually there are 20,000 rows with the same key. +create table extremely_skewed (id int, t text); +alter table extremely_skewed set (autovacuum_enabled = 'false'); +alter table extremely_skewed set (parallel_workers = 2); +analyze extremely_skewed; +insert into extremely_skewed + select 42 as id, 'aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa' + from generate_series(1, 20000); +update pg_class + set reltuples = 2, relpages = pg_relation_size('extremely_skewed') / 8192 + where relname = 'extremely_skewed'; + +-- Make a relation with a couple of enormous tuples. +create table wide as select generate_series(1, 2) as id, rpad('', 320000, 'x') as t; +alter table wide set (parallel_workers = 2); + +-- The "optimal" case: the hash table fits in memory; we plan for 1 +-- batch, we stick to that number, and peak memory usage stays within +-- our work_mem budget + +-- non-parallel +savepoint settings; +set local max_parallel_workers_per_gather = 0; +set local work_mem = '4MB'; +set local hash_mem_multiplier = 1.0; +explain (costs off) + select count(*) from simple r join simple s using (id); +select count(*) from simple r join simple s using (id); +select original > 1 as initially_multibatch, final > original as increased_batches + from hash_join_batches( +$$ + select count(*) from simple r join simple s using (id); +$$); +rollback to settings; + +-- parallel with parallel-oblivious hash join +savepoint settings; +set local max_parallel_workers_per_gather = 2; +set local work_mem = '4MB'; +set local hash_mem_multiplier = 1.0; +set local enable_parallel_hash = off; +explain (costs off) + select count(*) from simple r join simple s using (id); +select count(*) from simple r join simple s using (id); +select original > 1 as initially_multibatch, final > original as increased_batches + from hash_join_batches( +$$ + select count(*) from simple r join simple s using (id); +$$); +rollback to settings; + +-- parallel with parallel-aware hash join +savepoint settings; +set local max_parallel_workers_per_gather = 2; +set local work_mem = '4MB'; +set local hash_mem_multiplier = 1.0; +set local enable_parallel_hash = on; +explain (costs off) + select count(*) from simple r join simple s using (id); +select count(*) from simple r join simple s using (id); +select original > 1 as initially_multibatch, final > original as increased_batches + from hash_join_batches( +$$ + select count(*) from simple r join simple s using (id); +$$); +rollback to settings; + +-- The "good" case: batches required, but we plan the right number; we +-- plan for some number of batches, and we stick to that number, and +-- peak memory usage says within our work_mem budget + +-- non-parallel +savepoint settings; +set local max_parallel_workers_per_gather = 0; +set local work_mem = '128kB'; +set local hash_mem_multiplier = 1.0; +explain (costs off) + select count(*) from simple r join simple s using (id); +select count(*) from simple r join simple s using (id); +select original > 1 as initially_multibatch, final > original as increased_batches + from hash_join_batches( +$$ + select count(*) from simple r join simple s using (id); +$$); +rollback to settings; + +-- parallel with parallel-oblivious hash join +savepoint settings; +set local max_parallel_workers_per_gather = 2; +set local work_mem = '128kB'; +set local hash_mem_multiplier = 1.0; +set local enable_parallel_hash = off; +explain (costs off) + select count(*) from simple r join simple s using (id); +select count(*) from simple r join simple s using (id); +select original > 1 as initially_multibatch, final > original as increased_batches + from hash_join_batches( +$$ + select count(*) from simple r join simple s using (id); +$$); +rollback to settings; + +-- parallel with parallel-aware hash join +savepoint settings; +set