我的查询对于特定行来说很慢。 Postgres选择Seq Scan
而不是使用Index Scan
来表示某些行,我假设它实际上比使用索引更快。
以下是使用正常工作负载的索引的查询计划:http://explain.depesz.com/s/1A2o:
EXPLAIN (ANALYZE, BUFFERS) SELECT "blocks".* FROM "blocks" INNER JOIN "jobs" ON "blocks"."job_id" = "jobs"."id" WHERE "jobs"."project_id" = 1;
QUERY PLAN
--------------------------------------------------------------------------------------------------------------------------------------------
Nested Loop (cost=0.71..166.27 rows=19 width=130) (actual time=0.092..4.247 rows=2421 loops=1)
Buffers: shared hit=350
-> Index Scan using index_jobs_on_project_id on jobs (cost=0.29..18.81 rows=4 width=4) (actual time=0.044..0.099 rows=15 loops=1)
Index Cond: (project_id = 1)
Buffers: shared hit=17
-> Index Scan using index_blocks_on_job_id on blocks (cost=0.42..36.67 rows=19 width=130) (actual time=0.021..0.133 rows=161 loops=15)
Index Cond: (job_id = jobs.id)
Buffers: shared hit=333
Total runtime: 4.737 ms
(9 rows)
此处的查询计划选择对不太常规的工作负载执行顺序扫描:http://explain.depesz.com/s/cJOd:
EXPLAIN (ANALYZE, BUFFERS) SELECT "blocks".* FROM "blocks" INNER JOIN "jobs" ON "blocks"."job_id" = "jobs"."id" WHERE "jobs"."project_id" = 2;
QUERY PLAN
----------------------------------------------------------------------------------------------------------------------------------------------------
Hash Join (cost=1138.64..11236.94 rows=10421 width=130) (actual time=5.212..72.604 rows=2516 loops=1)
Hash Cond: (blocks.job_id = jobs.id)
Buffers: shared hit=5671
-> Seq Scan on blocks (cost=0.00..8478.06 rows=303206 width=130) (actual time=0.008..24.573 rows=298084 loops=1)
Buffers: shared hit=5446
-> Hash (cost=1111.79..1111.79 rows=2148 width=4) (actual time=3.346..3.346 rows=2164 loops=1)
Buckets: 1024 Batches: 1 Memory Usage: 77kB
Buffers: shared hit=225
-> Bitmap Heap Scan on jobs (cost=40.94..1111.79 rows=2148 width=4) (actual time=0.595..2.158 rows=2164 loops=1)
Recheck Cond: (project_id = 2)
Buffers: shared hit=225
-> Bitmap Index Scan on index_jobs_on_project_id (cost=0.00..40.40 rows=2148 width=0) (actual time=0.516..0.516 rows=2164 loops=1)
Index Cond: (project_id = 2)
Buffers: shared hit=8
Total runtime: 72.767 ms
(15 rows)
在第一种情况下,该项目有15个工作岗位和2421个工作区。在第二种情况下,该项目有2164个工作岗位和2516个工作区。
有没有办法查询这些数据,以便第二个工作量不会那么慢?或者我只是接近某种最糟糕的性能工作负载?
修改
将random_page_cost更新为1.1并重新运行EXPLAIN以进行慢速查询:http://explain.depesz.com/s/xKdd
EXPLAIN (ANALYZE, BUFFERS) SELECT "blocks".* FROM "blocks" INNER JOIN "jobs" ON "blocks"."job_id" = "jobs"."id" WHERE "jobs"."project_id" = 2;
QUERY PLAN
----------------------------------------------------------------------------------------------------------------------------------------------
Nested Loop (cost=0.71..7634.08 rows=10421 width=130) (actual time=0.025..10.597 rows=2516 loops=1)
Buffers: shared hit=9206
-> Index Scan using index_jobs_on_project_id on jobs (cost=0.29..1048.99 rows=2148 width=4) (actual time=0.015..1.239 rows=2164 loops=1)
Index Cond: (project_id = 32357)
Buffers: shared hit=225
-> Index Scan using index_blocks_on_job_id on blocks (cost=0.42..2.88 rows=19 width=130) (actual time=0.003..0.003 rows=1 loops=2164)
Index Cond: (job_id = jobs.id)
Buffers: shared hit=8981
Total runtime: 10.925 ms
(9 rows)
好多了!看起来我需要投入一些时间来调整服务器配置。
答案 0 :(得分:3)
由于两个索引扫描的嵌套循环比位图索引扫描的散列连接快得多,我说你的random_page_cost
并不能准确反映你的实际性能,至少在缓存数据时在RAM或shared_buffers
。
尝试设置SET random_page_cost = 1.1
并在该会话中重新运行。您可能还想在此问题上投入更多work_mem
。
如果random_page_cost
调整有效,您可能希望更新postgresql.conf
以反映它。请注意,1.1是一个非常极端的设置;默认值为4,seq_page_cost
为1,因此在配置文件中,我会从更像2或1.5开始,以避免使其他计划更糟。