MySQL数据库优化概述三_MySQL
Using where
WHERE 子句将用来限制哪些记录匹配了下一个表或者发送给客户端。除非你特别地想要取得或者检查表种的所有记录,否则的话当查询的 Extra 字段值不是 Using where 并且表连接类型是 ALL 或 index 时可能表示有问题。
如果你想要让查询尽可能的快,那么就应该注意 Extra 字段的值为Using filesort 和 Using temporary 的情况。
你可以通过 EXPLAIN 的结果中 rows 字段的值的乘积大概地知道本次连接表现如何。它可以粗略地告诉我们MySQL在查询过程中会查询多少条记录。如果是使用系统变量 max_join_size 来取得查询结果,这个乘积还可以用来确定会执行哪些多表 SELECT 语句。详情请看"7.5.2 Tuning Server Parameters"。
下面的例子展示了如何通过 EXPLAIN 提供的信息来较大程度地优化多表联合查询的性能。
假设有下面的 SELECT 语句,正打算用 EXPLAIN 来检测:
EXPLAIN SELECT tt.TicketNumber, tt.TimeIn,
tt.ProjectReference, tt.EstimatedShipDate,
tt.ActualShipDate, tt.ClientID,
tt.ServiceCodes, tt.RepetitiveID,
tt.CurrentProcess, tt.CurrentDPPerson,
tt.RecordVolume, tt.DPPrinted, et.COUNTRY,
et_1.COUNTRY, do.CUSTNAME
FROM tt, et, et AS et_1, do
WHERE tt.SubmitTime IS NULL
AND tt.ActualPC = et.EMPLOYID
AND tt.AssignedPC = et_1.EMPLOYID
AND tt.ClientID = do.CUSTNMBR;
在这个例子中,先做以下假设:
Table | Column | Column Type |
tt | ActualPC | CHAR(10) |
tt | AssignedPC | CHAR(10) |
tt | ClientID | CHAR(10) |
et | EMPLOYID | CHAR(15) |
do | CUSTNMBR | CHAR(15) |
Table | Index |
tt | ActualPC |
tt | AssignedPC |
tt | ClientID |
et | EMPLOYID (primary key) |
do | CUSTNMBR (primary key) |
在任何优化措施未采取之前,经过 EXPLAIN 分析的结果显示如下:
table type possible_keys key key_len ref rows Extra et ALL PRIMARY NULL NULL NULL 74 do ALL PRIMARY NULL NULL NULL 2135 et_1 ALL PRIMARY NULL NULL NULL 74 tt ALL AssignedPC, NULL NULL NULL 3872 ClientID, ActualPC range checked for each record (key map: 35) |
由于字段 type 的对于每个表值都是 ALL,这个结果意味着MySQL对所有的表做一个迪卡尔积;这就是说,每条记录的组合。这将需要花很长的时间,因为需要扫描每个表总记录数乘积的总和。在这情况下,它的积是 74 * 2135 * 74 * 3872 = 45,268,558,720 条记录。如果数据表更大的话,你可以想象一下需要多长的时间。
在这里有个问题是当字段定义一样的时候,MySQL就可以在这些字段上更快的是用索引(对 ISAM 类型的表来说,除非字段定义完全一样,否则不会使用索引)。在这个前提下,VARCHAR 和 CHAR是一样的除非它们定义的长度不一致。由于 tt.ActualPC 定义为 CHAR(10),et.EMPLOYID 定义为 CHAR(15),二者长度不一致。
为了解决这个问题,需要用 ALTER TABLE 来加大 ActualPC 的长度从10到15个字符
mysql> ALTER TABLE tt MODIFY ActualPC VARCHAR(15);
现在 tt.ActualPC 和 et.EMPLOYID 都是 VARCHAR(15)
了。再来执行一次 EXPLAIN 语句看看结果:
table type possible_keys key key_len ref rows Extra tt ALL AssignedPC, NULL NULL NULL 3872 Using ClientID, where ActualPC do ALL PRIMARY NULL NULL NULL 2135 range checked for each record (key map: 1) et_1 ALL PRIMARY NULL NULL NULL 74 range checked for each record (key map: 1) et eq_ref PRIMARY PRIMARY 15 tt.ActualPC 1 |
这还不够,它还可以做的更好:现在 rows 值乘积已经少了74倍。这次查询需要用2秒钟。
第二个改变是消除在比较 tt.AssignedPC = et_1.EMPLOYID 和 tt.ClientID = do.CUSTNMBR 中字段的长度不一致问题:
mysql> ALTER TABLE tt MODIFY AssignedPC VARCHAR(15), -> MODIFY ClientID VARCHAR(15); |
现在 EXPLAIN 的结果如下:
table type possible_keys key key_len ref rows Extra et ALL PRIMARY NULL NULL NULL 74 tt ref AssignedPC, ActualPC 15 et.EMPLOYID 52 Using ClientID, where ActualPC et_1 eq_ref PRIMARY PRIMARY 15 tt.AssignedPC 1 do eq_ref PRIMARY PRIMARY 15 tt.ClientID 1 |
这看起来已经是能做的最好的结果了。
遗留下来的问题是,MySQL默认地认为字段tt.ActualPC 的值是均匀分布的,然而表 tt 并非如此。幸好,我们可以很方便的让MySQL分析索引的分布:
mysql> ANALYZE TABLE tt; |
到此为止,表连接已经优化的很完美了,EXPLAIN 的结果如下:

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