local max_parallel_workers_per_gather = 2; +set local work_mem = '192kB'; +set local hash_mem_multiplier = 1.0; +set local enable_parallel_hash = on; +explain (costs off) + select count(*) from simple r join simple s using (id); +select count(*) from simple r join simple s using (id); +select original > 1 as initially_multibatch, final > original as increased_batches + from hash_join_batches( +$$ + select count(*) from simple r join simple s using (id); +$$); +rollback to settings; + +-- The "bad" case: during execution we need to increase number of +-- batches; in this case we plan for 1 batch, and increase at least a +-- couple of times, and peak memory usage stays within our work_mem +-- budget + +-- non-parallel +savepoint settings; +set local max_parallel_workers_per_gather = 0; +set local work_mem = '128kB'; +set local hash_mem_multiplier = 1.0; +explain (costs off) + select count(*) FROM simple r JOIN bigger_than_it_looks s USING (id); +select count(*) FROM simple r JOIN bigger_than_it_looks s USING (id); +select original > 1 as initially_multibatch, final > original as increased_batches + from hash_join_batches( +$$ + select count(*) FROM simple r JOIN bigger_than_it_looks s USING (id); +$$); +rollback to settings; + +-- parallel with parallel-oblivious hash join +savepoint settings; +set local max_parallel_workers_per_gather = 2; +set local work_mem = '128kB'; +set local hash_mem_multiplier = 1.0; +set local enable_parallel_hash = off; +explain (costs off) + select count(*) from simple r join bigger_than_it_looks s using (id); +select count(*) from simple r join bigger_than_it_looks s using (id); +select original > 1 as initially_multibatch, final > original as increased_batches + from hash_join_batches( +$$ + select count(*) from simple r join bigger_than_it_looks s using (id); +$$); +rollback to settings; + +-- parallel with parallel-aware hash join +savepoint settings; +set local max_parallel_workers_per_gather = 1; +set local work_mem = '192kB'; +set local hash_mem_multiplier = 1.0; +set local enable_parallel_hash = on; +explain (costs off) + select count(*) from simple r join bigger_than_it_looks s using (id); +select count(*) from simple r join bigger_than_it_looks s using (id); +select original > 1 as initially_multibatch, final > original as increased_batches + from hash_join_batches( +$$ + select count(*) from simple r join bigger_than_it_looks s using (id); +$$); +rollback to settings; + +-- The "ugly" case: increasing the number of batches during execution +-- doesn't help, so stop trying to fit in work_mem and hope for the +-- best; in this case we plan for 1 batch, increases just once and +-- then stop increasing because that didn't help at all, so we blow +-- right through the work_mem budget and hope for the best... + +-- non-parallel +savepoint settings; +set local max_parallel_workers_per_gather = 0; +set local work_mem = '128kB'; +set local hash_mem_multiplier = 1.0; +explain (costs off) + select count(*) from simple r join extremely_skewed s using (id); +select count(*) from simple r join extremely_skewed s using (id); +select * from hash_join_batches( +$$ + select count(*) from simple r join extremely_skewed s using (id); +$$); +rollback to settings; + +-- parallel with parallel-oblivious hash join +savepoint settings; +set local max_parallel_workers_per_gather = 2; +set local work_mem = '128kB'; +set local hash_mem_multiplier = 1.0; +set local enable_parallel_hash = off; +explain (costs off) + select count(*) from simple r join extremely_skewed s using (id); +select count(*) from simple r join extremely_skewed s using (id); +select * from hash_join_batches( +$$ + select count(*) from simple r join extremely_skewed s using (id); +$$); +rollback to settings; + +-- parallel with parallel-aware hash join +savepoint settings; +set local max_parallel_workers_per_gather = 1; +set local work_mem = '128kB'; +set local hash_mem_multiplier = 1.0; +set local enable_parallel_hash = on; +explain (costs off) + select count(*) from simple r join extremely_skewed s using (id); +select count(*) from simple r join extremely_skewed s using (id); +select * from hash_join_batches( +$$ + select count(*) from simple r join extremely_skewed s using (id); +$$); +rollback to settings; + +-- A couple of other hash join tests unrelated to work_mem management. + +-- Check that EXPLAIN ANALYZE has data even if the leader doesn't participate +savepoint settings; +set local max_parallel_workers_per_gather = 2; +set local work_mem = '4MB'; +set local hash_mem_multiplier = 1.0; +set local parallel_leader_participation = off; +select * from hash_join_batches( +$$ + select count(*) from simple r join simple s using (id); +$$); +rollback to settings; + +-- Exercise rescans. We'll turn off parallel_leader_participation so +-- that we can check that instrumentation comes back correctly. + +create table join_foo as select generate_series(1, 3) as id, 'xxxxx'::text as t; +alter table join_foo set (parallel_workers = 0); +create table join_bar as select generate_series(1, 10000) as id, 'xxxxx'::text as t; +alter table join_bar set (parallel_workers = 2); + +-- multi-batch with rescan, parallel-oblivious +savepoint settings; +set enable_parallel_hash = off; +set parallel_leader_participation = off; +set min_parallel_table_scan_size = 0; +set parallel_setup_cost = 0; +set parallel_tuple_cost = 0; +set max_parallel_workers_per_gather = 2; +set enable_material = off; +set enable_mergejoin = off; +set work_mem = '64kB'; +set hash_mem_multiplier = 1.0; +explain (costs off) + select count(*) from join_foo + left join (select b1.id, b1.t from join_bar b1 join join_bar b2 using (id)) ss + on join_foo.id < ss.id + 1 and join_foo.id > ss.id - 1; +select count(*) from join_foo + left join (select b1.id, b1.t from join_bar b1 join join_bar b2 using (id)) ss + on join_foo.id < ss.id + 1 and join_foo.id > ss.id - 1; +select final > 1 as multibatch + from hash_join_batches( +$$ + select count(*) from join_foo + left join (select b1.id, b1.t from join_bar b1 join join_bar b2 using (id)) ss + on join_foo.id < ss.id + 1 and join_foo.id > ss.id - 1; +$$); +rollback to settings; + +-- single-batch with rescan, parallel-oblivious +savepoint settings; +set enable_parallel_hash = off; +set parallel_leader_participation = off; +set min_parallel_table_scan_size = 0; +set parallel_setup_cost = 0; +set parallel_tuple_cost = 0; +set max_parallel_workers_per_gather = 2; +set enable_material = off; +set enable_mergejoin = off; +set work_mem = '4MB'; +set hash_mem_multiplier = 1.0; +explain (costs off) + select count(*) from join_foo + left join (select b1.id, b1.t from join_bar b1 join join_bar b2 using (id)) ss + on join_foo.id < ss.id + 1 and join_foo.id > ss.id - 1; +select count(*) from join_foo + left join (select b1.id, b1.t from join_bar b1 join join_bar b2 using (id)) ss + on join_foo.id < ss.id + 1 and join_foo.id > ss.id - 1; +select final > 1 as multibatch + from hash_join_batches( +$$ + select count(*) from join_foo + left join (select b1.id, b1.t from join_bar b1 join join_bar b2 using (id)) ss + on join_foo.id < ss.id + 1 and join_foo.id > ss.id - 1; +$$); +rollback to settings; + +-- multi-batch with rescan, parallel-aware +savepoint settings; +set enable_parallel_hash = on; +set parallel_leader_participation = off; +set min_parallel_table_scan_size = 0; +set parallel_setup_cost = 0; +set parallel_tuple_cost = 0; +set max_parallel_workers_per_gather = 2; +set enable_material = off; +set enable_mergejoin = off; +set work_mem = '64kB'; +set hash_mem_multiplier = 1.0; +explain (costs