优化Postgres删除孤立记录

use*_*752 9 sql postgresql query-optimization

采取以下两个表:

Table "public.contacts"
       Column       |            Type             |                       Modifiers                       | Storage  | Stats target | Description
--------------------+-----------------------------+-------------------------------------------------------+----------+--------------+-------------
 id                 | integer                     | not null default nextval('contacts_id_seq'::regclass) | plain    |              |
 created_at         | timestamp without time zone | not null                                              | plain    |              |
 updated_at         | timestamp without time zone | not null                                              | plain    |              |
 external_id        | integer                     |                                                       | plain    |              |
 email_address      | character varying           |                                                       | extended |              |
 first_name         | character varying           |                                                       | extended |              |
 last_name          | character varying           |                                                       | extended |              |
 company            | character varying           |                                                       | extended |              |
 industry           | character varying           |                                                       | extended |              |
 country            | character varying           |                                                       | extended |              |
 region             | character varying           |                                                       | extended |              |
 ext_instance_id    | integer                     |                                                       | plain    |              |
 title              | character varying           |                                                       | extended |              |
Indexes:
    "contacts_pkey" PRIMARY KEY, btree (id)
    "index_contacts_on_ext_instance_id_and_external_id" UNIQUE, btree (ext_instance_id, external_id)
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Table "public.members"
        Column         |            Type             |                             Modifiers                              | Storage  | Stats target | Description
-----------------------+-----------------------------+--------------------------------------------------------------------+----------+--------------+-------------
 id                    | integer                     | not null default nextval('members_id_seq'::regclass)               | plain    |              |
 step_id               | integer                     |                                                                    | plain    |              |
 contact_id            | integer                     |                                                                    | plain    |              |
 rule_id               | integer                     |                                                                    | plain    |              |
 request_id            | integer                     |                                                                    | plain    |              |
 sync_id               | integer                     |                                                                    | plain    |              |
 status                | integer                     | not null default 0                                                 | plain    |              |
 matched_targeted_rule | boolean                     | default false                                                      | plain    |              |
 external_fields       | jsonb                       |                                                                    | extended |              |
 imported_at           | timestamp without time zone |                                                                    | plain    |              |
 campaign_id           | integer                     |                                                                    | plain    |              |
 ext_instance_id       | integer                     |                                                                    | plain    |              |
 created_at            | timestamp without time zone |                                                                    | plain    |              |
Indexes:
    "members_pkey" PRIMARY KEY, btree (id)
    "index_members_on_contact_id_and_step_id" UNIQUE, btree (contact_id, step_id)
    "index_members_on_campaign_id" btree (campaign_id)
    "index_members_on_step_id" btree (step_id)
    "index_members_on_sync_id" btree (sync_id)
    "index_members_on_request_id" btree (request_id)
    "index_members_on_status" btree (status)
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主键和主键都存在指数members.contact_id.

我需要删除任何contact没有相关的内容members.大约有3MM contact和25MM的member记录.

我正在尝试以下两个查询:

查询1:

DELETE FROM "contacts"
WHERE  "contacts"."id" IN (SELECT "contacts"."id" 
                           FROM   "contacts" 
                                  LEFT OUTER JOIN members 
                                               ON 
                                  members.contact_id = contacts.id 
                           WHERE  members.id IS NULL);

DELETE 0
Time: 173033.801 ms

-----------------------------------------------------------------------------------------------------------------------------------------------------------------
 Delete on contacts  (cost=2654306.79..2654307.86 rows=1 width=18) (actual time=188717.354..188717.354 rows=0 loops=1)
   ->  Nested Loop  (cost=2654306.79..2654307.86 rows=1 width=18) (actual time=188717.351..188717.351 rows=0 loops=1)
         ->  HashAggregate  (cost=2654306.36..2654306.37 rows=1 width=16) (actual time=188717.349..188717.349 rows=0 loops=1)
               Group Key: contacts_1.id
               ->  Hash Right Join  (cost=161177.46..2654306.36 rows=1 width=16) (actual time=188717.345..188717.345 rows=0 loops=1)
                     Hash Cond: (members.contact_id = contacts_1.id)
                     Filter: (members.id IS NULL)
                     Rows Removed by Filter: 26725870
                     ->  Seq Scan on members  (cost=0.00..1818698.96 rows=25322396 width=14) (actual time=0.043..160226.686 rows=26725870 loops=1)
                     ->  Hash  (cost=105460.65..105460.65 rows=3205265 width=10) (actual time=1962.612..1962.612 rows=3196180 loops=1)
                           Buckets: 262144  Batches: 4  Memory Usage: 34361kB
                           ->  Seq Scan on contacts contacts_1  (cost=0.00..105460.65 rows=3205265 width=10) (actual time=0.011..950.657 rows=3196180 loops=1)
         ->  Index Scan using contacts_pkey on contacts  (cost=0.43..1.48 rows=1 width=10) (never executed)
               Index Cond: (id = contacts_1.id)
 Planning time: 0.488 ms
 Execution time: 188718.862 ms
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查询2:

