That query, if I add the ORDER BY and LIMIT, returns the same results. The problem is the fact that it behaves the same way regarding its speed as the original query with the index you suggested. Sometimes it takes 800ms, sometimes it takes 6s to run, how the hell can I get it to behave the same every time? After I added the index you suggested, it was fine for a while, next morning the run time exploded back to several seconds per query... and it oscillates. On Wed, Aug 21, 2019 at 2:25 PM Luís Roberto Weck <luisroberto@xxxxxxxxxxxxxxx> wrote: > > Em 21/08/2019 04:30, Barbu Paul - Gheorghe escreveu: > > I wonder how I missed that... probabily because of the "WHERE" clause > > in what I already had. > > > > I indexed by scheduler_task_executions.device_id and the new plan is > > as follows: https://explain.depesz.com/s/cQRq > > > > Can it be further improved? > > > > Limit (cost=138511.45..138519.36 rows=2 width=54) (actual > > time=598.703..618.524 rows=2 loops=1) > > Buffers: shared hit=242389 read=44098 > > -> Unique (cost=138511.45..138527.26 rows=4 width=54) (actual > > time=598.701..598.878 rows=2 loops=1) > > Buffers: shared hit=242389 read=44098 > > -> Sort (cost=138511.45..138519.36 rows=3162 width=54) > > (actual time=598.699..598.767 rows=2052 loops=1) > > Sort Key: results.attribute_id, results."timestamp" DESC > > Sort Method: quicksort Memory: 641kB > > Buffers: shared hit=242389 read=44098 > > -> Gather (cost=44082.11..138327.64 rows=3162 > > width=54) (actual time=117.548..616.456 rows=4102 loops=1) > > Workers Planned: 2 > > Workers Launched: 2 > > Buffers: shared hit=242389 read=44098 > > -> Nested Loop (cost=43082.11..137011.44 > > rows=1318 width=54) (actual time=47.436..525.664 rows=1367 loops=3) > > Buffers: shared hit=242389 read=44098 > > -> Parallel Hash Join > > (cost=43081.68..124545.34 rows=24085 width=4) (actual > > time=33.099..469.958 rows=19756 loops=3) > > Hash Cond: > > (scheduler_operation_executions.task_execution_id = > > scheduler_task_executions.id) > > Buffers: shared hit=32518 read=44098 > > -> Parallel Seq Scan on > > scheduler_operation_executions (cost=0.00..74945.82 rows=2482982 > > width=8) (actual time=8.493..245.190 rows=1986887 loops=3) > > Buffers: shared hit=6018 read=44098 > > -> Parallel Hash > > (cost=42881.33..42881.33 rows=16028 width=4) (actual > > time=23.272..23.272 rows=13558 loops=3) > > Buckets: 65536 Batches: 1 > > Memory Usage: 2112kB > > Buffers: shared hit=26416 > > -> Parallel Bitmap Heap Scan on > > scheduler_task_executions (cost=722.55..42881.33 rows=16028 width=4) > > (actual time=27.290..61.563 rows=40675 loops=1) > > Recheck Cond: (device_id = 97) > > Heap Blocks: exact=26302 > > Buffers: shared hit=26416 > > -> Bitmap Index Scan on > > scheduler_task_executions_device_id_idx (cost=0.00..712.93 rows=38467 > > width=0) (actual time=17.087..17.087 rows=40675 loops=1) > > Index Cond: (device_id = 97) > > Buffers: shared hit=114 > > -> Index Scan using > > index_operation_execution_id_asc on results (cost=0.43..0.51 rows=1 > > width=58) (actual time=0.003..0.003 rows=0 loops=59269) > > Index Cond: (operation_execution_id = > > scheduler_operation_executions.id) > > Filter: ((data IS NOT NULL) AND (data > > <> '<NullData/>'::text) AND (attribute_id = ANY ('{4,5}'::integer[])) > > AND (object_id = 1955) AND (data_access_result = 'SUCCESS'::text)) > > Rows Removed by Filter: 0 > > Buffers: shared hit=209871 > > Planning Time: 2.327 ms > > Execution Time: 618.935 ms > > > > On Tue, Aug 20, 2019 at 5:54 PM Luís Roberto Weck > > <luisroberto@xxxxxxxxxxxxxxx> wrote: > >> Em 20/08/2019 10:54, Barbu Paul - Gheorghe escreveu: > >>> Hello, > >>> I'm running "PostgreSQL 11.2, compiled by Visual C++ build 1914, > >>> 64-bit" and I have a query that runs several times per user action > >>> (9-10 times). > >>> The query takes a long time to execute, specially at first, due to > >>> cold caches I think, but the performance varies greatly during a run > >>> of the application (while applying the said action by the user several > >>> times). > >>> > >>> My tables are only getting bigger with time, not much DELETEs and even > >>> less UPDATEs as far as I can tell. > >>> > >>> Problematic query: > >>> > >>> EXPLAIN (ANALYZE,BUFFERS) > >>> SELECT DISTINCT ON (results.attribute_id) results.timestamp, > >>> results.data FROM results > >>> JOIN scheduler_operation_executions ON > >>> scheduler_operation_executions.id = results.operation_execution_id > >>> JOIN scheduler_task_executions ON scheduler_task_executions.id = > >>> scheduler_operation_executions.task_execution_id > >>> WHERE scheduler_task_executions.device_id = 97 > >>> AND results.data <> '<NullData/>' > >>> AND results.data IS NOT NULL > >>> AND results.object_id = 1955 > >>> AND results.attribute_id IN (4, 5) -- possibly a longer list here > >>> AND results.data_access_result = 'SUCCESS' > >>> ORDER BY results.attribute_id, results.timestamp DESC > >>> LIMIT 2 -- limit by the length of the attributes list > >>> > >>> In words: I want the latest (ORDER BY results.timestamp DESC) results > >>> of a device (scheduler_task_executions.device_id = 97 - hence the > >>> joins results -> scheduler_operation_executions -> > >>> scheduler_task_executions) > >>> for a given object and attributes with some additional constraints on > >>> the data column. But I only want the latest attributes for which we > >>> have results, hence the DISTINCT ON (results.attribute_id) and LIMIT. > >>> > >>> First run: https://explain.depesz.com/s/qh4C > >>> Limit (cost=157282.39..157290.29 rows=2 width=54) (actual > >>> time=44068.166..44086.970 rows=2 loops=1) > >>> Buffers: shared hit=215928 read=85139 > >>> -> Unique (cost=157282.39..157298.20 rows=4 width=54) (actual > >>> time=44068.164..44069.301 rows=2 loops=1) > >>> Buffers: shared hit=215928 read=85139 > >>> -> Sort (cost=157282.39..157290.29 rows=3162 width=54) > >>> (actual time=44068.161..44068.464 rows=2052 loops=1) > >>> Sort Key: results.attribute_id, results."timestamp" DESC > >>> Sort Method: quicksort Memory: 641kB > >>> Buffers: shared hit=215928 read=85139 > >>> -> Gather (cost=62853.04..157098.57 rows=3162 > >>> width=54) (actual time=23518.745..44076.385 rows=4102 loops=1) > >>> Workers Planned: 2 > >>> Workers Launched: 2 > >>> Buffers: shared hit=215928 read=85139 > >>> -> Nested Loop (cost=61853.04..155782.37 > >>> rows=1318 width=54) (actual time=23290.514..43832.223 rows=1367 > >>> loops=3) > >>> Buffers: shared hit=215928 read=85139 > >>> -> Parallel Hash Join > >>> (cost=61852.61..143316.27 rows=24085 width=4) (actual > >>> time=23271.275..40018.451 rows=19756 loops=3) > >>> Hash Cond: > >>> (scheduler_operation_executions.task_execution_id = > >>> scheduler_task_executions.id) > >>> Buffers: shared hit=6057 read=85139 > >>> -> Parallel Seq Scan on > >>> scheduler_operation_executions (cost=0.00..74945.82 rows=2482982 > >>> width=8) (actual time=7.575..15694.435 rows=1986887 loops=3) > >>> Buffers: shared hit=2996 read=47120 > >>> -> Parallel Hash > >>> (cost=61652.25..61652.25 rows=16029 width=4) (actual > >>> time=23253.337..23253.337 