Re: Query performance changes significantly depending on limit value

2017-02-23 15:02 GMT+01:00 Rowan Seymour <rowanseymour(at)gmail(dot)com>:

> Hi Pavel. That suggestion gets me as far as LIMIT 694 with the fast plan
> then things get slow again. This is now what happens at LIMIT 695:
>
> Limit (cost=35945.78..50034.52 rows=695 width=88) (actual
> time=12852.580..12854.382 rows=695 loops=1)
> Buffers: shared hit=6 read=66689
> -> Merge Join (cost=35945.78..56176.80 rows=998 width=88) (actual
> time=12852.577..12854.271 rows=695 loops=1)
> Merge Cond: (contacts_contact.id = contacts_contactgroup_
> contacts.contact_id)
> Buffers: shared hit=6 read=66689
> -> Sort (cost=35944.53..35949.54 rows=2004 width=92) (actual
> time=12852.486..12852.577 rows=710 loops=1)
> Sort Key: contacts_contact.id
> Sort Method: quicksort Memory: 34327kB
> Buffers: shared hit=6 read=66677
> -> Hash Join (cost=6816.19..35834.63 rows=2004 width=92)
> (actual time=721.293..12591.204 rows=200412 loops=1)
> Hash Cond: (contacts_contact.id = u0.contact_id)
> Buffers: shared hit=6 read=66677
> -> Seq Scan on contacts_contact (cost=0.00..25266.00
> rows=1000000 width=88) (actual time=0.003..267.258 rows=1000000 loops=1)
> Buffers: shared hit=1 read=15265
> -> Hash (cost=6813.14..6813.14 rows=244 width=4)
> (actual time=714.373..714.373 rows=200412 loops=1)
> Buckets: 1024 Batches: 1 Memory Usage: 7046kB
> Buffers: shared hit=5 read=51412
> -> HashAggregate (cost=6810.70..6813.14
> rows=244 width=4) (actual time=561.099..644.822 rows=200412 loops=1)
> Buffers: shared hit=5 read=51412
> -> Bitmap Heap Scan on values_value u0
> (cost=60.98..6805.69 rows=2004 width=4) (actual time=75.410..364.976
> rows=200412 loops=1)
> Recheck Cond: ((contact_field_id =
> 1) AND (upper(string_value) = 'F'::text))
> Buffers: shared hit=5 read=51412
> -> Bitmap Index Scan on
> values_value_field_string_value_contact (cost=0.00..60.47 rows=2004
> width=0) (actual time=57.642..57.642 rows=200412 loops=1)
> Index Cond: ((contact_field_id
> = 1) AND (upper(string_value) = 'F'::text))
> Buffers: shared hit=5 read=765
> -> Index Only Scan Backward using contacts_contactgroup_
> contacts_contactgroup_id_0f909f73_uniq on contacts_contactgroup_contacts
> (cost=0.43..18967.29 rows=497992 width=4) (actual time=0.080..0.651
> rows=1707 loops=1)
> Index Cond: (contactgroup_id = 1)
> Heap Fetches: 0
> Buffers: shared read=12
> Total runtime: 12863.938 ms
>
> https://explain.depesz.com/s/nfw1
>
> Can you explain a bit more about what you mean about " dependency between
> contact_field_id = 1 and upper(string_value) = 'F'::text"?
>

look to related node in plan

-> Hash (cost=6813.14..6813.14 rows=244 width=4)
(actual time=714.373..714.373 rows=200412 loops=1)
Buckets: 1024 Batches: 1 Memory Usage: 7046kB
Buffers: shared hit=5 read=51412
-> HashAggregate (cost=6810.70..6813.14
rows=244 width=4) (actual time=561.099..644.822 rows=200412 loops=1)
Buffers: shared hit=5 read=51412
-> Bitmap Heap Scan on values_value u0
(cost=60.98..6805.69 rows=2004 width=4) (actual time=75.410..364.976
rows=200412 loops=1)
Recheck Cond: ((contact_field_id = 1)
AND (upper(string_value) = 'F'::text))
Buffers: shared hit=5 read=51412

There is lot of significant differences between estimation (2004) and
reality (200412) - two orders - so the plan must be suboptimal

I am looking to your schema - and it is variant on EAV table - this is
antippatern and for more then small returned rows it should be slow.