DELETE FROM contacts 
WHERE  NOT EXISTS (SELECT 1 
                   FROM   members c 
                   WHERE  c.contact_id = contacts.id); 

DELETE 0
Time: 170871.219 ms

-------------------------------------------------------------------------------------------------------------------------------------------------------------
 Delete on contacts  (cost=2258873.91..2954594.50 rows=1895601 width=12) (actual time=177523.034..177523.034 rows=0 loops=1)
   ->  Hash Anti Join  (cost=2258873.91..2954594.50 rows=1895601 width=12) (actual time=177523.029..177523.029 rows=0 loops=1)
         Hash Cond: (contacts.id = c.contact_id)
         ->  Seq Scan on contacts  (cost=0.00..105460.65 rows=3205265 width=10) (actual time=0.018..1068.357 rows=3196180 loops=1)
         ->  Hash  (cost=1818698.96..1818698.96 rows=25322396 width=10) (actual time=169587.802..169587.802 rows=26725870 loops=1)
               Buckets: 262144  Batches: 32  Memory Usage: 36228kB
               ->  Seq Scan on members c  (cost=0.00..1818698.96 rows=25322396 width=10) (actual time=0.052..160081.880 rows=26725870 loops=1)
 Planning time: 0.901 ms
 Execution time: 177524.526 ms
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正如您所看到的,即使删除任何记录,两个查询都会显示相似的性能,大约需要3分钟.

服务器的磁盘I/O峰值为100%,因此我假设数据,因为顺序扫描上都做的是被泼到磁盘contactsmembers.

服务器是EC2 r3.large(15GB RAM).

有关如何优化此查询的任何想法?

更新#1:

运行vacuum analyze两个表并确保enable_mergejoin设置为on查询时间没有区别后:

DELETE FROM contacts 
WHERE  NOT EXISTS (SELECT 1 
                   FROM   members c 
                   WHERE  c.contact_id = contacts.id); 

-------------------------------------------------------------------------------------------------------------------------------------------------------------
 Delete on contacts  (cost=2246088.17..2966677.08 rows=1875003 width=12) (actual time=209406.342..209406.342 rows=0 loops=1)
   ->  Hash Anti Join  (cost=2246088.17..2966677.08 rows=1875003 width=12) (actual time=209406.338..209406.338 rows=0 loops=1)
         Hash Cond: (contacts.id = c.contact_id)
         ->  Seq Scan on contacts  (cost=0.00..105683.28 rows=3227528 width=10) (actual time=0.008..1010.643 rows=3227462 loops=1)
         ->  Hash  (cost=1814029.74..1814029.74 rows=24855474 width=10) (actual time=198054.302..198054.302 rows=27307060 loops=1)
               Buckets: 262144  Batches: 32  Memory Usage: 37006kB
               ->  Seq Scan on members c  (cost=0.00..1814029.74 rows=24855474 width=10) (actual time=1.132..188654.555 rows=27307060 loops=1)
 Planning time: 0.328 ms
 Execution time: 209408.040 ms
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更新2:

PG版本:

PostgreSQL 9.4.4 on x86_64-pc-linux-gnu, compiled by x86_64-pc-linux-gnu-gcc (Gentoo Hardened 4.5.4 p1.0, pie-0.4.7) 4.5.4, 64-bit
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关系大小:

         Table         |  Size   | External Size
-----------------------+---------+---------------
 members               | 23 GB   | 11 GB
 contacts              | 944 MB  | 371 MB
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设置:

 work_mem
----------
 64MB

 random_page_cost
------------------
 4
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更新3:

尝试批量执行此操作似乎并没有帮助I/O使用(仍然达到100%)并且尽管使用基于索引的计划,但似乎并没有按时完善.

DO $do$ 
BEGIN 
  FOR i IN 57..668 
  LOOP 
    DELETE 
    FROM   contacts 
    WHERE  contacts.id IN 
           ( 
                           SELECT          contacts.id 
                           FROM            contacts 
                           left outer join members 
                           ON              members.contact_id = contacts.id 
                           WHERE           members.id IS NULL 
                           AND             contacts.id >= (i    * 10000) 
                           AND             contacts.id < ((i+1) * 10000));
END LOOP;END $do$;
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之后我不得不终止查询,Time: 1203492.326 ms并且在查询运行的整个时间内磁盘I/O保持在100%.我还尝试了1,000和5,000块,但没有看到任何性能提升.

