On 03-03-14 19:24, Eli Naeher wrote:
Hello,
I have two versions of essentially the same query; one using nested
joins, the other using subselects. The version using the subselect is
roughly an order of magnitude faster (~70ms on my box and data vs
~900ms for the nested joins). Of course the obvious answer here is
just to use the faster version, but I'd like to understand why the
other version is so slow. These queries are automatically generated by
our code and I'd like to feel more informed when deciding what style
of query it should be generating (and to know whether there is a way
to write the nested-join queries that will more closely approach the
performance of the subselect).
(The table aliasing is an artifact of the code that is generating this
query--I assume there is no big performance impact there, but perhaps
that assumption is mistaken.)
The join version:
(SELECT DISTINCT resource_type_1.*
FROM resource_type AS resource_type_1
LEFT JOIN group_authorization AS group_authorization_2
INNER JOIN group_member AS group_member_4
ON ( ( group_authorization_2.person_oid =
group_member_4.person_oid )
AND ( group_authorization_2.group_oid =
group_member_4.group_oid ) )
INNER JOIN wco_group AS group_5
ON ( group_authorization_2.group_oid =
group_5.obj_oid )
ON ( resource_type_1.obj_oid =
group_authorization_2.rtype_oid )
WHERE ( ( ( ( ( group_5.end_date IS NULL )
OR ( group_5.end_date >=
'2014-03-03T18:08:23.543001Z' ) )
AND ( ( group_member_4.expire IS NULL )
OR ( group_member_4.expire >=
'2014-03-03T18:08:23.543001Z'
) )
AND ( ( group_authorization_2.expire IS NULL )
OR ( group_authorization_2.expire >=
'2014-03-03T18:08:23.543001Z'
)
)
)
AND ( group_authorization_2.person_oid = 1 ) )
OR ( resource_type_1.authorized = false ) ))
(explain (analyze, buffers) output is at http://explain.depesz.com/s/wPZL)
The subselect version:
(SELECT DISTINCT resource_type_1.*
FROM resource_type AS resource_type_1
WHERE ( ( resource_type_1.authorized = false )
OR ( resource_type_1.obj_oid IN (SELECT rtype_oid
FROM group_authorization
INNER JOIN group_member
ON ( (
group_member.group_oid
=
group_authorization.group_oid )
AND ( group_member.person_oid =
group_authorization.person_oid ) )
INNER JOIN wco_group
ON ( group_member.group_oid = wco_group.obj_oid )
WHERE ( ( group_member.person_oid = 1 )
AND ( ( group_authorization.expire >
'2014-03-03T18:11:20.553844Z' )
OR ( group_authorization.expire IS NULL ) )
AND ( ( group_member.expire >
'2014-03-03T18:11:20.553844Z' )
OR ( group_member.expire IS NULL ) )
AND ( ( wco_group.end_date >
'2014-03-03T18:11:20.553844Z' )
OR ( wco_group.end_date IS NULL ) ) )) ) ))
(explain (analyze, buffers) output is at http://explain.depesz.com/s/70dd)
This is using Postgres 9.3.3. The table wco_group has ~5000 rows,
group_member has ~15000 rows, and group_authorization is the big one
with ~385000 rows.
I noticed that the nested join version was doing a lot of seq scans
and not using the indexes. I tried setting enable_seqscan to off to
force index use, and it was a bit slower that way, so the query
optimizer is definitely doing the right thing.
Any thoughts would be much appreciated.
Thank you,
-Eli
The explains show that the join version builds up an ever larger set of
rows before finally filtering,
while the subselect manages to reduce the number of rows to 2500 and
avoids the large set.
This may be as simple as the order in which you join, inner join's
should preferably eliminate as many rows
as possible as quickly as possible.
Also, DISTINCT on * does not help, why are you getting duplicates and
why can't you filter them out before doing the final select?
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