我正在尝试优化以下场景:
以文字格式:我有 2 个表,alerts
和 user_devices
;在 user_devices
中,我们跟踪连接到 user_id
的设备是否想要接收通知,在 alerts
表中,我们跟踪用户与通知者的关系.基本上,任务是选择每个具有任何警报的 user_id
并允许通知注册到它的任何设备。
表“警报”,大约 90 万条记录:
Table "public.alerts"
Column | Type | Modifiers
-------------+--------------------------+-----------
id | uuid | not null
user_id | uuid |
target_id | uuid |
target_type | text |
added_on | timestamp with time zone |
old_id | text |
Indexes:
"alerts_pkey" PRIMARY KEY, btree (id)
"one_alert_per_business_per_user" UNIQUE CONSTRAINT, btree (user_id, target_id)
"addedon" btree (added_on)
"targetid" btree (target_id)
"userid" btree (user_id)
"userid_targetid" btree (user_id, target_id)
Foreign-key constraints:
"alerts_user_id_fkey" FOREIGN KEY (user_id) REFERENCES users(id)
表 'user_devices',大约 12k 条记录:
Table "public.user_devices"
Column | Type | Modifiers
---------------------+--------------------------+-----------
id | uuid | not null
user_id | uuid |
device_id | text |
device_token | text |
push_notify_enabled | boolean |
device_type | integer |
device_name | text |
badge_count | integer |
added_on | timestamp with time zone |
Indexes:
"user_devices_pkey" PRIMARY KEY, btree (id)
"push_notification" btree (push_notify_enabled)
"user_id" btree (user_id)
"user_id_push_notification" btree (user_id, push_notify_enabled)
Foreign-key constraints:
"user_devices_user_id_fkey" FOREIGN KEY (user_id) REFERENCES users(id)
以下查询:
select COUNT(DISTINCT a.user_id)
from alerts a
inner join user_devices ud on a.user_id = ud.user_id
WHERE ud.push_notify_enabled = true;
大约需要 3 秒并生成以下计划:
explain select COUNT(DISTINCT a.user_id) from alerts a inner join user_devices ud on a.user_id = ud.user_id WHERE ud.push_notify_enabled = true;
QUERY PLAN
------------------------------------------------------------------------------------
Aggregate (cost=49777.32..49777.33 rows=1 width=16)
-> Hash Join (cost=34508.97..48239.63 rows=615074 width=16)
Hash Cond: (ud.user_id = a.user_id)
-> Seq Scan on user_devices ud (cost=0.00..480.75 rows=9202 width=16)
Filter: push_notify_enabled
-> Hash (cost=20572.32..20572.32 rows=801732 width=16)
-> Seq Scan on alerts a (cost=0.00..20572.32 rows=801732 width=16)
我错过了什么,有没有办法加快速度?
谢谢。
== 编辑 ==
根据建议,尝试在连接内移动条件,没有区别:
=> explain select COUNT(DISTINCT a.user_id) from alerts a inner join user_devices ud on a.user_id = ud.user_id and ud.push_notify_enabled;
QUERY PLAN
------------------------------------------------------------------------------------
Aggregate (cost=49777.32..49777.33 rows=1 width=16)
-> Hash Join (cost=34508.97..48239.63 rows=615074 width=16)
Hash Cond: (ud.user_id = a.user_id)
-> Seq Scan on user_devices ud (cost=0.00..480.75 rows=9202 width=16)
Filter: push_notify_enabled
-> Hash (cost=20572.32..20572.32 rows=801732 width=16)
-> Seq Scan on alerts a (cost=0.00..20572.32 rows=801732 width=16)
所以,没有办法摆脱 2 FTS 吗?如果我至少能让它以某种方式使用“警报”表上的索引,那就太好了……
== 编辑 ==
添加`EXPLAIN ANALYZE。
=> explain ANALYZE select COUNT(DISTINCT a.user_id) from alerts a inner join user_devices ud on a.user_id = ud.user_id and ud.push_notify_enabled;
QUERY PLAN
-------------------------------------------------------------------------------------------------------------------------------------
Aggregate (cost=49777.32..49777.33 rows=1 width=16) (actual time=5254.355..5254.356 rows=1 loops=1)
-> Hash Join (cost=34508.97..48239.63 rows=615074 width=16) (actual time=1824.607..2863.635 rows=614768 loops=1)
Hash Cond: (ud.user_id = a.user_id)
-> Seq Scan on user_devices ud (cost=0.00..480.75 rows=9202 width=16) (actual time=0.048..16.784 rows=9186 loops=1)
Filter: push_notify_enabled
-> Hash (cost=20572.32..20572.32 rows=801732 width=16) (actual time=1824.229..1824.229 rows=801765 loops=1)
Buckets: 4096 Batches: 32 Memory Usage: 990kB
-> Seq Scan on alerts a (cost=0.00..20572.32 rows=801732 width=16) (actual time=0.047..878.429 rows=801765 loops=1)
Total runtime: 5255.427 ms
(9 rows)
===编辑===
添加请求的配置。其中大部分是 Ubuntu PG9.1 默认值:
/etc/postgresql/9.1/main# cat postgresql.conf | grep -e "work_mem" -e "effective_cache" -e "shared_buff" -e "random_page_c"
shared_buffers = 24MB # min 128kB
#work_mem = 1MB # min 64kB
#maintenance_work_mem = 16MB # min 1MB
#wal_buffers = -1 # min 32kB, -1 sets based on shared_buffers
#random_page_cost = 4.0 # same scale as above
#effective_cache_size = 128MB
最佳答案
用部分索引替换索引:
DROP INDEX user_id_push_notification ;
CREATE INDEX user_id_push_notification ON user_devices (user_id)
WHERE push_notify_enabled =True
;
,并将 random_page_cost 设置为较低的值:
SET random_page_cost = 1.1;
使用 push_notification on user_devices ud 对我造成了索引扫描
(< 300 毫秒)。 YMMV。
警报上的 seqscan 似乎或多或少是不可避免的,因为您期望 800K/900K := 88%) 行。恕我直言,索引扫描仅在行大小非常大时才有效。
更新:将用户表添加到查询中似乎强制执行三重索引扫描。 (但大约在同一时间)
explain ANALYZE
select COUNT(DISTINCT a.user_id)
from alerts a
join user_devices ud on a.user_id = ud.user_id
join users us on a.user_id = us.id
WHERE ud.push_notify_enabled = true;
关于performance - 为什么我在此 PostgreSQL 查询中得到 'Hash Join' 和 FTS?,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/14404209/