sql - PostgreSQL 查询未使用索引

Question

环境

我的 PostgreSQL (9.2) 架构如下所示:

CREATE TABLE first
(
   id_first bigint NOT NULL,
   first_date timestamp without time zone NOT NULL,
   CONSTRAINT first_pkey PRIMARY KEY (id_first)
)
WITH (
   OIDS=FALSE
);

CREATE INDEX first_first_date_idx
   ON first
   USING btree
     (first_date);

CREATE TABLE second
(
   id_second bigint NOT NULL,
   id_first bigint NOT NULL,
   CONSTRAINT second_pkey PRIMARY KEY (id_second),
   CONSTRAINT fk_first FOREIGN KEY (id_first)
      REFERENCES first (id_first) MATCH SIMPLE
      ON UPDATE NO ACTION ON DELETE NO ACTION
)
WITH (
   OIDS=FALSE
);

CREATE INDEX second_id_first_idx
   ON second
   USING btree
   (id_first);

CREATE TABLE third
(
   id_third bigint NOT NULL,
   id_second bigint NOT NULL,
   CONSTRAINT third_pkey PRIMARY KEY (id_third),
   CONSTRAINT fk_second FOREIGN KEY (id_second)
      REFERENCES second (id_second) MATCH SIMPLE
      ON UPDATE NO ACTION ON DELETE NO ACTION
)
WITH (
   OIDS=FALSE
);

CREATE INDEX third_id_second_idx
   ON third
   USING btree
   (id_second);

所以，我有 3 个表有自己的 PK。 First在 first_date 上有一个索引, Second有来自 First 的 FK并对其进行索引。 Third作为来自 Second 的 FK并对其进行索引:

 First (0 --> n) Second (0 --> n) Third

First表包含关于 10 000 000记录。 Second表包含关于 20 000 000记录。 Third表包含关于 18 000 000记录。

first_date 列中的日期范围从2016-01-01到今天。

random_cost_page设置为 2.0 . default_statistics_target设置为 100 .全部FK , PK和 first_date STATISTICS设置为 5000

要完成的任务

我想统计所有Third与 First 相关的行, 其中first_date < X

我的查询:

SELECT count(t.id_third) AS count
FROM first f
JOIN second s ON s.id_first = f.id_first 
JOIN third t ON t.id_second = s.id_second
WHERE first_date < _my_date

问题描述

• 要求 2 天 - _my_date = '2016-01-03'

一切正常。查询持续 1-2 秒。 EXPLAIN ANALYZE :

"Aggregate  (cost=8585512.55..8585512.56 rows=1 width=8) (actual time=67.310..67.310 rows=1 loops=1)"
"  ->  Merge Join  (cost=4208477.49..8583088.04 rows=969805 width=8) (actual time=44.277..65.948 rows=17631 loops=1)"
"        Merge Cond: (s.id_second = t.id_second)"
"        ->  Sort  (cost=4208477.48..4211121.75 rows=1057709 width=8) (actual time=44.263..46.035 rows=19230 loops=1)"
"              Sort Key: s.id_second"
"              Sort Method: quicksort  Memory: 1670kB"
"              ->  Nested Loop  (cost=0.01..4092310.41 rows=1057709 width=8) (actual time=6.169..39.183 rows=19230 loops=1)"
"                    ->  Index Scan using first_first_date_idx on first f  (cost=0.01..483786.81 rows=492376 width=8)  (actual time=6.159..12.223 rows=10346 loops=1)"
"                          Index Cond: (first_date < '2016-01-03 00:00:00'::timestamp without time zone)"
"                    ->  Index Scan using second_id_first_idx on second s  (cost=0.00..7.26 rows=7 width=16) (actual time=0.002..0.002 rows=2 loops=10346)"
"                          Index Cond: (id_first = f.id_first)"
"        ->  Index Scan using third_id_second_idx on third t  (cost=0.00..4316649.89 rows=17193788 width=16) (actual time=0.008..7.293 rows=17632 loops=1)"
"Total runtime: 67.369 ms"

• 要求 10 天或更长时间 - _my_date = '2016-01-11'或更多

查询未使用 indexscan不再 - 替换为 seqscan最后3-4分钟...查询计划:

