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這篇文章將為大家詳細(xì)講解有關(guān) Mysql 在 LONGTEXT 字段上作 like 操作的消耗是怎樣的,文章內(nèi)容質(zhì)量較高,因此丸趣 TV 小編分享給大家做個(gè)參考,希望大家閱讀完這篇文章后對(duì)相關(guān)知識(shí)有一定的了解。
# Mysql 5140 @ RHEL 5u4 X86_64
# 先提供一些表的信息:
===================================================================
root@127.0.0.1 : trac_apsara 17:18:46 show create table wiki G
*************************** 1. row ***************************
Table: wiki
Create Table: CREATE TABLE `wiki` (
`name` longtext COLLATE utf8_bin,
`version` int(11) DEFAULT NULL,
`time` bigint(20) DEFAULT NULL,
`author` longtext COLLATE utf8_bin,
`ipnr` longtext COLLATE utf8_bin,
`text` longtext COLLATE utf8_bin,
`comment` longtext COLLATE utf8_bin,
`readonly` int(11) DEFAULT NULL,
KEY `wiki_time_idx` (`time`),
KEY `name_ver_ind` (`name`(200),`version`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8 COLLATE=utf8_bin
1 row in set (0.00 sec)
root@127.0.0.1 : trac_apsara 17:19:04 select count(*) from wiki;
+———-+
| count(*) |
+———-+
| 76514 |
+———-+
1 row in set (0.03 sec)
root@127.0.0.1 : trac_apsara 17:19:08 select count(distinct name) from wiki;
+———————–+
| count(distinct name) |
+———————–+
| 40369 |
+———————–+
1 row in set (0.59 sec)
root@127.0.0.1 : trac_apsara 17:19:21 show variables like innodb_buffer%
+————————-+————+
| Variable_name | Value |
+————————-+————+
| innodb_buffer_pool_size | 1073741824 |
+————————-+————+
1 row in set (0.00 sec)
root@127.0.0.1 : trac_apsara 17:21:08 show table status like wiki G
*************************** 1. row ***************************
Name: wiki
Engine: InnoDB
Version: 10
Row_format: Compact
Rows: 336009
Avg_row_length: 4458
Data_length: 1498120192
Max_data_length: 0
Index_length: 10551296
Data_free: 7340032
Auto_increment: NULL
Create_time: 2010-09-29 14:49:20
Update_time: NULL
Check_time: NULL
Collation: utf8_bin
Checksum: NULL
Create_options:
Comment:
1 row in set (0.01 sec)
===================================================================
# 下面我們來(lái)看一下 SQL 和數(shù)據(jù):
## SQL1 :
SELECT w1.name,w1.time,w1.author,w1.text
FROM wiki w1,
(SELECT name,max(version) AS ver FROM wiki GROUP BY name) w2
WHERE w1.version = w2.ver AND w1.name = w2.name
AND (w1.name LIKE %RpcRequestPtr% ESCAPE /
OR w1.author LIKE %RpcRequestPtr% ESCAPE /
OR w1.text LIKE %RpcRequestPtr% ESCAPE /
);
## SQL2 :
SELECT w1.name,w1.time,w1.author,w1.text
FROM wiki w1,
(SELECT name,max(version) AS ver FROM wiki GROUP BY name) w2
WHERE w1.version = w2.ver AND w1.name = w2.name
AND (w1.name LIKE %RpcRequestPtr% ESCAPE /
OR w1.author LIKE %RpcRequestPtr% ESCAPE /
###### OR w1.text LIKE %RpcRequestPtr% ESCAPE /
);
兩個(gè) SQL 僅一個(gè) WHERE 條件之差。
root@127.0.0.1 : trac_apsara 17:24:08 explain SELECT w1.name,w1.time,w1.author,w1.text
– FROM wiki w1,
– (SELECT name,max(version) AS ver FROM wiki GROUP BY name) w2
– WHERE w1.version = w2.ver AND w1.name = w2.name
– AND (w1.name LIKE %RpcRequestPtr% ESCAPE /
