将PostreSQL从9.1升级到9.4后性能下降

Question

将Postgres 9.1升级到9.4后，性能变得非常低下。以下是两个查询运行速度显着更慢的示例。

注意：我意识到这些查询可能会被重写为更有效的工作，但我关心的主要问题是升级到更新版本的Postgres后，它们突然以更慢的速度运行100倍！我希望有一个我忽略的配置变量。

在升级过程中，我使用了pg_upgrade命令和--link选项。配置文件在9.4和9.1之间相同。它不是在完全相同的硬件上运行的，但它们都在Linode上运行，并且我已经尝试使用3种不同的Linode来作为新服务器，所以我不认为这是硬件问题。

看起来在这两种情况下，9.4是使用不同的索引比9.1？

9.1：

EXPLAIN ANALYZE SELECT "id", "title", "timestamp", "parent", "deleted", "sunk", "closed", "sticky", "lastupdate", "views", "oldid", "editedon", "devpost", "hideblue", "totalvotes", "statustag", "forum_category_id", "account_id" FROM "forum_posts" WHERE "parent" = 882269 ORDER BY "timestamp" DESC LIMIT 1; 
                     QUERY PLAN                  
    ----------------------------------------------------------------------------------------------------------------------------------------------------- 
    Limit (cost=63.87..63.87 rows=1 width=78) (actual time=0.020..0.020 rows=0 loops=1) 
     -> Sort (cost=63.87..63.98 rows=45 width=78) (actual time=0.018..0.018 rows=0 loops=1) 
      Sort Key: "timestamp" 
      Sort Method: quicksort Memory: 17kB 
      -> Index Scan using index_forum_posts_parent on forum_posts (cost=0.00..63.65 rows=45 width=78) (actual time=0.013..0.013 rows=0 loops=1) 
        Index Cond: (parent = 882269) 
    Total runtime: 0.074 ms 
    (7 rows) 

9.4：

EXPLAIN ANALYZE SELECT "id", "title", "timestamp", "parent", "deleted", "sunk", "closed", "sticky", "lastupdate", "views", "oldid", "editedon", "devpost", "hideblue", "totalvotes", "statustag", "forum_category_id", "account_id" FROM "forum_posts" WHERE "parent" = 882269 ORDER BY "timestamp" DESC LIMIT 1; 
                       QUERY PLAN                    
----------------------------------------------------------------------------------------------------------------------------------------------------------------------- 
Limit (cost=0.42..63.48 rows=1 width=1078) (actual time=920.484..920.484 rows=0 loops=1) 
    -> Index Scan Backward using forum_posts_timestamp_index on forum_posts (cost=0.42..182622.07 rows=2896 width=1078) (actual time=920.480..920.480 rows=0 loops=1) 
     Filter: (parent = 882269) 
     Rows Removed by Filter: 1576382 
Planning time: 0.166 ms 
Execution time: 920.521 ms 
(6 rows) 

9.1：

EXPLAIN ANALYZE SELECT "user_library_images"."id", "user_library_images"."imgsrc", "user_library_images"."library_image_id", "user_library_images"."type", "user_library_images"."is_user_uploaded", "user_library_images"."credit", "user_library_images"."orig_dimensions", "user_library_images"."account_id" FROM "user_library_images" INNER JOIN "image_tags" ON "user_library_images"."id" = "image_tags"."user_library_image_id" WHERE ("user_library_images"."account_id" = 769718 AND "image_tags"."tag" ILIKE '%stone%') GROUP BY "user_library_images"."id", "user_library_images"."imgsrc", "user_library_images"."library_image_id", "user_library_images"."type", "user_library_images"."is_user_uploaded", "user_library_images"."credit", "user_library_images"."orig_dimensions", "user_library_images"."account_id" ORDER BY "user_library_images"."id"; 

Group (cost=2015.46..2015.49 rows=1 width=247) (actual time=0.629..0.652 rows=6 loops=1) 
    -> Sort (cost=2015.46..2015.47 rows=1 width=247) (actual time=0.626..0.632 rows=6 loops=1) 
     Sort Key: user_library_images.id, user_library_images.imgsrc, user_library_images.library_image_id, user_library_images.type, user_library_images.is_user_uploaded, user_library_images.credit, user_library_images.orig_dimensions, user_library_images.account_id 
     Sort Method: quicksort Memory: 19kB 
     -> Nested Loop (cost=0.00..2015.45 rows=1 width=247) (actual time=0.283..0.603 rows=6 loops=1) 
       -> Index Scan using index_user_library_images_account on user_library_images (cost=0.00..445.57 rows=285 width=247) (actual time=0.076..0.273 rows=13 loops=1) 
        Index Cond: (account_id = 769718) 
       -> Index Scan using index_image_tags_user_library_image on image_tags (cost=0.00..5.50 rows=1 width=4) (actual time=0.020..0.021 rows=0 loops=13) 
        Index Cond: (user_library_image_id = user_library_images.id) 
        Filter: (tag ~~* '%stone%'::text) 
Total runtime: 0.697 ms 
(11 rows) 

