Re: Query performance

From: Pavel Stehule <pavel(dot)stehule(at)gmail(dot)com>
To: Joe Van Dyk <joe(at)tanga(dot)com>
Cc: "pgsql-performance(at)postgresql(dot)org" <pgsql-performance(at)postgresql(dot)org>
Subject: Re: Query performance
Date: 2015-01-25 08:03:27
Message-ID: CAFj8pRDm92FvgzNEE7VMqYbhijXgOy6geY-xcGkey1mM7qoq6A@mail.gmail.com
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2015-01-25 8:20 GMT+01:00 Joe Van Dyk <joe(at)tanga(dot)com>:

> On Sat, Jan 24, 2015 at 11:14 PM, Pavel Stehule <pavel(dot)stehule(at)gmail(dot)com>
> wrote:
>
>>
>>
>> 2015-01-25 7:38 GMT+01:00 Joe Van Dyk <joe(at)tanga(dot)com>:
>>
>>>
>>>
>>> On Sat, Jan 24, 2015 at 10:12 PM, Pavel Stehule <pavel(dot)stehule(at)gmail(dot)com
>>> > wrote:
>>>
>>>> Hi
>>>>
>>>> this plan looks well
>>>>
>>>> Regards
>>>>
>>>> Pavel
>>>>
>>>
>>> Here's one that's not quite as well: http://explain.depesz.com/s/SgT
>>>
>>
>> I see a possible issue
>>
>> (product_id <> '81716'::citext) .. this operation is CPU expensive and
>> maybe nonsense
>>
>> product_id should be integer -- and if it isn't - it should not be on 4M
>> rows extremly fast - mainly on citext
>>
>> try to force a opposite cast - you will safe a case insensitive text
>> comparation
>>
>> product_id::int <> 81716
>>
>
> It might not always be an integer, just happens to be so here. Should I
> try text instead? I don't have to have the case-insensitive matching.
>

text can be better

this design is unhappy, but you cannot to change ot probably

>
> Joe
>
>
>>
>> Regards
>>
>> Pavel
>>
>>
>>
>>
>>>
>>> Joe
>>>
>>>
>>>>
>>>> 2015-01-25 6:45 GMT+01:00 Joe Van Dyk <joe(at)tanga(dot)com>:
>>>>
>>>>> Oops, didn't run vacuum analyze after deleting the events. Here is
>>>>> another 'explain analyze': http://explain.depesz.com/s/AviN
>>>>>
>>>>> On Sat, Jan 24, 2015 at 9:43 PM, Joe Van Dyk <joe(at)tanga(dot)com> wrote:
>>>>>
>>>>>> On Sat, Jan 24, 2015 at 9:41 PM, Joe Van Dyk <joe(at)tanga(dot)com> wrote:
>>>>>>
>>>>>>> I have an events table that records page views and purchases (type =
>>>>>>> 'viewed' or type='purchased'). I have a query that figures out "people who
>>>>>>> bought/viewed this also bought/viewed that".
>>>>>>>
>>>>>>> It worked fine, taking about 0.1 seconds to complete, until a few
>>>>>>> hours ago when it started taking hours to complete. Vacuum/analyze didn't
>>>>>>> help. Turned out there was one session_id that had 400k rows in the
>>>>>>> system. Deleting that made the query performant again.
>>>>>>>
>>>>>>> Is there anything I can do to make the query work better in cases
>>>>>>> like that? Missing index, or better query?
>>>>>>>
>>>>>>> This is on 9.3.5.
>>>>>>>
>>>>>>> The below is reproduced at the following URL if it's not formatted
>>>>>>> correctly in the email.
>>>>>>> https://gist.githubusercontent.com/joevandyk/cb8f4afdb6c1b178c606/raw/9940bbe033ebd56d38caa46e33c1ddfd9df36eda/gistfile1.txt
>>>>>>>
>>>>>>> explain select
>>>>>>> e1.product_id,
>>>>>>> e2.site_id,
>>>>>>> e2.product_id,
>>>>>>> count(nullif(e2.type='viewed', false)) view_count,
>>>>>>> count(nullif(e2.type='purchased', false)) purchase_count
>>>>>>> from events e1
>>>>>>> join events e2 on e1.session_id = e2.session_id and e1.type = e2.type
>>>>>>> where
>>>>>>> e1.product_id = '82503' and
>>>>>>> e1.product_id != e2.product_id
>>>>>>> group by e1.product_id, e2.product_id, e2.site_id;
>>>>>>> QUERY PLAN
>>>>>>> ----------------------------------------------------------------------------------------------------------------------------
>>>>>>> GroupAggregate (cost=828395.67..945838.90 rows=22110 width=19)
>>>>>>> -> Sort (cost=828395.67..840117.89 rows=4688885 width=19)
>>>>>>> Sort Key: e1.product_id, e2.product_id, e2.site_id
>>>>>>> -> Nested Loop (cost=11.85..20371.14 rows=4688885 width=19)
>>>>>>> -> Bitmap Heap Scan on events e1 (cost=11.29..1404.31 rows=369 width=49)
>>>>>>> Recheck Cond: (product_id = '82503'::citext)
>>>>>>> -> Bitmap Index Scan on events_product_id_site_id_idx (cost=0.00..11.20 rows=369 width=0)
>>>>>>> Index Cond: (product_id = '82503'::citext)
>>>>>>> -> Index Scan using events_session_id_type_product_id_idx on events e2 (cost=0.56..51.28 rows=12 width=51)
>>>>>>> Index Cond: ((session_id = e1.session_id) AND (type = e1.type))
>>>>>>> Filter: (e1.product_id <> product_id)
>>>>>>> (11 rows)
>>>>>>>
>>>>>>> recommender_production=> \d events
>>>>>>> Table "public.events"
>>>>>>> Column | Type | Modifiers
>>>>>>> -------------+--------------------------+-----------------------------------------------------
>>>>>>> id | bigint | not null default nextval('events_id_seq'::regclass)
>>>>>>> user_id | citext |
>>>>>>> session_id | citext | not null
>>>>>>> product_id | citext | not null
>>>>>>> site_id | citext | not null
>>>>>>> type | text | not null
>>>>>>> happened_at | timestamp with time zone | not null
>>>>>>> created_at | timestamp with time zone | not null
>>>>>>> Indexes:
>>>>>>> "events_pkey" PRIMARY KEY, btree (id)
>>>>>>> "events_product_id_site_id_idx" btree (product_id, site_id)
>>>>>>> "events_session_id_type_product_id_idx" btree (session_id, type, product_id)
>>>>>>> Check constraints:
>>>>>>> "events_session_id_check" CHECK (length(session_id::text) < 255)
>>>>>>> "events_type_check" CHECK (type = ANY (ARRAY['purchased'::text, 'viewed'::text]))
>>>>>>> "events_user_id_check" CHECK (length(user_id::text) < 255)
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>> After removing the session with 400k events, I was able to do an
>>>>>> explain analyze, here is one of them:
>>>>>> http://explain.depesz.com/s/PFNk
>>>>>>
>>>>>
>>>>>
>>>>
>>>
>>
>

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