On Sat, Aug 07, 2021 at 07:35:25PM +0000, Alex wrote: > Table "product" has a GIN index on "lexeme" column (tsvector) that is not used. > > Query that doesn't use lexeme idx: https://explain.dalibo.com/plan/BlB#plan, ~8s, ~60.000 blocks needed > > Query forced to use lexeme idx: https://explain.dalibo.com/plan/i52, ~800ms (10x less), ~15.000 blocks needed (x4 less) Could you show the table stats for product.id ? In particular its "correlation". I guess the correlation is ~1, and the 10,659 index scans on product.id are considered to be cheaper than scannning the lexeme index - since there are no correlation stats for tsvector. How large is shared_buffers ? Does the query plan improve if you increase work_mem ? Maybe you could encourage scanning in order of product_property.product. You could CLUSTER product_property_default on an index on "product" and then ANALYZE. Or you could write the query with a temp table: CREATE TEMP TABLE product_ids AS SELECT product FROM product_property WHERE "meaning" = 'B' AND "first" = 1.7179869184E10 GROUP BY 1 -- or DISTINCT, because the table is only used for EXISTS ORDER BY 1; -- to scan product in order of id ANALYZE product_ids; The index scans on product.id should be faster when you use EXISTS(SELECT 1 FROM product_ids ...), even though it didn't use the lexeme index. Maybe it would help to create stats on "first" and "meaning"; the rowcount is underestimated by 3x, which means it did several times more index scans into "product" than planned. | Bitmap Heap Scan on product_property_default product_property_default (cost=2,748.6..8,823.4 rows=6,318 width=4) (actual time=43.945..211.621 rows=21,061 loops=1) CREATE STATISTICS first_meaning ON first,meaning FROM product_property; ANALYZE product_property; > Table metdata: > relname | relpages | reltuples | relallvisible | relkind | relnatts | relhassubclass | reloptions | pg_table_size > --------------------------+----------+-----------+---------------+---------+----------+----------------+------------+--------------- > product_property_default | 8992 | 622969 | 8992 | r | 16 | f | | 73719808 > product | 49686 | 413840 | 49686 | r | 14 | f | | 493314048 > > Table stats: > frac_mcv | tablename | attname | inherited | null_frac | n_distinct | n_mcv | n_hist | correlation > ---------------+--------------------------+---------+-----------+-----------+-------------+-------+--------+------------- > | product | lexeme | f | 0 | -1 | | | > 0.99773335 | product_property_default | meaning | f | 0 | 63 | 39 | 24 | 0.19444875 > 0.6416333 | product_property_default | first | f | 0 | 2193 | 100 | 101 | -0.09763639 > 0.00023333334 | product_property_default | product | f | 0 | -0.15221785 | 1 | 101 | 0.08643274 > > > Using windows docker with wsl2.Both cases are run with cold cache.All database memory is limited to 1GB by using .wslconfig file with memory=1GB, also the docker container is limited to 1GB. > My requirement is to optimize disk access with this limited memory
