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-- Perform tests on the Memoize node.
-- The cache hits/misses/evictions from the Memoize node can vary between
-- machines. Let's just replace the number with an 'N'. In order to allow us
-- to perform validation when the measure was zero, we replace a zero value
-- with "Zero". All other numbers are replaced with 'N'.
create function explain_memoize(query text, hide_hitmiss bool) returns setof text
language plpgsql as
$$
declare
ln text;
begin
for ln in
execute format('explain (analyze, costs off, summary off, timing off) %s',
query)
loop
if hide_hitmiss = true then
ln := regexp_replace(ln, 'Hits: 0', 'Hits: Zero');
ln := regexp_replace(ln, 'Hits: \d+', 'Hits: N');
ln := regexp_replace(ln, 'Misses: 0', 'Misses: Zero');
ln := regexp_replace(ln, 'Misses: \d+', 'Misses: N');
end if;
ln := regexp_replace(ln, 'Evictions: 0', 'Evictions: Zero');
ln := regexp_replace(ln, 'Evictions: \d+', 'Evictions: N');
ln := regexp_replace(ln, 'Memory Usage: \d+', 'Memory Usage: N');
ln := regexp_replace(ln, 'Heap Fetches: \d+', 'Heap Fetches: N');
ln := regexp_replace(ln, 'loops=\d+', 'loops=N');
return next ln;
end loop;
end;
$$;
-- Ensure we get a memoize node on the inner side of the nested loop
SET enable_hashjoin TO off;
SET enable_bitmapscan TO off;
SELECT explain_memoize('
SELECT COUNT(*),AVG(t1.unique1) FROM tenk1 t1
INNER JOIN tenk1 t2 ON t1.unique1 = t2.twenty
WHERE t2.unique1 < 1000;', false);
-- And check we get the expected results.
SELECT COUNT(*),AVG(t1.unique1) FROM tenk1 t1
INNER JOIN tenk1 t2 ON t1.unique1 = t2.twenty
WHERE t2.unique1 < 1000;
-- Try with LATERAL joins
SELECT explain_memoize('
SELECT COUNT(*),AVG(t2.unique1) FROM tenk1 t1,
LATERAL (SELECT t2.unique1 FROM tenk1 t2
WHERE t1.twenty = t2.unique1 OFFSET 0) t2
WHERE t1.unique1 < 1000;', false);
-- And check we get the expected results.
SELECT COUNT(*),AVG(t2.unique1) FROM tenk1 t1,
LATERAL (SELECT t2.unique1 FROM tenk1 t2
WHERE t1.twenty = t2.unique1 OFFSET 0) t2
WHERE t1.unique1 < 1000;
SET enable_mergejoin TO off;
-- Test for varlena datatype with expr evaluation
CREATE TABLE expr_key (x numeric, t text);
INSERT INTO expr_key (x, t)
SELECT d1::numeric, d1::text FROM (
SELECT round((d / pi())::numeric, 7) AS d1 FROM generate_series(1, 20) AS d
) t;
-- duplicate rows so we get some cache hits
INSERT INTO expr_key SELECT * FROM expr_key;
CREATE INDEX expr_key_idx_x_t ON expr_key (x, t);
VACUUM ANALYZE expr_key;
-- Ensure we get we get a cache miss and hit for each of the 20 distinct values
SELECT explain_memoize('
SELECT * FROM expr_key t1 INNER JOIN expr_key t2
ON t1.x = t2.t::numeric AND t1.t::numeric = t2.x;', false);
DROP TABLE expr_key;
-- Reduce work_mem and hash_mem_multiplier so that we see some cache evictions
SET work_mem TO '64kB';
SET hash_mem_multiplier TO 1.0;
-- Ensure we get some evictions. We're unable to validate the hits and misses
-- here as the number of entries that fit in the cache at once will vary
-- between different machines.
