-- 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;