why do you need tsvector @@ q ? Much better to use tsquery = tsqueryexplain analyze
select * from test.test_tsq
where to_tsvector('400000x400000') @@ q
test=# explain analyze select * from test_tsq where q = '400000x400000'::tsque>
QUERY PLAN
-----------------------------------------------------------------------------------------------------------
Seq Scan on test_tsq (cost=0.00..16667.01 rows=1 width=38) (actual time=129.208..341.111 rows=1 loops=1)
Filter: (q = '''400000x400000'''::tsquery)
Total runtime: 341.134 ms
(3 rows)
M-mmm... Seems your understood me incorrectly.
I have to find NOT queries which are exactly equal to another query, BUT queries which MATCH the GIVEN document. '400000x400000' was a sample only, in real cases it will be 1-2K document.
Here is a more realistic sample:
explain analyze
select * from test.test_tsq
where to_tsvector('
Here is a real document text. It may be long, 1-2K.
In this sample it contains a lexem "400000x400000", so there is a tsquery
in test_tsq.q which matches this document. I need to find all such queries fast.
Of course, in real cases the document text is unpredictable.
') @@ q
I have to find NOT queries which are exactly equal to another query, BUT queries which MATCH the GIVEN document. '400000x400000' was a sample only, in real cases it will be 1-2K document.
Here is a more realistic sample:
explain analyze
select * from test.test_tsq
where to_tsvector('
Here is a real document text. It may be long, 1-2K.
In this sample it contains a lexem "400000x400000", so there is a tsquery
in test_tsq.q which matches this document. I need to find all such queries fast.
Of course, in real cases the document text is unpredictable.
') @@ q
'800' is the number of estimated rows, which is not good, since you got only 1 row.QUERY PLAN
Seq Scan on test_tsq (cost=0.00..17477.01 rows=800 width=36) (actual
time=68.698..181.458 rows=1 loops=1)
Filter: ('''400000x400000'':1'::tsvector @@ q)
Total runtime: 181.484 ms
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