SELECT explain_memoize('
SELECT COUNT(*),AVG(t1.unique1) FROM tenk1 t1
INNER JOIN tenk1 t2 ON t1.unique1 = t2.thousand
WHERE t2.unique1 < 1200;', true);
CREATE TABLE flt (f float);
CREATE INDEX flt_f_idx ON flt (f);
INSERT INTO flt VALUES('-0.0'::float),('+0.0'::float);
ANALYZE flt;
SET enable_seqscan TO off;
-- Ensure memoize operates in logical mode
SELECT explain_memoize('
SELECT * FROM flt f1 INNER JOIN flt f2 ON f1.f = f2.f;', false);
-- Ensure memoize operates in binary mode
SELECT explain_memoize('
SELECT * FROM flt f1 INNER JOIN flt f2 ON f1.f >= f2.f;', false);
DROP TABLE flt;
-- Exercise Memoize in binary mode with a large fixed width type and a
-- varlena type.
CREATE TABLE strtest (n name, t text);
CREATE INDEX strtest_n_idx ON strtest (n);
CREATE INDEX strtest_t_idx ON strtest (t);
INSERT INTO strtest VALUES('one','one'),('two','two'),('three',repeat(md5('three'),100));
-- duplicate rows so we get some cache hits
INSERT INTO strtest SELECT * FROM strtest;
ANALYZE strtest;
-- Ensure we get 3 hits and 3 misses
SELECT explain_memoize('
SELECT * FROM strtest s1 INNER JOIN strtest s2 ON s1.n >= s2.n;', false);
-- Ensure we get 3 hits and 3 misses
SELECT explain_memoize('
SELECT * FROM strtest s1 INNER JOIN strtest s2 ON s1.t >= s2.t;', false);
DROP TABLE strtest;
-- Ensure memoize works with partitionwise join
SET enable_partitionwise_join TO on;
CREATE TABLE prt (a int) PARTITION BY RANGE(a);
CREATE TABLE prt_p1 PARTITION OF prt FOR VALUES FROM (0) TO (10);
CREATE TABLE prt_p2 PARTITION OF prt FOR VALUES FROM (10) TO (20);
INSERT INTO prt VALUES (0), (0), (0), (0);
INSERT INTO prt VALUES (10), (10), (10), (10);
CREATE INDEX iprt_p1_a ON prt_p1 (a);
CREATE INDEX iprt_p2_a ON prt_p2 (a);
ANALYZE prt;
SELECT explain_memoize('
SELECT * FROM prt t1 INNER JOIN prt t2 ON t1.a = t2.a;', false);
DROP TABLE prt;
RESET enable_partitionwise_join;
-- Exercise Memoize code that flushes the cache when a parameter changes which
-- is not part of the cache key.
-- Ensure we get a Memoize plan
EXPLAIN (COSTS OFF)
SELECT unique1 FROM tenk1 t0
WHERE unique1 < 3
AND EXISTS (
SELECT 1 FROM tenk1 t1
INNER JOIN tenk1 t2 ON t1.unique1 = t2.hundred
WHERE t0.ten = t1.twenty AND t0.two <> t2.four OFFSET 0);
-- Ensure the above query returns the correct result
SELECT unique1 FROM tenk1 t0
WHERE unique1 < 3
AND EXISTS (
SELECT 1 FROM tenk1 t1
INNER JOIN tenk1 t2 ON t1.unique1 = t2.hundred
WHERE t0.ten = t1.twenty AND t0.two <> t2.four OFFSET 0);
RESET enable_seqscan;
RESET enable_mergejoin;
RESET work_mem;
RESET hash_mem_multiplier;
RESET enable_bitmapscan;
RESET enable_hashjoin;
-- Test parallel plans with Memoize
SET min_parallel_table_scan_size TO 0;
SET parallel_setup_cost TO 0;
SET parallel_tuple_cost TO 0;
SET max_parallel_workers_per_gather TO 2;
-- Ensure we get a parallel plan.
EXPLAIN (COSTS OFF)
SELECT COUNT(*),AVG(t2.unique1) FROM tenk1 t1,
LATERAL (SELECT t2.unique1 FROM tenk1 t2 WHERE t1.twenty = t2.unique1) t2
WHERE t1.unique1 < 1000;
-- And ensure the parallel plan gives us the correct results.
SELECT COUNT(*),AVG(t2.unique1) FROM tenk1 t1,
LATERAL (SELECT t2.unique1 FROM tenk1 t2 WHERE t1.twenty = t2.unique1) t2
WHERE t1.unique1 < 1000;
RESET max_parallel_workers_per_gather;
RESET parallel_tuple_cost;
RESET parallel_setup_cost;
RESET min_parallel_table_scan_size;
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