"Aggregate  (cost=8731468.75..8731468.76 rows=1 width=8) (actual time=234411.229..234411.229 rows=1 loops=1)"
"  ->  Hash Join  (cost=4352424.81..8728697.88 rows=1108348 width=8) (actual time=189670.068..234400.540 rows=138246 loops=1)"
"        Hash Cond: (t.id_second = o.id_second)"
"        ->  Seq Scan on third t  (cost=0.00..4128080.88 rows=17193788 width=16) (actual time=0.016..124111.453 rows=17570724 loops=1)"
"        ->  Hash  (cost=4332592.69..4332592.69 rows=1208810 width=8) (actual time=98566.740..98566.740 rows=151263 loops=1)"
"              Buckets: 16384  Batches: 16  Memory Usage: 378kB"
"              ->  Hash Join  (cost=561918.25..4332592.69 rows=1208810 width=8) (actual time=6535.801..98535.915 rows=151263 loops=1)"
"                    Hash Cond: (s.id_first = f.id_first)"
"                    ->  Seq Scan on second s  (cost=0.00..3432617.48 rows=18752248 width=16) (actual time=6090.771..88891.691 rows=19132869 loops=1)"
"                    ->  Hash  (cost=552685.31..552685.31 rows=562715 width=8) (actual time=444.630..444.630 rows=81650 loops=1)"
"                          ->  Index Scan using first_first_date_idx on first f  (cost=0.01..552685.31 rows=562715 width=8) (actual time=7.987..421.087 rows=81650 loops=1)"
"                                Index Cond: (first_date < '2016-01-13 00:00:00'::timestamp without time zone)"
"Total runtime: 234411.303 ms"

为了测试目的，我设置了:

 SET enable_seqscan = OFF;

我的查询开始使用 indexscan再次持续 1-10 秒(取决于范围)。

问题

为什么会这样？如何说服查询规划师使用 indexscan ？

编辑

减少一个random_page_cost之后至 1.1 ，我现在可以选择大约 30 天仍在使用 indexscan .查询计划稍微改变了一点:

"Aggregate  (cost=8071389.47..8071389.48 rows=1 width=8) (actual  time=4915.196..4915.196 rows=1 loops=1)"
"  ->  Nested Loop  (cost=0.01..8067832.28 rows=1422878 width=8) (actual time=14.402..4866.937 rows=399184 loops=1)"
"        ->  Nested Loop  (cost=0.01..3492321.55 rows=1551849 width=8) (actual time=14.393..3012.617 rows=436794 loops=1)"
"              ->  Index Scan using first_first_date_idx on first f  (cost=0.01..432541.99 rows=722404 width=8) (actual time=14.372..729.233 rows=236007 loops=1)"
"                    Index Cond: (first_date < '2016-02-01 00:00:00'::timestamp without time zone)"
"              ->  Index Scan using second_id_first_idx on second s  (cost=0.00..4.17 rows=7 width=16) (actual time=0.008..0.009 rows=2 loops=236007)"
"                    Index Cond: (second = f.id_second)"
"        ->  Index Scan using third_id_second_idx on third t  (cost=0.00..2.94 rows=1 width=16) (actual time=0.004..0.004 rows=1 loops=436794)"
"              Index Cond: (id_second = s.id_second)"
"Total runtime: 4915.254 ms"

但是，我仍然不明白为什么要求更多的原因 seqscan ...

有趣的是，当我要求范围刚好超过某种限制时，我得到了这样的查询计划(这里选择 40 天 - 要求更多会再次产生完整的 seqscan):