rows=13558 loops=3) > >>> Buckets: 65536 Batches: 1 > >>> Memory Usage: 2144kB > >>> Buffers: shared hit=2977 read=38019 > >>> -> Parallel Seq Scan on > >>> scheduler_task_executions (cost=0.00..61652.25 rows=16029 width=4) > >>> (actual time=25.939..23222.174 rows=13558 loops=3) > >>> Filter: (device_id = 97) > >>> Rows Removed by Filter: 1308337 > >>> Buffers: shared hit=2977 read=38019 > >>> -> Index Scan using > >>> index_operation_execution_id_asc on results (cost=0.43..0.51 rows=1 > >>> width=58) (actual time=0.191..0.191 rows=0 loops=59269) > >>> Index Cond: (operation_execution_id = > >>> scheduler_operation_executions.id) > >>> Filter: ((data IS NOT NULL) AND (data > >>> <> '<NullData/>'::text) AND (attribute_id = ANY ('{4,5}'::integer[])) > >>> AND (object_id = 1955) AND (data_access_result = 'SUCCESS'::text)) > >>> Rows Removed by Filter: 0 > >>> Buffers: shared hit=209871 > >>> Planning Time: 29.295 ms > >>> Execution Time: 44087.365 ms > >>> > >>> > >>> Second run: https://explain.depesz.com/s/uy9f > >>> Limit (cost=157282.39..157290.29 rows=2 width=54) (actual > >>> time=789.363..810.440 rows=2 loops=1) > >>> Buffers: shared hit=216312 read=84755 > >>> -> Unique (cost=157282.39..157298.20 rows=4 width=54) (actual > >>> time=789.361..789.535 rows=2 loops=1) > >>> Buffers: shared hit=216312 read=84755 > >>> -> Sort (cost=157282.39..157290.29 rows=3162 width=54) > >>> (actual time=789.361..789.418 rows=2052 loops=1) > >>> Sort Key: results.attribute_id, results."timestamp" DESC > >>> Sort Method: quicksort Memory: 641kB > >>> Buffers: shared hit=216312 read=84755 > >>> -> Gather (cost=62853.04..157098.57 rows=3162 > >>> width=54) (actual time=290.356..808.454 rows=4102 loops=1) > >>> Workers Planned: 2 > >>> Workers Launched: 2 > >>> Buffers: shared hit=216312 read=84755 > >>> -> Nested Loop (cost=61853.04..155782.37 > >>> rows=1318 width=54) (actual time=238.313..735.472 rows=1367 loops=3) > >>> Buffers: shared hit=216312 read=84755 > >>> -> Parallel Hash Join > >>> (cost=61852.61..143316.27 rows=24085 width=4) (actual > >>> time=237.966..677.975 rows=19756 loops=3) > >>> Hash Cond: > >>> (scheduler_operation_executions.task_execution_id = > >>> scheduler_task_executions.id) > >>> Buffers: shared hit=6441 read=84755 > >>> -> Parallel Seq Scan on > >>> scheduler_operation_executions (cost=0.00..74945.82 rows=2482982 > >>> width=8) (actual time=0.117..234.279 rows=1986887 loops=3) > >>> Buffers: shared hit=3188 read=46928 > >>> -> Parallel Hash > >>> (cost=61652.25..61652.25 rows=16029 width=4) (actual > >>> time=236.631..236.631 rows=13558 loops=3) > >>> Buckets: 65536 Batches: 1 > >>> Memory Usage: 2144kB > >>> Buffers: shared hit=3169 read=37827 > >>> -> Parallel Seq Scan on > >>> scheduler_task_executions (cost=0.00..61652.25 rows=16029 width=4) > >>> (actual time=0.132..232.758 rows=13558 loops=3) > >>> Filter: (device_id = 97) > >>> Rows Removed by Filter: 1308337 > >>> Buffers: shared hit=3169 read=37827 > >>> -> Index Scan using > >>> index_operation_execution_id_asc on results (cost=0.43..0.51 rows=1 > >>> width=58) (actual time=0.003..0.003 rows=0 loops=59269) > >>> Index Cond: (operation_execution_id = > >>> scheduler_operation_executions.id) > >>> Filter: ((data IS NOT NULL) AND (data > >>> <> '<NullData/>'::text) AND (attribute_id = ANY ('{4,5}'::integer[])) > >>> AND (object_id = 1955) AND (data_access_result = 'SUCCESS'::text)) > >>> Rows Removed by Filter: 0 > >>> Buffers: shared hit=209871 > >>> Planning Time: 1.787 ms > >>> Execution Time: 810.634 ms > >>> > >>> You can see that the second run takes less than one second to run... > >>> which is 43 seconds better than the first try, just by re-running the > >>> query. > >>> Other runs take maybe 1s, 3s, still a long time. > >>> > >>> How can I improve it to be consistently fast (is it possible to get to > >>> several milliseconds?)