off) + select count(*) from join_foo + left join (select b1.id, b1.t from join_bar b1 join join_bar b2 using (id)) ss + on join_foo.id < ss.id + 1 and join_foo.id > ss.id - 1; +select count(*) from join_foo + left join (select b1.id, b1.t from join_bar b1 join join_bar b2 using (id)) ss + on join_foo.id < ss.id + 1 and join_foo.id > ss.id - 1; +select final > 1 as multibatch + from hash_join_batches( +$$ + select count(*) from join_foo + left join (select b1.id, b1.t from join_bar b1 join join_bar b2 using (id)) ss + on join_foo.id < ss.id + 1 and join_foo.id > ss.id - 1; +$$); +rollback to settings; + +-- single-batch with rescan, parallel-aware +savepoint settings; +set enable_parallel_hash = on; +set parallel_leader_participation = off; +set min_parallel_table_scan_size = 0; +set parallel_setup_cost = 0; +set parallel_tuple_cost = 0; +set max_parallel_workers_per_gather = 2; +set enable_material = off; +set enable_mergejoin = off; +set work_mem = '4MB'; +set hash_mem_multiplier = 1.0; +explain (costs off) + select count(*) from join_foo + left join (select b1.id, b1.t from join_bar b1 join join_bar b2 using (id)) ss + on join_foo.id < ss.id + 1 and join_foo.id > ss.id - 1; +select count(*) from join_foo + left join (select b1.id, b1.t from join_bar b1 join join_bar b2 using (id)) ss + on join_foo.id < ss.id + 1 and join_foo.id > ss.id - 1; +select final > 1 as multibatch + from hash_join_batches( +$$ + select count(*) from join_foo + left join (select b1.id, b1.t from join_bar b1 join join_bar b2 using (id)) ss + on join_foo.id < ss.id + 1 and join_foo.id > ss.id - 1; +$$); +rollback to settings; + +-- A full outer join where every record is matched. + +-- non-parallel +savepoint settings; +set local max_parallel_workers_per_gather = 0; +explain (costs off) + select count(*) from simple r full outer join simple s using (id); +select count(*) from simple r full outer join simple s using (id); +rollback to settings; + +-- parallelism not possible with parallel-oblivious outer hash join +savepoint settings; +set local max_parallel_workers_per_gather = 2; +explain (costs off) + select count(*) from simple r full outer join simple s using (id); +select count(*) from simple r full outer join simple s using (id); +rollback to settings; + +-- An full outer join where every record is not matched. + +-- non-parallel +savepoint settings; +set local max_parallel_workers_per_gather = 0; +explain (costs off) + select count(*) from simple r full outer join simple s on (r.id = 0 - s.id); +select count(*) from simple r full outer join simple s on (r.id = 0 - s.id); +rollback to settings; + +-- parallelism not possible with parallel-oblivious outer hash join +savepoint settings; +set local max_parallel_workers_per_gather = 2; +explain (costs off) + select count(*) from simple r full outer join simple s on (r.id = 0 - s.id); +select count(*) from simple r full outer join simple s on (r.id = 0 - s.id); +rollback to settings; + +-- exercise special code paths for huge tuples (note use of non-strict +-- expression and left join required to get the detoasted tuple into +-- the hash table) + +-- parallel with parallel-aware hash join (hits ExecParallelHashLoadTuple and +-- sts_puttuple oversized tuple cases because it's multi-batch) +savepoint settings; +set max_parallel_workers_per_gather = 2; +set enable_parallel_hash = on; +set work_mem = '128kB'; +set hash_mem_multiplier = 1.0; +explain (costs off) + select length(max(s.t)) + from wide left join (select id, coalesce(t, '') || '' as t from wide) s using (id); +select length(max(s.t)) +from wide left join (select id, coalesce(t, '') || '' as t from wide) s using (id); +select final > 1 as multibatch + from hash_join_batches( +$$ + select length(max(s.t)) + from wide left join (select id, coalesce(t, '') || '' as