![]() Instead of using MAX(events.updated_at) we can simply sort the events in descending order by the "id" column and grab the first row. In other words, instead of this: SELECT max(events.updated_at) AS max_id FROM events LEFT OUTER JOIN projects ON projects.id = events.project_id LEFT OUTER JOIN namespaces ON namespaces.id = projects.namespace_id WHERE events.author_id IS NOT NULL AND events.project_id IN (13083); we can use this: SELECT events.updated_at AS max_id FROM events LEFT OUTER JOIN projects ON projects.id = events.project_id LEFT OUTER JOIN namespaces ON namespaces.id = projects.namespace_id WHERE events.author_id IS NOT NULL AND events.project_id IN (13083) ORDER BY events.id DESC LIMIT 1; This has the benefit that on PostgreSQL a backwards index scan can be used, which due to the "LIMIT 1" will at most process only a single row. This in turn greatly speeds up the process of grabbing the latest update time. This can be confirmed by looking at the query plans. The first query produces the following plan: Aggregate (cost=43779.84..43779.85 rows=1 width=12) (actual time=2142.462..2142.462 rows=1 loops=1) -> Index Scan using index_events_on_project_id on events (cost=0.43..43704.69 rows=30060 width=12) (actual time=0.033..2138.086 rows=32769 loops=1) Index Cond: (project_id = 13083) Filter: (author_id IS NOT NULL) Planning time: 1.248 ms Execution time: 2142.548 ms The second query in turn produces the following plan: Limit (cost=0.43..41.65 rows=1 width=16) (actual time=1.394..1.394 rows=1 loops=1) -> Index Scan Backward using events_pkey on events (cost=0.43..1238907.96 rows=30060 width=16) (actual time=1.394..1.394 rows=1 loops=1) Filter: ((author_id IS NOT NULL) AND (project_id = 13083)) Rows Removed by Filter: 2104 Planning time: 0.166 ms Execution time: 1.408 ms According to the above plans the 2nd query is around 1500 times faster. However, re-running the first query produces timings of around 80 ms, making the 2nd query "only" around 55 times faster. |
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