– OR w1.author LIKE %RpcRequestPtr% ESCAPE /
– OR w1.text LIKE %RpcRequestPtr% ESCAPE /
– );
+—-+————-+————+——+—————+————–+———+—————-+——–+———————————+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+—-+————-+————+——+—————+————–+———+—————-+——–+———————————+
| 1 | PRIMARY || ALL | NULL | NULL | NULL | NULL | 40369 | |
| 1 | PRIMARY | w1 | ref | name_ver_ind | name_ver_ind | 608 | w2.name,w2.ver | 3 | Using where |
| 2 | DERIVED | wiki | ALL | NULL | NULL | NULL | NULL | 445724 | Using temporary; Using filesort |
+—-+————-+————+——+—————+————–+———+—————-+——–+———————————+
3 rows in set (1.04 sec)
root@127.0.0.1 : trac_apsara 17:22:26 explain SELECT w1.name,w1.time,w1.author,w1.text
– FROM wiki w1,
– (SELECT name,max(version) AS ver FROM wiki GROUP BY name) w2
– WHERE w1.version = w2.ver AND w1.name = w2.name
– AND (w1.name LIKE %RpcRequestPtr% ESCAPE /
– OR w1.author LIKE %RpcRequestPtr% ESCAPE /
– # OR w1.text LIKE %RpcRequestPtr% ESCAPE /
– );
+—-+————-+————+——+—————+————–+———+—————-+——–+———————————+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+—-+————-+————+——+—————+————–+———+—————-+——–+———————————+
| 1 | PRIMARY || ALL | NULL | NULL | NULL | NULL | 40369 | |
| 1 | PRIMARY | w1 | ref | name_ver_ind | name_ver_ind | 608 | w2.name,w2.ver | 3 | Using where |
| 2 | DERIVED | wiki | ALL | NULL | NULL | NULL | NULL | 445724 | Using temporary; Using filesort |
+—-+————-+————+——+—————+————–+———+—————-+——–+———————————+
3 rows in set (1.03 sec)
### 從執(zhí)行計(jì)劃來(lái)看,兩個(gè) SQL 一模一樣;處理的行數(shù)也是一樣的;
root@127.0.0.1 : trac_apsara 17:25:39 reset query cache ;
Query OK, 0 rows affected (0.00 sec)
root@127.0.0.1 : trac_apsara 17:25:52 SELECT w1.name,w1.time,w1.author,w1.text
– FROM wiki w1,
– (SELECT name,max(version) AS ver FROM wiki GROUP BY name) w2
– WHERE w1.version = w2.ver AND w1.name = w2.name
– AND (w1.name LIKE %RpcRequestPtr% ESCAPE /
– OR w1.author LIKE %RpcRequestPtr% ESCAPE /
– # OR w1.text LIKE %RpcRequestPtr% ESCAPE /
– );
Empty set (1.31 sec)
root@127.0.0.1 : trac_apsara 17:26:12 reset query cache ;
Query OK, 0 rows affected (0.00 sec)
root@127.0.0.1 : trac_apsara 17:26:15 SELECT w1.name,w1.time,w1.author,w1.text
– FROM wiki w1,
– (SELECT name,max(version) AS ver FROM wiki GROUP BY name) w2
– WHERE w1.version = w2.ver AND w1.name = w2.name
– AND (w1.name LIKE %RpcRequestPtr% ESCAPE /
– OR w1.author LIKE %RpcRequestPtr% ESCAPE /
– OR w1.text LIKE %RpcRequestPtr% ESCAPE /
– );
13 rows in set (3.50 sec)
## 從執(zhí)行時(shí)間來(lái)看,
## SQL1 : 3.50 sec , SQL2: 1.31 sec
## 從這里我們基本可以判斷出來(lái),MYSQL 用了 2.19 sec 在內(nèi)存中處理 40369 次 TEXT 字段的 LIKE 模糊查詢(xún)操作;
## 而從 WIKI 表 INDEX 查詢(xún) 40369 次,卻只用了 1.31 秒(可能更少),當(dāng)然數(shù)據(jù)已經(jīng)在 CACHE 里。
## 我們以后做 SQL 可要注意了。不光是讀硬盤(pán)會(huì)消耗時(shí)間,在內(nèi)存中的 LIKE 模糊查詢(xún)操作,也很費(fèi)時(shí)間;
關(guān)于 Mysql 在 LONGTEXT 字段上作 like 操作的消耗是怎樣的就分享到這里了,希望以上內(nèi)容可以對(duì)大家有一定的幫助,可以學(xué)到更多知識(shí)。如果覺(jué)得文章不錯(cuò),可以把它分享出去讓更多的人看到。