Regards

Pavel

> Btw I created the index values_value_field_string_value_contact as
>
> CREATE INDEX values_value_field_string_value_contact
> ON values_value(contact_field_id, UPPER(string_value), contact_id DESC)
> WHERE contact_field_id IS NOT NULL;
>
> I'm not sure why it needs the contact_id column but without it the planner
> picks a slow approach for even smaller LIMIT values.
>
>
> On 23 February 2017 at 15:32, Pavel Stehule <pavel(dot)stehule(at)gmail(dot)com>
> wrote:
>
>>
>>
>> 2017-02-23 14:11 GMT+01:00 Rowan Seymour <rowanseymour(at)gmail(dot)com>:
>>
>>> Hi guys
>>>
>>> I'm a bit stuck on a query that performs fantastically up to a certain
>>> limit value, after which the planner goes off in a completely different
>>> direction and performance gets dramatically worse. Am using Postgresql 9.3
>>>
>>> You can see all the relevant schemas at http://pastebin.com/PNEqw2id
>>> and in the test database there are 1,000,000 records in contacts_contact,
>>> and about half of those will match the subquery on values_value.
>>>
>>> The query in question is:
>>>
>>> SELECT "contacts_contact".* FROM "contacts_contact"
>>> INNER JOIN "contacts_contactgroup_contacts" ON ("contacts_contact"."id"
>>> = "contacts_contactgroup_contacts"."contact_id")
>>> WHERE ("contacts_contactgroup_contacts"."contactgroup_id" = 1
>>> AND "contacts_contact"."id" IN (
>>> SELECT U0."contact_id" FROM "values_value" U0 WHERE
>>> (U0."contact_field_id" = 1 AND UPPER(U0."string_value"::text) = UPPER('F'))
>>> )
>>> ) ORDER BY "contacts_contact"."id" DESC LIMIT 222;
>>>
>>> With that limit of 222, it performs like:
>>>
>>> Limit (cost=3.09..13256.36 rows=222 width=88) (actual time=0.122..3.358
>>> rows=222 loops=1)
>>> Buffers: shared hit=708 read=63
>>> -> Nested Loop (cost=3.09..59583.10 rows=998 width=88) (actual
>>> time=0.120..3.304 rows=222 loops=1)
>>> Buffers: shared hit=708 read=63
>>> -> Merge Semi Join (cost=2.65..51687.89 rows=2004 width=92)
>>> (actual time=0.103..1.968 rows=227 loops=1)
>>> Merge Cond: (contacts_contact.id = u0.contact_id)
>>> Buffers: shared hit=24 read=63
>>> -> Index Scan Backward using contacts_contact_pkey on
>>> contacts_contact (cost=0.42..41249.43 rows=1000000 width=88) (actual
>>> time=0.008..0.502 rows=1117 loops=1)
>>> Buffers: shared hit=22 read=2
>>> -> Index Scan using values_value_field_string_value_contact
>>> on values_value u0 (cost=0.43..7934.72 rows=2004 width=4) (actual
>>> time=0.086..0.857 rows=227 loops=1)
>>> Index Cond: ((contact_field_id = 1) AND
>>> (upper(string_value) = 'F'::text))
>>> Buffers: shared hit=2 read=61
>>> -> Index Only Scan using contacts_contactgroup_contacts_contactgroup_id_0f909f73_uniq
>>> on contacts_contactgroup_contacts (cost=0.43..3.93 rows=1 width=4) (actual
>>> time=0.005..0.005 rows=1 loops=227)
>>> Index Cond: ((contactgroup_id = 1) AND (contact_id =
>>> contacts_contact.id))
