SQL有外連接的時候注意過濾條件位置否則會導致網頁慢

2024-08-31 00:56:12

字體：大中小

來源：轉載

供稿：網友

奶奶的，為啥現在五一節只放3天，5月的天氣最適合出游了，不過俺們這些苦逼的IT男是沒法享受了。
一來到公司，項目經理就找到開發leader，說我們網站頁面很慢，讓他排查原因。
一聽說網站慢，頁面慢哥就來精神了，哥的老本行就是解決“慢”的問題。
開發leader 很郁悶的說，我們已經加了 memcache了，20分鐘 cache一次，咋個還是慢呢，
于是哥就問，那個網頁跑了哪些SQL？能抓出來讓我看看嗎？開發Leader 果斷的把SQL 抓了出來。
經過排查，我們發現了一個SQL確實跑得慢。該SQL 如下

復制代碼代碼如下:

select *
from (select u.NAME UniversityName,
u.id UniversityId,
count(a.SIGNUPNUMBER) playercnt
from T_B_UNIVERSITY u
left join T_D_EDUCATION e
on e.UNIVERSITY_ID = u.id
left join T_D_VIDEO_PLAYER a
on a.USER_ID = e.user_id
and e.ISDEFAULT = 1
and e.ISVALID = 1
and a.AUDITSTATUS = 1
and a.ISVALID = 1
left join T_D_USER c
on a.USER_ID = c.id
and c.ISVALID = 1
where u.REGION_CODE like '43%'
group by u.NAME, u.id)
order by playercnt desc;

執行計劃如下

復制代碼代碼如下:

執行計劃
----------------------------------------------------------
Plan hash value: 3938743742
--------------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
--------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 142 | 10366 | 170 (3)| 00:00:03 |
| 1 | SORT ORDER BY | | 142 | 10366 | 170 (3)| 00:00:03 |
| 2 | HASH GROUP BY | | 142 | 10366 | 170 (3)| 00:00:03 |
|* 3 | HASH JOIN RIGHT OUTER| | 672 | 49056 | 168 (2)| 00:00:03 |
|* 4 | TABLE ACCESS FULL | T_D_USER | 690 | 5520 | 5 (0)| 00:00:01 |
| 5 | NESTED LOOPS OUTER | | 672 | 43680 | 162 (1)| 00:00:02 |
|* 6 | HASH JOIN OUTER | | 672 | 37632 | 14 (8)| 00:00:01 |
|* 7 | TABLE ACCESS FULL | T_B_UNIVERSITY | 50 | 2050 | 8 (0)| 00:00:01 |
| 8 | TABLE ACCESS FULL | T_D_EDUCATION | 672 | 10080 | 5 (0)| 00:00:01 |
| 9 | VIEW | | 1 | 9 | 0 (0)| 00:00:01 |
|* 10 | FILTER | | | | | |
|* 11 | TABLE ACCESS FULL| T_D_VIDEO_PLAYER | 1 | 15 | 3 (0)| 00:00:01 |
--------------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
3 - access("A"."USER_ID"="C"."ID"(+))
4 - filter("C"."ISVALID"(+)=1)
6 - access("E"."UNIVERSITY_ID"(+)="U"."ID")
7 - filter("U"."REGION_CODE" LIKE '43%')
10 - filter("E"."ISVALID"=1 AND "E"."ISDEFAULT"=1)
11 - filter("A"."USER_ID"="E"."USER_ID" AND "A"."AUDITSTATUS"=1 AND
"A"."ISVALID"=1)

大家能發現這個SQL 的問題嗎？這個 SQL 之所以跑得慢是因為開發人員把SQL的條件寫錯位置了
正確的寫法應該是下面這樣的

復制代碼代碼如下:

select *
from (select u.NAME UniversityName,
u.id UniversityId,
count(a.SIGNUPNUMBER) playercnt
from T_B_UNIVERSITY u
left join T_D_EDUCATION e
on e.UNIVERSITY_ID = u.id
and e.ISDEFAULT = 1
and e.ISVALID = 1
left join T_D_VIDEO_PLAYER a
on a.USER_ID = e.user_id
and a.AUDITSTATUS = 1
and a.ISVALID = 1
left join T_D_USER c
on a.USER_ID = c.id
and c.ISVALID = 1
where u.REGION_CODE like '43%'
group by u.NAME, u.id)
order by playercnt desc;

執行計劃如下

復制代碼代碼如下:

執行計劃
----------------------------------------------------------
Plan hash value: 2738827747
---------------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
---------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 142 | 11218 | 25 (16)| 00:00:01 |
| 1 | SORT ORDER BY | | 142 | 11218 | 25 (16)| 00:00:01 |
| 2 | HASH GROUP BY | | 142 | 11218 | 25 (16)| 00:00:01 |
|* 3 | HASH JOIN RIGHT OUTER | | 301 | 23779 | 23 (9)| 00:00:01 |
|* 4 | TABLE ACCESS FULL | T_D_USER | 690 | 5520 | 5 (0)| 00:00:01 |
|* 5 | HASH JOIN RIGHT OUTER| | 301 | 21371 | 17 (6)| 00:00:01 |
|* 6 | TABLE ACCESS FULL | T_D_VIDEO_PLAYER | 78 | 1170 | 3 (0)| 00:00:01 |
|* 7 | HASH JOIN OUTER | | 301 | 16856 | 14 (8)| 00:00:01 |
|* 8 | TABLE ACCESS FULL | T_B_UNIVERSITY | 50 | 2050 | 8 (0)| 00:00:01 |
|* 9 | TABLE ACCESS FULL | T_D_EDUCATION | 301 | 4515 | 5 (0)| 00:00:01 |
---------------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
3 - access("A"."USER_ID"="C"."ID"(+))
4 - filter("C"."ISVALID"(+)=1)
5 - access("A"."USER_ID"(+)="E"."USER_ID")
6 - filter("A"."AUDITSTATUS"(+)=1 AND "A"."ISVALID"(+)=1)
7 - access("E"."UNIVERSITY_ID"(+)="U"."ID")
8 - filter("U"."REGION_CODE" LIKE '43%')
9 - filter("E"."ISDEFAULT"(+)=1 AND "E"."ISVALID"(+)=1)