Віталій Тимчишин wrote:
Hello.
I have a query that performs very poor because there is a limit on
join column that is not applied to other columns:
select * from company this_ left outer join company_tag this_1_ on
this_.id=this_1_.company_id left outer join company_measures
companymea2_ on this_.id=companymea2_.company_id left outer join
company_descr ces3_ on this_.id=ces3_.company_id where this_1_.tag_id
= 7 and this_.id>50000000
and this_1_.company_id>50000000
order by this_.id asc limit 1000;
(plan1.txt)
Total runtime: 7794.692 ms
At the same time if I apply the limit (>50000000) to other columns in
query itself it works like a charm:
select * from company this_ left outer join company_tag this_1_ on
this_.id=this_1_.company_id left outer join company_measures
companymea2_ on this_.id=companymea2_.company_id left outer join
company_descr ces3_ on this_.id=ces3_.company_id where this_1_.tag_id
= 7 and this_.id>50000000
and this_1_.company_id>50000000
and companymea2_.company_id>50000000 and ces3_.company_id>50000000
order by this_.id asc limit 1000;
(plan2.txt)
Total runtime: 27.547 ms
I've thought and someone in this list've told me that this should be
done automatically.
Yes, if you have in a query a=b and b=c, then the optimizer figures out
that a=c as well. (a,b and c are then member of the same equivalence class).
However both queries are not the same, since the joins you're using are
outer joins. In the first it's possible that records are returned for
company records with no matching ces3_ records, the ces3_ records is
null in that case. In the second query no NULL ces3_ information may be
returned.
Another thing is it seems that the number of rows guessed is far off
from the actual number of rows, is the number 5000000 artificial or are
you're statistics old or too small histogram/mcv's?
regards,
Yeb Havinga
--
Sent via pgsql-performance mailing list (pgsql-performance@postgresql.org)
To make changes to your subscription:
http://www.postgresql.org/mailpref/pgsql-performance
