Chetan Suttraway wrote:
On Fri, Mar 25, 2011 at 12:05 PM, Adarsh
Sharma <adarsh.sharma@xxxxxxxxxx>
wrote:
Dear
all,
Today I got to run a query internally from my application by more than
10 connections.
But The query performed very badly. A the data size of tables are as :
pdc_uima=# select pg_size_pretty(pg_total_relation_size('clause2'));
pg_size_pretty
----------------
5858 MB
(1 row)
pdc_uima=# select pg_size_pretty(pg_total_relation_size('svo2'));
pg_size_pretty
----------------
4719 MB
(1 row)
I explain the query as after making the indexes as :
pdc_uima=# explain select c.clause, s.* from clause2 c, svo2 s where
c.clause_id=s.clause_id and s.doc_id=c.source_id and c.
pdc_uima-# sentence_id=s.sentence_id ;
QUERY PLAN
--------------------------------------------------------------------------------------------------------------
Merge Join (cost=5673831.05..34033959.87 rows=167324179 width=2053)
Merge Cond: ((s.clause_id = c.clause_id) AND (s.doc_id = c.source_id)
AND (s.sentence_id = c.sentence_id))
-> Index Scan using idx_svo2 on svo2 s (cost=0.00..24489343.65
rows=27471560 width=1993)
-> Materialize (cost=5673828.74..6071992.29 rows=31853084
width=72)
-> Sort (cost=5673828.74..5753461.45 rows=31853084 width=72)
Sort Key: c.clause_id, c.source_id, c.sentence_id
-> Seq Scan on clause2 c (cost=0.00..770951.84
rows=31853084 width=72)
Indexes are :
CREATE INDEX idx_clause ON clause2 USING btree (clause_id,
source_id, sentence_id);
CREATE INDEX idx_svo2 ON svo2 USING btree (clause_id, doc_id,
sentence_id);
I don't know why it not uses the index scan for clause2 table.
In this case, there are no predicates or filters on individual table.
(maybe something like c.source_id=10)
so either of the 2 tables will have to go for simple scan.
Are you expecting seq. scan on svo2 and index scan on clause2?
As per the size consideration and the number of rows, I think index
scan on clause2 is better.
Your constraint is valid but I need to perform this query faster.
What is the reason behind the seq scan of clause2.
Regards,
Adarsh
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