t from wide) s using (id); +$$); +rollback to settings; + +rollback; + + +-- Verify that hash key expressions reference the correct +-- nodes. Hashjoin's hashkeys need to reference its outer plan, Hash's +-- need to reference Hash's outer plan (which is below HashJoin's +-- inner plan). It's not trivial to verify that the references are +-- correct (we don't display the hashkeys themselves), but if the +-- hashkeys contain subplan references, those will be displayed. Force +-- subplans to appear just about everywhere. +-- +-- Bug report: +-- https://www.postgresql.org/message-id/CAPpHfdvGVegF_TKKRiBrSmatJL2dR9uwFCuR%2BteQ_8tEXU8mxg%40mail.gmail.com +-- +BEGIN; +SET LOCAL enable_sort = OFF; -- avoid mergejoins +SET LOCAL from_collapse_limit = 1; -- allows easy changing of join order + +CREATE TABLE hjtest_1 (a text, b int, id int, c bool); +CREATE TABLE hjtest_2 (a bool, id int, b text, c int); + +INSERT INTO hjtest_1(a, b, id, c) VALUES ('text', 2, 1, false); -- matches +INSERT INTO hjtest_1(a, b, id, c) VALUES ('text', 1, 2, false); -- fails id join condition +INSERT INTO hjtest_1(a, b, id, c) VALUES ('text', 20, 1, false); -- fails < 50 +INSERT INTO hjtest_1(a, b, id, c) VALUES ('text', 1, 1, false); -- fails (SELECT hjtest_1.b * 5) = (SELECT hjtest_2.c*5) + +INSERT INTO hjtest_2(a, id, b, c) VALUES (true, 1, 'another', 2); -- matches +INSERT INTO hjtest_2(a, id, b, c) VALUES (true, 3, 'another', 7); -- fails id join condition +INSERT INTO hjtest_2(a, id, b, c) VALUES (true, 1, 'another', 90); -- fails < 55 +INSERT INTO hjtest_2(a, id, b, c) VALUES (true, 1, 'another', 3); -- fails (SELECT hjtest_1.b * 5) = (SELECT hjtest_2.c*5) +INSERT INTO hjtest_2(a, id, b, c) VALUES (true, 1, 'text', 1); -- fails hjtest_1.a <> hjtest_2.b; + +EXPLAIN (COSTS OFF, VERBOSE) +SELECT hjtest_1.a a1, hjtest_2.a a2,hjtest_1.tableoid::regclass t1, hjtest_2.tableoid::regclass t2 +FROM hjtest_1, hjtest_2 +WHERE + hjtest_1.id = (SELECT 1 WHERE hjtest_2.id = 1) + AND (SELECT hjtest_1.b * 5) = (SELECT hjtest_2.c*5) + AND (SELECT hjtest_1.b * 5) < 50 + AND (SELECT hjtest_2.c * 5) < 55 + AND hjtest_1.a <> hjtest_2.b; + +SELECT hjtest_1.a a1, hjtest_2.a a2,hjtest_1.tableoid::regclass t1, hjtest_2.tableoid::regclass t2 +FROM hjtest_1, hjtest_2 +WHERE + hjtest_1.id = (SELECT 1 WHERE hjtest_2.id = 1) + AND (SELECT hjtest_1.b * 5) = (SELECT hjtest_2.c*5) + AND (SELECT hjtest_1.b * 5) < 50 + AND (SELECT hjtest_2.c * 5) < 55 + AND hjtest_1.a <> hjtest_2.b; + +EXPLAIN (COSTS OFF, VERBOSE) +SELECT hjtest_1.a a1, hjtest_2.a a2,hjtest_1.tableoid::regclass t1, hjtest_2.tableoid::regclass t2 +FROM hjtest_2, hjtest_1 +WHERE + hjtest_1.id = (SELECT 1 WHERE hjtest_2.id = 1) + AND (SELECT hjtest_1.b * 5) = (SELECT hjtest_2.c*5) + AND (SELECT hjtest_1.b * 5) < 50 + AND (SELECT hjtest_2.c * 5) < 55 + AND hjtest_1.a <> hjtest_2.b; + +SELECT hjtest_1.a a1, hjtest_2.a a2,hjtest_1.tableoid::regclass t1, hjtest_2.tableoid::regclass t2 +FROM hjtest_2, hjtest_1 +WHERE + hjtest_1.id = (SELECT 1 WHERE hjtest_2.id = 1) + AND (SELECT hjtest_1.b * 5) = (SELECT hjtest_2.c*5) + AND (SELECT hjtest_1.b * 5) < 50 + AND (SELECT hjtest_2.c * 5) < 55 + AND hjtest_1.a <> hjtest_2.b; + +ROLLBACK; + +-- Verify that we behave sanely when the inner hash keys contain parameters +-- (that is, outer or lateral references). This situation has to defeat +-- re-use of the inner hash table across rescans. +begin; +set local enable_hashjoin = on; + +explain (costs off) +select i8.q2, ss.* from +int8_tbl i8, +lateral (select t1.fivethous, i4.f1 from tenk1 t1 join int4_tbl i4 + on t1.fivethous = i4.f1+i8.q2 order by 1,2) ss; + +select i8.q2, ss.* from +int8_tbl i8, +lateral (select t1.fivethous, i4.f1 from tenk1 t1 join int4_tbl i4 + on t1.fivethous = i4.f1+i8.q2 order by 1,2) ss; + +rollback; -- cgit v1.2.3