On Sat, Jan 24, 2015 at 10:12 PM, Pavel Stehule <pavel.steh...@gmail.com> wrote:
> Hi > > this plan looks well > > Regards > > Pavel > Here's one that's not quite as well: http://explain.depesz.com/s/SgT Joe > > 2015-01-25 6:45 GMT+01:00 Joe Van Dyk <j...@tanga.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 <j...@tanga.com> wrote: >> >>> On Sat, Jan 24, 2015 at 9:41 PM, Joe Van Dyk <j...@tanga.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 >>> >> >> >