"Aggregate  (cost=8403399.27..8403399.28 rows=1 width=8) (actual time=138303.216..138303.217 rows=1 loops=1)"
"  ->  Hash Join  (cost=3887619.07..8399467.63 rows=1572656 width=8) (actual time=44056.443..138261.203 rows=512062 loops=1)"
"        Hash Cond: (t.id_second = s.id_second)"
"        ->  Seq Scan on third t  (cost=0.00..4128080.88 rows=17193788 width=16) (actual time=0.004..119497.056 rows=17570724 loops=1)"
"        ->  Hash  (cost=3859478.04..3859478.04 rows=1715203 width=8) (actual time=5695.077..5695.077 rows=560503 loops=1)"
"              Buckets: 16384  Batches: 16  Memory Usage: 1390kB"
"              ->  Nested Loop  (cost=0.01..3859478.04 rows=1715203 width=8) (actual time=65.250..5533.413 rows=560503 loops=1)"
"                    ->  Index Scan using first_first_date_idx on first f  (cost=0.01..477985.28 rows=798447 width=8) (actual time=64.927..1688.341 rows=302663 loops=1)"
"                          Index Cond: (first_date < '2016-02-11 00:00:00'::timestamp without time zone)"
"                    ->  Index Scan using second_id_first_idx on second s (cost=0.00..4.17 rows=7 width=16) (actual time=0.010..0.012 rows=2 loops=302663)"
"                          Index Cond: (id_first = f.id_first)"
"Total runtime: 138303.306 ms"

在 Laurenz Able 建议后更新

按照 Laurenz Able 的建议重写查询计划后:

"Aggregate  (cost=9102321.05..9102321.06 rows=1 width=8) (actual time=15237.830..15237.830 rows=1 loops=1)"
"  ->  Merge Join  (cost=4578171.25..9097528.19 rows=1917143 width=8) (actual time=9111.694..15156.092 rows=803657 loops=1)"
"        Merge Cond: (third.id_second = s.id_second)"
"        ->  Index Scan using third_id_second_idx on third  (cost=0.00..4270478.19 rows=17193788 width=16) (actual time=23.650..5425.137 rows=803658 loops=1)"
"        ->  Materialize  (cost=4577722.81..4588177.38 rows=2090914 width=8) (actual time=9088.030..9354.326 rows=879283 loops=1)"
"              ->  Sort  (cost=4577722.81..4582950.09 rows=2090914 width=8) (actual time=9088.023..9238.426 rows=879283 loops=1)"
"                    Sort Key: s.id_second"
"                    Sort Method: external sort  Disk: 15480kB"
"                    ->  Merge Join  (cost=673389.38..4341477.37 rows=2090914 width=8) (actual time=3662.239..8485.768 rows=879283 loops=1)"
"                          Merge Cond: (s.id_first = f.id_first)"
"                          ->  Index Scan using second_id_first_idx on second s  (cost=0.00..3587838.88 rows=18752248 width=16) (actual time=0.015..4204.308 rows=879284 loops=1)"
"                          ->  Materialize  (cost=672960.82..677827.55 rows=973345 width=8) (actual time=3662.216..3855.667 rows=892988 loops=1)"
"                                ->  Sort  (cost=672960.82..675394.19 rows=973345 width=8) (actual time=3662.213..3745.975 rows=476519 loops=1)"
"                                      Sort Key: f.id_first"
"                                      Sort Method: external sort  Disk: 8400kB"
"                                      ->  Index Scan using first_first_date_idx on first f (cost=0.01..568352.90 rows=973345 width=8) (actual time=126.386..3233.134 rows=476519 loops=1)"
"                                            Index Cond: (first_date < '2016-03-03 00:00:00'::timestamp without time zone)"
"Total runtime: 15244.404 ms"

Answer 1

首先，看起来有些估计是错误的。
尝试ANALYZE 表，看看这是否会改变所选的查询计划。

可能还有帮助的是将 random_page_cost 的值降低到略高于 1 的值，看看这是否会改进计划。

有趣的是，快速查询中 third_id_second_idx 的索引扫描仅产生 17632 行而不是超过 1700 万行，我只能通过假设从该行开始的值来解释id_second 不再匹配 first 和 second 的连接中的任何行，即合并连接在此之后完成。

您可以尝试通过重写查询来利用它。尝试

JOIN (SELECT id_second, id_third FROM third ORDER BY id_second) t

代替

JOIN third t

这可能会导致更好的计划，因为 PostgreSQL 不会优化 ORDER BY使用合并联接可能更便宜。这样你就可以欺骗计划者选择一个它不会认为是理想的计划。对于不同的值(value)分布，规划者最初的选择可能会更好。