? > >>> What I don't really understand is why the nested loop has 3 loops > >>> (three joined tables)? > >>> And why does the first index scan indicate ~60k loops? And does it > >>> really work? It doesn't seem to filter out any rows. > >>> > >>> Should I add an index only on (attribute_id, object_id)? And maybe > >>> data_access_result? > >>> Does it make sens to add it on a text column (results.data)? > >>> > >>> My tables: > >>> https://gist.githubusercontent.com/paulbarbu/0d36271d710349d8fb6102d9a466bb54/raw/7a6946ba7c2adec5b87ed90f343f1aff37432d21/gistfile1.txt > >>> > >>> As you can see from the gist the foreign keys are indexed. Other > >>> indices were added to speed up other queries. > >>> Other relevant information (my tables have 3+ millions of rows, not > >>> very big I think?), additional info with regards to size also included > >>> below. > >>> This query has poor performance on two PCs (both running off of HDDs) > >>> so I think it has more to do with my indices and query than Postgres > >>> config & hardware, will post those if necessary. > >>> > >>> > >>> Size info: > >>> SELECT relname, relpages, reltuples, relallvisible, relkind, relnatts, > >>> relhassubclass, reloptions, pg_table_size(oid) FROM pg_class WHERE > >>> relname IN ('results', 'scheduler_operation_executions', > >>> 'scheduler_task_executions'); > >>> -[ RECORD 1 ]--+------------------------------- > >>> relname | results > >>> relpages | 65922 > >>> reltuples | 3.17104e+06 > >>> relallvisible | 65922 > >>> relkind | r > >>> relnatts | 9 > >>> relhassubclass | f > >>> reloptions | > >>> pg_table_size | 588791808 > >>> -[ RECORD 2 ]--+------------------------------- > >>> relname | scheduler_operation_executions > >>> relpages | 50116 > >>> reltuples | 5.95916e+06 > >>> relallvisible | 50116 > >>> relkind | r > >>> relnatts | 8 > >>> relhassubclass | f > >>> reloptions | > >>> pg_table_size | 410697728 > >>> -[ RECORD 3 ]--+------------------------------- > >>> relname | scheduler_task_executions > >>> relpages | 40996 > >>> reltuples | 3.966e+06 > >>> relallvisible | 40996 > >>> relkind | r > >>> relnatts | 12 > >>> relhassubclass | f > >>> reloptions | > >>> pg_table_size | 335970304 > >>> > >>> Thanks for your time! > >>> > >>> -- > >>> Barbu Paul - Gheorghe > >>> > >> Can you create an index on scheduler_task_executions.device_id and run > >> it again? > Can you try this query, please? Although I'm not really sure it'll give > you the same results. > > SELECT DISTINCT ON (results.attribute_id) > results.timestamp, > results.data > FROM results > WHERE results.data <> '<NullData/>' > AND results.data IS NOT NULL > AND results.object_id = 1955 > AND results.attribute_id IN (4, 5) -- possibly a longer list here > AND results.data_access_result = 'SUCCESS' > AND EXISTS (SELECT 1 > FROM scheduler_operation_executions > JOIN scheduler_task_executions ON > scheduler_task_executions.id = > scheduler_operation_executions.task_execution_id > WHERE scheduler_operation_executions.id = > results.operation_execution_id > AND scheduler_task_executions.device_id = 97) > ORDER BY results.attribute_id, results.timestamp DESC > LIMIT 2 -- limit by the length of the attributes list -- Barbu Paul - Gheorghe
