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83f4fcc655
"Result Cache" was never a great name for this node, but nobody managed to come up with another name that anyone liked enough. That was until David Johnston mentioned "Node Memoization", which Tom Lane revised to just "Memoize". People seem to like "Memoize", so let's do the rename. Reviewed-by: Justin Pryzby Discussion: https://postgr.es/m/20210708165145.GG1176@momjian.us Backpatch-through: 14, where Result Cache was introduced
94 lines
3.3 KiB
PL/PgSQL
94 lines
3.3 KiB
PL/PgSQL
-- Perform tests on the Memoize node.
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-- The cache hits/misses/evictions from the Memoize node can vary between
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-- machines. Let's just replace the number with an 'N'. In order to allow us
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-- to perform validation when the measure was zero, we replace a zero value
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-- with "Zero". All other numbers are replaced with 'N'.
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create function explain_memoize(query text, hide_hitmiss bool) returns setof text
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language plpgsql as
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$$
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declare
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ln text;
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begin
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for ln in
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execute format('explain (analyze, costs off, summary off, timing off) %s',
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query)
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loop
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if hide_hitmiss = true then
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ln := regexp_replace(ln, 'Hits: 0', 'Hits: Zero');
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ln := regexp_replace(ln, 'Hits: \d+', 'Hits: N');
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ln := regexp_replace(ln, 'Misses: 0', 'Misses: Zero');
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ln := regexp_replace(ln, 'Misses: \d+', 'Misses: N');
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end if;
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ln := regexp_replace(ln, 'Evictions: 0', 'Evictions: Zero');
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ln := regexp_replace(ln, 'Evictions: \d+', 'Evictions: N');
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ln := regexp_replace(ln, 'Memory Usage: \d+', 'Memory Usage: N');
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ln := regexp_replace(ln, 'Heap Fetches: \d+', 'Heap Fetches: N');
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ln := regexp_replace(ln, 'loops=\d+', 'loops=N');
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return next ln;
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end loop;
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end;
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$$;
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-- Ensure we get a memoize node on the inner side of the nested loop
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SET enable_hashjoin TO off;
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SET enable_bitmapscan TO off;
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SELECT explain_memoize('
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SELECT COUNT(*),AVG(t1.unique1) FROM tenk1 t1
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INNER JOIN tenk1 t2 ON t1.unique1 = t2.twenty
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WHERE t2.unique1 < 1000;', false);
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-- And check we get the expected results.
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SELECT COUNT(*),AVG(t1.unique1) FROM tenk1 t1
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INNER JOIN tenk1 t2 ON t1.unique1 = t2.twenty
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WHERE t2.unique1 < 1000;
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-- Try with LATERAL joins
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SELECT explain_memoize('
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SELECT COUNT(*),AVG(t2.unique1) FROM tenk1 t1,
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LATERAL (SELECT t2.unique1 FROM tenk1 t2 WHERE t1.twenty = t2.unique1) t2
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WHERE t1.unique1 < 1000;', false);
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-- And check we get the expected results.
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SELECT COUNT(*),AVG(t2.unique1) FROM tenk1 t1,
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LATERAL (SELECT t2.unique1 FROM tenk1 t2 WHERE t1.twenty = t2.unique1) t2
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WHERE t1.unique1 < 1000;
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-- Reduce work_mem so that we see some cache evictions
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SET work_mem TO '64kB';
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SET enable_mergejoin TO off;
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-- Ensure we get some evictions. We're unable to validate the hits and misses
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-- here as the number of entries that fit in the cache at once will vary
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-- between different machines.
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SELECT explain_memoize('
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SELECT COUNT(*),AVG(t1.unique1) FROM tenk1 t1
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INNER JOIN tenk1 t2 ON t1.unique1 = t2.thousand
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WHERE t2.unique1 < 1200;', true);
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RESET enable_mergejoin;
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RESET work_mem;
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RESET enable_bitmapscan;
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RESET enable_hashjoin;
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-- Test parallel plans with Memoize
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SET min_parallel_table_scan_size TO 0;
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SET parallel_setup_cost TO 0;
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SET parallel_tuple_cost TO 0;
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SET max_parallel_workers_per_gather TO 2;
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-- Ensure we get a parallel plan.
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EXPLAIN (COSTS OFF)
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SELECT COUNT(*),AVG(t2.unique1) FROM tenk1 t1,
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LATERAL (SELECT t2.unique1 FROM tenk1 t2 WHERE t1.twenty = t2.unique1) t2
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WHERE t1.unique1 < 1000;
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-- And ensure the parallel plan gives us the correct results.
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SELECT COUNT(*),AVG(t2.unique1) FROM tenk1 t1,
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LATERAL (SELECT t2.unique1 FROM tenk1 t2 WHERE t1.twenty = t2.unique1) t2
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WHERE t1.unique1 < 1000;
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RESET max_parallel_workers_per_gather;
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RESET parallel_tuple_cost;
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RESET parallel_setup_cost;
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RESET min_parallel_table_scan_size;
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