>>> Heap Fetches: 0
>>> Buffers: shared hit=684
>>> Total runtime: 3.488 ms
>>>
>>> https://explain.depesz.com/s/iPPJ
>>>
>>> But if increase the limit to 223 then it performs like:
>>>
>>> Limit (cost=8785.68..13306.24 rows=223 width=88) (actual
>>> time=2685.830..2686.534 rows=223 loops=1)
>>> Buffers: shared hit=767648 read=86530
>>> -> Merge Join (cost=8785.68..29016.70 rows=998 width=88) (actual
>>> time=2685.828..2686.461 rows=223 loops=1)
>>> Merge Cond: (contacts_contact.id =
>>> contacts_contactgroup_contacts.contact_id)
>>> Buffers: shared hit=767648 read=86530
>>> -> Sort (cost=8784.44..8789.45 rows=2004 width=92) (actual
>>> time=2685.742..2685.804 rows=228 loops=1)
>>> Sort Key: contacts_contact.id
>>> Sort Method: quicksort Memory: 34327kB
>>> Buffers: shared hit=767648 read=86524
>>> -> Nested Loop (cost=6811.12..8674.53 rows=2004
>>> width=92) (actual time=646.573..2417.291 rows=200412 loops=1)
>>>
>>
>> There is pretty bad estimation probably due dependency between
>> contact_field_id = 1 and upper(string_value) = 'F'::text
>>
>> The most simple solution is disable nested loop - set enable_nestloop to
>> off
>>
>> Regards
>>
>> Pavel
>>
>>
>>> Buffers: shared hit=767648 read=86524
>>> -> HashAggregate (cost=6810.70..6813.14 rows=244
>>> width=4) (actual time=646.532..766.200 rows=200412 loops=1)
>>> Buffers: shared read=51417
>>> -> Bitmap Heap Scan on values_value u0
>>> (cost=60.98..6805.69 rows=2004 width=4) (actual time=92.016..433.709
>>> rows=200412 loops=1)
>>> Recheck Cond: ((contact_field_id = 1)
>>> AND (upper(string_value) = 'F'::text))
>>> Buffers: shared read=51417
>>> -> Bitmap Index Scan on
>>> values_value_field_string_value_contact (cost=0.00..60.47 rows=2004
>>> width=0) (actual time=70.647..70.647 rows=200412 loops=1)
>>> Index Cond: ((contact_field_id =
>>> 1) AND (upper(string_value) = 'F'::text))
>>> Buffers: shared read=770
>>> -> Index Scan using contacts_contact_pkey on
>>> contacts_contact (cost=0.42..7.62 rows=1 width=88) (actual
>>> time=0.007..0.007 rows=1 loops=200412)
>>> Index Cond: (id = u0.contact_id)
>>> Buffers: shared hit=767648 read=35107
>>> -> Index Only Scan Backward using contacts_contactgroup_contacts_contactgroup_id_0f909f73_uniq
>>> on contacts_contactgroup_contacts (cost=0.43..18967.29 rows=497992
>>> width=4) (actual time=0.073..0.273 rows=550 loops=1)
>>> Index Cond: (contactgroup_id = 1)
>>> Heap Fetches: 0
>>> Buffers: shared read=6
>>> Total runtime: 2695.301 ms
>>>
>>> https://explain.depesz.com/s/gXS
>>>
>>> I've tried running ANALYZE but that actually reduced the limit at which
>>> things get worse. Any insight into the reasoning of the query planner would
>>> be much appreciated.
>>>
>>> Thanks
>>>
>>> --
>>> *Rowan Seymour* | +260 964153686 <+260%2096%204153686> | @rowanseymour
>>>
>>
>>
>
>
> --
> *Rowan Seymour* | +260 964153686 <+260%2096%204153686> | @rowanseymour
>