注意:使用57..668范围是因为我知道这些是现有的联系人ID.(例如min(id)max(id))

Erw*_*ter 4

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关于我可以做什么来优化这个查询有什么想法吗?

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你的查询很完美。我会使用该NOT EXISTS变体。
\n你的索引index_members_on_contact_id_and_step_id也有好处:

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但请参阅下文有关 BRIN 指数的内容。

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您可以调整服务器、表和索引配置。

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由于您几乎不更新或删除任何行,根据您的评论,请重点关注优化读取性能。

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1.升级你的Postgres版本

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您提供:

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服务器是 EC2 r3.large(15GB RAM)。

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和:

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PostgreSQL 9.4.4

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你的版本已经严重过时了。至少升级到最新的小版本。更好的是,升级到当前的主要版本。Postgres 9.5 和 9.6 为大数据带来了重大改进——这正是您所需要的。

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考虑项目的版本控制策略。

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亚马逊允许您升级!

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2. 改进表统计

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在基本顺序扫描中,预期行数与实际行数之间存在意外的 10% 不匹配:

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对成员 c 进行 Seq 扫描(成本=0.00..1814029.74行=24855474宽度=10)(实际时间=1.132..188654.555行=27307060循环=1)

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一点也不引人注目,但仍然不应该出现在这个查询中。表示您可能需要调整autovacuum设置 - 对于非常大的表,可能需要调整设置。

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问题比较多:

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哈希反连接(成本=2246088.17..2966677.08行=1875003宽度=12)(实际时间=209406.338..209406.338行=0循环=1)

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Postgres 期望找到 1875003 行要删除,而实际上找到 0 行。这是出乎意料的。members.contact_id也许大幅增加和的统计目标contacts.id可以帮助缩小差距,这可能会允许更好的查询计划。看:

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3.避免表和索引膨胀

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您的 ~ 25MM 行members占用 23 GB - 每行几乎 1kb,这对于您提供的表定义来说似乎过多(即使您提供的总大小应包括索引):

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 4 bytes  item identifier\n\n24        tuple header\n 8        null bitmap\n36        9x integer\n16        2x ts\n 1        1x bool\n??        1x jsonb\n
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看:

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每行 89 个字节 - 或者更少,带有一些 NULL 值 - 几乎没有任何对齐填充,因此最大 96 个字节,加上您的jsonb列。

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要么jsonb列非常大,这会让我建议将数据规范化为单独的列或单独的表。考虑:

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或者你的桌子很臃肿,这可以用 或 来解决VACUUM FULL ANALYZE,同时在它上面:

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CLUSTER members USING index_members_on_contact_id_and_step_id;\nVACUUM members;\n
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但要么在表上获得独占锁,你说你负担不起。pg_repack无需独占锁即可做到。看:

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即使我们考虑索引大小,您的表似乎太大了:您有 7 个小索引,每个索引每行 36 - 44 字节,没有膨胀,NULL 值更少,因此总共 < 300 字节。

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无论哪种方式,请考虑对您的表进行更激进的autovacuum设置members。有关的:

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和/或从一开始就停止让表格膨胀。您是否经常更新行?您经常更新哪个特定专栏?也许是那个jsonb专栏?您可以将其移动到一个单独的 (1:1) 表,只是为了停止用死元组使主表膨胀 - 并阻止其autovacuum完成其工作。

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4. 尝试 BRIN 索引

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块范围索引需要 Postgres 9.5 或更高版本,并显着减少索引大小。我对初稿过于乐观了。如果每个索引都有很多行,则BRIN 索引非常适合您的用例- 在对表进行至少一次物理聚类之后(有关拟合命令,请参阅 \xe2\x91\xa2)。在这种情况下,Postgres 可以快速排除整个数据页。但是您的数字表明每个 大约只有 8 行,因此数据页通常会包含多个值,这会导致大部分效果无效。取决于您的数据分布的实际细节......memberscontact.idCLUSTERcontact.id

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另一方面,就目前情况而言,元组大小约为 1 kb,因此每个数据页只有约 8 行(通常为 8kb)。如果这不是主要的膨胀,那么 BRIN 索引毕竟可能会有所帮助。

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但您需要先升级您的服务器版本。请参阅\xe2\x91\xa0。

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CREATE INDEX members_contact_id_brin_idx ON members USING BRIN (contact_id);\n
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