database - Postgres order by foreign key 性能？

Question

我在 Postgres 中通过外键进行排序时遇到奇怪的(？)问题。这是第二个表和查询，使用 order by 比没有使用要花费更长的时间。

EXPLAIN ANALYZE SELECT "spoleczniak_zdjecia"."id", "spoleczniak_zdjecia"."postac_id", "spoleczniak_zdjecia"."zdjecie", "spoleczniak_zdjecia"."opis", "spoleczniak_zdjecia"."data", "spoleczniak_zdjecia"."avatar", "spoleczniak_zdjecia"."tagi", "postac_postacie"."id", "postac_postacie"."user_id", "postac_postacie"."avatar", "postac_postacie"."ikonka", "postac_postacie"."imie", "postac_postacie"."nazwisko", "postac_postacie"."pseudonim", "postac_postacie"."plec", "postac_postacie"."wzrost", "postac_postacie"."waga", "postac_postacie"."ur_tydz", "postac_postacie"."ur_rok", "postac_postacie"."ur_miasto_id", "postac_postacie"."akt_miasto_id", "postac_postacie"."kasa", "postac_postacie"."punkty", "postac_postacie"."zmeczenie", "postac_postacie"."zdrowie", "postac_postacie"."kariera" FROM "spoleczniak_zdjecia" INNER JOIN "taggit_taggeditem" ON ("spoleczniak_zdjecia"."id" = "taggit_taggeditem"."object_id") INNER JOIN "taggit_tag" ON ("taggit_taggeditem"."tag_id" = "taggit_tag"."id") INNER JOIN "postac_postacie" ON ("spoleczniak_zdjecia"."postac_id" = "postac_postacie"."id") WHERE ("taggit_tag"."slug" = 'ja' AND "taggit_taggeditem"."content_type_id" = 922 ) ORDER BY "spoleczniak_zdjecia"."id" DESC LIMIT 28;
                                                                                QUERY PLAN
---------------------------------------------------------------------------------------------------------------------------------------------------------------------------
 Limit  (cost=27.88..27.89 rows=7 width=198) (actual time=2984.689..2984.697 rows=28 loops=1)
   ->  Sort  (cost=27.88..27.89 rows=7 width=198) (actual time=2984.688..2984.692 rows=28 loops=1)
         Sort Key: spoleczniak_zdjecia.id
         Sort Method: top-N heapsort  Memory: 32kB
         ->  Nested Loop  (cost=2.31..27.78 rows=7 width=198) (actual time=1.063..2974.901 rows=9091 loops=1)
               ->  Nested Loop  (cost=2.31..22.02 rows=7 width=109) (actual time=1.057..2899.010 rows=9091 loops=1)
                     ->  Nested Loop  (cost=2.31..19.92 rows=7 width=4) (actual time=1.046..2848.853 rows=9103 loops=1)
                           ->  Index Scan using taggit_tag_slug on taggit_tag  (cost=0.00..4.27 rows=1 width=4) (actual time=0.025..0.027 rows=1 loops=1)
                                 Index Cond: ((slug)::text = 'ja'::text)
                           ->  Bitmap Heap Scan on taggit_taggeditem  (cost=2.31..15.56 rows=7 width=8) (actual time=1.019..2847.244 rows=9103 loops=1)
                                 Recheck Cond: (tag_id = taggit_tag.id)
                                 Filter: (content_type_id = 922)
                                 ->  Bitmap Index Scan on taggit_taggeditem_tag_id  (cost=0.00..2.31 rows=7 width=0) (actual time=0.954..0.954 rows=9103 loops=1)
                                       Index Cond: (tag_id = taggit_tag.id)
                     ->  Index Scan using spoleczniak_zdjecia_pkey on spoleczniak_zdjecia  (cost=0.00..0.29 rows=1 width=109) (actual time=0.005..0.005 rows=1 loops=9103)
                           Index Cond: (id = taggit_taggeditem.object_id)
               ->  Index Scan using postac_postacie_pkey on postac_postacie  (cost=0.00..0.81 rows=1 width=89) (actual time=0.007..0.007 rows=1 loops=9091)
                     Index Cond: (id = spoleczniak_zdjecia.postac_id)
 Total runtime: 2984.760 ms

这里没有订单:

EXPLAIN ANALYZE SELECT "spoleczniak_zdjecia"."id", "spoleczniak_zdjecia"."postac_id", "spoleczniak_zdjecia"."zdjecie", "spoleczniak_zdjecia"."opis", "spoleczniak_zdjecia"."data", "spoleczniak_zdjecia"."avatar", "spoleczniak_zdjecia"."tagi", "postac_postacie"."id", "postac_postacie"."user_id", "postac_postacie"."avatar", "postac_postacie"."ikonka", "postac_postacie"."imie", "postac_postacie"."nazwisko", "postac_postacie"."pseudonim", "postac_postacie"."plec", "postac_postacie"."wzrost", "postac_postacie"."waga", "postac_postacie"."ur_tydz", "postac_postacie"."ur_rok", "postac_postacie"."ur_miasto_id", "postac_postacie"."akt_miasto_id", "postac_postacie"."kasa", "postac_postacie"."punkty", "postac_postacie"."zmeczenie", "postac_postacie"."zdrowie", "postac_postacie"."kariera" FROM "spoleczniak_zdjecia" INNER JOIN "taggit_taggeditem" ON ("spoleczniak_zdjecia"."id" = "taggit_taggeditem"."object_id") INNER JOIN "taggit_tag" ON ("taggit_taggeditem"."tag_id" = "taggit_tag"."id") INNER JOIN "postac_postacie" ON ("spoleczniak_zdjecia"."postac_id" = "postac_postacie"."id") WHERE ("taggit_tag"."slug" = 'ja' AND "taggit_taggeditem"."content_type_id" = 922 ) LIMIT 28;
                                                                            QUERY PLAN
-------------------------------------------------------------------------------------------------------------------------------------------------------------------
 Limit  (cost=2.31..27.78 rows=7 width=198) (actual time=1.113..1.482 rows=28 loops=1)
   ->  Nested Loop  (cost=2.31..27.78 rows=7 width=198) (actual time=1.112..1.477 rows=28 loops=1)
         ->  Nested Loop  (cost=2.31..22.02 rows=7 width=109) (actual time=1.102..1.292 rows=28 loops=1)
               ->  Nested Loop  (cost=2.31..19.92 rows=7 width=4) (actual time=1.092..1.145 rows=28 loops=1)
                     ->  Index Scan using taggit_tag_slug on taggit_tag  (cost=0.00..4.27 rows=1 width=4) (actual time=0.017..0.017 rows=1 loops=1)
                           Index Cond: ((slug)::text = 'ja'::text)
                     ->  Bitmap Heap Scan on taggit_taggeditem  (cost=2.31..15.56 rows=7 width=8) (actual time=1.072..1.118 rows=28 loops=1)
                           Recheck Cond: (tag_id = taggit_tag.id)
                           Filter: (content_type_id = 922)
                           ->  Bitmap Index Scan on taggit_taggeditem_tag_id  (cost=0.00..2.31 rows=7 width=0) (actual time=0.989..0.989 rows=9103 loops=1)
                                 Index Cond: (tag_id = taggit_tag.id)
               ->  Index Scan using spoleczniak_zdjecia_pkey on spoleczniak_zdjecia  (cost=0.00..0.29 rows=1 width=109) (actual time=0.004..0.005 rows=1 loops=28)
                     Index Cond: (id = taggit_taggeditem.object_id)
         ->  Index Scan using postac_postacie_pkey on postac_postacie  (cost=0.00..0.81 rows=1 width=89) (actual time=0.005..0.005 rows=1 loops=28)
               Index Cond: (id = spoleczniak_zdjecia.postac_id)
 Total runtime: 1.562 ms

什么会导致问题？是查询？配置？我应该检查任何特定的配置吗？在我的最后一个问题中有更复杂的查询，但那个查询一点也不复杂。有什么建议吗？

顺便说一句。该查询由 Django(准确地说是 django-taggit)生成。顺便说一句。第二部分，它一点也不差硬件(i7、16 GB RAM、用于操作系统和数据的 RAID 10 3x2 + 2 个用于 WAL 的 RAID1 磁盘、512 MB RAID 缓存 + BBU)

纯文本查询:

SELECT "spoleczniak_zdjecia"."id", "spoleczniak_zdjecia"."postac_id", "spoleczniak_zdjecia"."zdjecie", "spoleczniak_zdjecia"."opis", "spoleczniak_zdjecia"."data", "spoleczniak_zdjecia"."avatar ", "spoleczniak_zdjecia"."tagi", "postac_postacie"."id", "postac_postacie"."user_id", "postac_postacie"."avatar", "postac_postacie"."ikonka", "postac_postacie"."imie", “postac_postacie”。“nazwisko”，“postac_postacie”。“pseudonim”，“postac_postacie”。 “.ur_rok”、“postac_postacie”、“ur_miasto_id”、“postac_postacie”、“akt_miasto_id”、“postac_postacie”、“kasa”、“postac_postacie”、“punkty”、“postac_postacie”、“zmeczenie”、“postac_postacie”。 “zdrowie”、“postac_postacie”、“kariera”来自“spoleczniak_zdjecia”内部连接“taggit_taggeditem”ON(“spoleczniak_zdjecia”、“id”=“taggit_taggeditem”、“object_id”)内部连接“taggit_tag”ON(“taggit_taggeditem”。 tag_id"= "taggit_tag"."id") INNER JOIN "postac_postaci e"ON ("spoleczniak_zdjecia"."postac_id"= "postac_postacie"."id") WHERE ("taggit_tag"."slug"= 'ja' AND "taggit_taggeditem"."content_type_id"= 922) 按“spoleczniak_zdjecia”排序。 "id"DESC LIMIT 28;

Answer 1

区别就在 EXPLAIN 输出的第二行:

->  Sort  (cost=27.88..27.89 rows=7 width=198) (actual time=2984.688..2984.692 rows=28 loops=1)

请注意，“实际时间”几乎是查询的整个时间。排序不仅需要一堆比较(即排序任何东西的成本)，还需要额外的数据管理，服务器需要将一些数据(行或行指针)复制到一个临时位置，以便可以在不打扰其他任何东西的情况下对其进行排序.

除非您运气好并且您的排序与磁盘上的顺序匹配并且优化器可以注意到它们匹配，否则任何排序查询都会花费更长的时间。