Hi Ilia!
On 05.09.2025 16:03, David Geier wrote:
>>> I propose an optimization: when the column datatype supports
>>> ordering(i.e., has < and >), we can sort both MCV lists and apply
>>> mege-style algorithm to detect matches. This reduces runtime from
>>> O(N^2) to O(NlogN), where N is the number of MCV entries. The patch
>>> also applies the same optimization to semi-join clauses, which show
>>> similar performance behavior.
>
> Why do you sort both lists and then merge instead of putting the smaller
> list into a hash map and then doing hash lookups (if the type is hashable)?
I've tested your and my code with the following script:
CREATE TABLE foo(col TEXT);
CREATE TABLE bar(col TEXT);
SET default_statistics_target = 10000;
-- Generate MCV values. PostgreSQL doesn't store MCVs if the table has
-- only a single value or every value has exactly the same cardinality.
DO $$
BEGIN
FOR i IN 1..10000 LOOP
FOR j IN 1..least(i, 50) LOOP
INSERT INTO foo VALUES ('aaaaaaaaaaaaaaaaaaaa' || i::TEXT);
INSERT INTO bar VALUES ('aaaaaaaaaaaaaaaaaaaa' || (i + 100000)::TEXT);
END LOOP;
END LOOP;
END;
$$;
ANALYZE foo, bar;
\timing on
EXPLAIN SELECT * FROM foo f, bar b WHERE f.col = b.col;
Results are:
- master: 433 ms
- Order+Merge: 11 ms
- Hash map: 4 ms
I've attached my draft patch.
--
David Geier