9.4：

Group (cost=166708.13..166709.46 rows=59 width=1241) (actual time=9677.052..9677.052 rows=0 loops=1) 
    Group Key: user_library_images.id, user_library_images.imgsrc, user_library_images.library_image_id, user_library_images.type, user_library_images.is_user_uploaded, user_library_images.credit, user_library_images.orig_dimensions, user_library_images.account_id 
    -> Sort (cost=166708.13..166708.28 rows=59 width=1241) (actual time=9677.049..9677.049 rows=0 loops=1) 
     Sort Key: user_library_images.id, user_library_images.imgsrc, user_library_images.library_image_id, user_library_images.type, user_library_images.is_user_uploaded, user_library_images.credit, user_library_images.orig_dimensions, user_library_images.account_id 
     Sort Method: quicksort Memory: 17kB 
     -> Hash Join (cost=10113.22..166706.39 rows=59 width=1241) (actual time=9677.035..9677.035 rows=0 loops=1) 
       Hash Cond: (image_tags.user_library_image_id = user_library_images.id) 
       -> Seq Scan on image_tags (cost=0.00..156488.85 rows=11855 width=4) (actual time=0.301..9592.048 rows=63868 loops=1) 
        Filter: (tag ~~* '%stone%'::text) 
        Rows Removed by Filter: 9370406 
       -> Hash (cost=10045.97..10045.97 rows=5380 width=1241) (actual time=0.047..0.047 rows=4 loops=1) 
        Buckets: 1024 Batches: 1 Memory Usage: 1kB 
        -> Bitmap Heap Scan on user_library_images (cost=288.12..10045.97 rows=5380 width=1241) (actual time=0.027..0.037 rows=4 loops=1) 
          Recheck Cond: (account_id = 769718) 
          Heap Blocks: exact=4 
          -> Bitmap Index Scan on index_user_library_images_account (cost=0.00..286.78 rows=5380 width=0) (actual time=0.019..0.019 rows=4 loops=1) 
           Index Cond: (account_id = 769718) 
Planning time: 0.223 ms 
Execution time: 9677.109 ms 
(19 rows) 

====

运行分析脚本（请参阅下面的答案）后，问题就解决了。作为参考，这里是新的ANALYZE输出（9.4）：

Group (cost=2062.82..2062.91 rows=4 width=248) (actual time=8.775..8.801 rows=7 loops=1) 
    Group Key: user_library_images.id, user_library_images.imgsrc, user_library_images.library_image_id, user_library_images.type, user_library_images.is_user_uploaded, user_library_images.credit, user_library_images.orig_dimensions, user_library_images.account_id 
    -> Sort (cost=2062.82..2062.83 rows=4 width=248) (actual time=8.771..8.780 rows=7 loops=1) 
     Sort Key: user_library_images.id, user_library_images.imgsrc, user_library_images.library_image_id, user_library_images.type, user_library_images.is_user_uploaded, user_library_images.credit, user_library_images.orig_dimensions, user_library_images.account_id 
     Sort Method: quicksort Memory: 19kB 
     -> Nested Loop (cost=0.87..2062.78 rows=4 width=248) (actual time=4.156..8.685 rows=7 loops=1) 
       -> Index Scan using index_user_library_images_account on user_library_images (cost=0.43..469.62 rows=304 width=248) (actual time=0.319..2.528 rows=363 loops=1) 
        Index Cond: (account_id = 769718) 
       -> Index Scan using index_image_tags_user_library_image on image_tags (cost=0.43..5.23 rows=1 width=4) (actual time=0.014..0.014 rows=0 loops=363) 
        Index Cond: (user_library_image_id = user_library_images.id) 
        Filter: (tag ~~* '%stone%'::text) 
        Rows Removed by Filter: 2 
Planning time: 2.956 ms 
Execution time: 8.907 ms 
(14 rows) 



Limit (cost=65.81..65.81 rows=1 width=77) (actual time=0.256..0.256 rows=0 loops=1) 
    -> Sort (cost=65.81..65.92 rows=47 width=77) (actual time=0.252..0.252 rows=0 loops=1) 
     Sort Key: "timestamp" 
     Sort Method: quicksort Memory: 17kB 
     -> Index Scan using index_forum_posts_parent on forum_posts (cost=0.43..65.57 rows=47 width=77) (actual time=0.211..0.211 rows=0 loops=1) 
       Index Cond: (parent = 882269) 
Planning time: 2.978 ms 
Execution time: 0.380 ms 
(8 rows) 

Answer 1

pg_upgrade不会复制（或迁移）的统计数据为你的数据库。

因此，您需要分析您的表以便更新迁移数据库中的统计信息。 pg_upgrade将创建一个名称为analyze_new_cluster的批处理文件/ shell脚本，可用于此目的。

或者，您可以手动使用vacuum analyze来实现相同的目的。

通过查看执行计划可以检测到缺少的统计信息。行的预期数目和实际的号之间的差是太高：

(cost=0.00..286.78 rows=5380 width=0) (actual time=0.019..0.019 rows=4 loops=1) 

==> 5380对4行

或

(cost=0.00..156488.85 rows=11855 width=4) (actual time=0.301..9592.048 rows=63868 loops=1) 

==> 11855与63868行