在数据库日常维护中，开发人员是最让人头痛的，很多时候都会由于SQL语句写的有问题导致服务器出问题，导致资源耗尽。最危险的操作就是在做DML操作的时候忘加where条件，导致全表更新，这是作为运维或者DBA的我们改如何处理呢？下面我分别针对update和delete操作忘加where条件导致全表更新的处理方法。
一. update 忘加where条件误操作恢复数据(binglog格式必须是ROW)
1.创建测试用的数据表
mysql> create table t1 ( -> id int unsigned not null auto_increment, -> name char(20) not null, -> sex enum('f','m') not null default 'm', -> address varchar(30) not null, -> primary key(id) -> ); Query OK, 0 rows affected (0.31 sec)
mysql>
2.插入测试数据
mysql> insert into t1 (name,sex,address)values('daiiy','m','guangzhou'); Query OK, 1 row affected (0.01 sec) mysql> insert into t1 (name,sex,address)values('tom','f','shanghai'); Query OK, 1 row affected (0.00 sec) mysql> insert into t1 (name,sex,address)values('liany','m','beijing'); Query OK, 1 row affected (0.00 sec) mysql> insert into t1 (name,sex,address)values('lilu','m','zhuhai'); Query OK, 1 row affected (0.05 sec) mysql>
3.现在需要将id等于2的用户的地址改为zhuhai，update时没有添加where条件
mysql> select * from t1; +----+-------+-----+-----------+ | id | name | sex | address | +----+-------+-----+-----------+ | 1 | daiiy | m | guangzhou | | 2 | tom | f | shanghai | | 3 | liany | m | beijing | | 4 | lilu | m | zhuhai | +----+-------+-----+-----------+ 4 rows in set (0.01 sec) mysql> update t1 set address='zhuhai'; Query OK, 3 rows affected (0.09 sec) Rows matched: 4 Changed: 3 Warnings: 0 mysql> select * from t1; +----+-------+-----+---------+ | id | name | sex | address | +----+-------+-----+---------+ | 1 | daiiy | m | zhuhai | | 2 | tom | f | zhuhai | | 3 | liany | m | zhuhai | | 4 | lilu | m | zhuhai | +----+-------+-----+---------+ 4 rows in set (0.00 sec) mysql>
4.开始恢复，在线上的话，应该比较复杂，要先进行锁表，以免数据再次被污染。（锁表，查看正在写哪个二进制日志）
mysql> lock tables t1 read ; Query OK, 0 rows affected (0.00 sec) mysql> show master status; +------------------+----------+--------------+------------------+ | File | Position | Binlog_Do_DB | Binlog_Ignore_DB | +------------------+----------+--------------+------------------+ | mysql-bin.000024 | 1852 | | | +------------------+----------+--------------+------------------+ 1 row in set (0.00 sec) mysql>
5.分析二进制日志，并且在其中找到相关记录，在更新时是address=’zhuhai’,我们可以在日志中过滤出来。
[root@localhost mysql]# mysqlbinlog --no-defaults -v -v --base64-output=DECODE-ROWS mysql-bin.000024 | grep -B 15 'zhuhai'
# at 1629 # at 1679 #140305 10:52:24 server id 1 end_log_pos 1679 Table_map: `db01`.`t1` mapped to number 38 #140305 10:52:24 server id 1 end_log_pos 1825 Update_rows: table id 38 flags: STMT_END_F ### UPDATE db01.t1 ### WHERE ### @1=1 /* INT meta=0 nullable=0 is_null=0 */ ### @2='daiiy' /* STRING(60) meta=65084 nullable=0 is_null=0 */ ### @3=2 /* ENUM(1 byte) meta=63233 nullable=0 is_null=0 */ ### @4='guangzhou' /* VARSTRING(90) meta=90 nullable=0 is_null=0 */ ### SET ### @1=1 /* INT meta=0 nullable=0 is_null=0 */ ### @2='daiiy' /* STRING(60) meta=65084 nullable=0 is_null=0 */ ### @3=2 /* ENUM(1 byte) meta=63233 nullable=0 is_null=0 */ ### @4='zhuhai' /* VARSTRING(90) meta=90 nullable=0 is_null=0 */ ### UPDATE db01.t1 ### WHERE ### @1=2 /* INT meta=0 nullable=0 is_null=0 */ ### @2='tom' /* STRING(60) meta=65084 nullable=0 is_null=0 */ ### @3=1 /* ENUM(1 byte) meta=63233 nullable=0 is_null=0 */ ### @4='shanghai' /* VARSTRING(90) meta=90 nullable=0 is_null=0 */ ### SET ### @1=2 /* INT meta=0 nullable=0 is_null=0 */ ### @2='tom' /* STRING(60) meta=65084 nullable=0 is_null=0 */ ### @3=1 /* ENUM(1 byte) meta=63233 nullable=0 is_null=0 */ ### @4='zhuhai' /* VARSTRING(90) meta=90 nullable=0 is_null=0 */ ### UPDATE db01.t1 ### WHERE ### @1=3 /* INT meta=0 nullable=0 is_null=0 */ ### @2='liany' /* STRING(60) meta=65084 nullable=0 is_null=0 */ ### @3=2 /* ENUM(1 byte) meta=63233 nullable=0 is_null=0 */ ### @4='beijing' /* VARSTRING(90) meta=90 nullable=0 is_null=0 */ ### SET ### @1=3 /* INT meta=0 nullable=0 is_null=0 */ ### @2='liany' /* STRING(60) meta=65084 nullable=0 is_null=0 */ ### @3=2 /* ENUM(1 byte) meta=63233 nullable=0 is_null=0 */ ### @4='zhuhai' /* VARSTRING(90) meta=90 nullable=0 is_null=0 */
可以看见里面记录了每一行的变化，这也是binglog格式要一定是row才行的原因。其中@1,@2,@3,@4,分别对应表中id,name,sex,address字段。相信大家看到这里有点明白了吧，对，没错，你猜到了，我们将相关记录转换为sql语句，重新导入数据库。
6.处理分析处理的二进制日志
[root@localhost mysql]# mysqlbinlog --no-defaults -v -v --base64-output=DECODE-ROWS mysql-bin.000024 | sed -n '/# at 1679/,/COMMIT/p' > t1.txt [root@localhost mysql]# cat t1.txt # at 1679 #140305 10:52:24 server id 1 end_log_pos 1679 Table_map: `db01`.`t1` mapped to number 38 #140305 10:52:24 server id 1 end_log_pos 1825 Update_rows: table id 38 flags: STMT_END_F ### UPDATE db01.t1 ### WHERE ### @1=1 /* INT meta=0 nullable=0 is_null=0 */ ### @2='daiiy' /* STRING(60) meta=65084 nullable=0 is_null=0 */ ### @3=2 /* ENUM(1 byte) meta=63233 nullable=0 is_null=0 */ ### @4='guangzhou' /* VARSTRING(90) meta=90 nullable=0 is_null=0 */ ### SET ### @1=1 /* INT meta=0 nullable=0 is_null=0 */ ### @2='daiiy' /* STRING(60) meta=65084 nullable=0 is_null=0 */ ### @3=2 /* ENUM(1 byte) meta=63233 nullable=0 is_null=0 */ ### @4='zhuhai' /* VARSTRING(90) meta=90 nullable=0 is_null=0 */ ### UPDATE db01.t1 ### WHERE ### @1=2 /* INT meta=0 nullable=0 is_null=0 */ ### @2='tom' /* STRING(60) meta=65084 nullable=0 is_null=0 */ ### @3=1 /* ENUM(1 byte) meta=63233 nullable=0 is_null=0 */ ### @4='shanghai' /* VARSTRING(90) meta=90 nullable=0 is_null=0 */ ### SET ### @1=2 /* INT meta=0 nullable=0 is_null=0 */ ### @2='tom' /* STRING(60) meta=65084 nullable=0 is_null=0 */ ### @3=1 /* ENUM(1 byte) meta=63233 nullable=0 is_null=0 */ ### @4='zhuhai' /* VARSTRING(90) meta=90 nullable=0 is_null=0 */ ### UPDATE db01.t1 ### WHERE ### @1=3 /* INT meta=0 nullable=0 is_null=0 */ ### @2='liany' /* STRING(60) meta=65084 nullable=0 is_null=0 */ ### @3=2 /* ENUM(1 byte) meta=63233 nullable=0 is_null=0 */ ### @4='beijing' /* VARSTRING(90) meta=90 nullable=0 is_null=0 */ ### SET ### @1=3 /* INT meta=0 nullable=0 is_null=0 */ ### @2='liany' /* STRING(60) meta=65084 nullable=0 is_null=0 */ ### @3=2 /* ENUM(1 byte) meta=63233 nullable=0 is_null=0 */ ### @4='zhuhai' /* VARSTRING(90) meta=90 nullable=0 is_null=0 */ # at 1825 #140305 10:52:24 server id 1 end_log_pos 1852 Xid = 26 COMMIT/*!*/; [root@localhost mysql]#
这里sed有点复杂，需要童鞋们好好自己研究研究，这里我就不多说了。
[root@localhost mysql]# sed '/WHERE/{:a;N;/SET/!ba;s/\([^\n]*\)\n\(.*\)\n\(.*\)/\3\n\2\n\1/}' t1.txt | sed -r '/WHERE/{:a;N;/@4/!ba;s/### @2.*//g}' | sed 's/### //g;s/\/\*.*/,/g' | sed '/WHERE/{:a;N;/@1/!ba;s/,/;/g};s/#.*//g;s/COMMIT,//g' | sed '/^$/d' > recover.sql
[root@localhost mysql]# cat recover.sql UPDATE db01.t1 SET @1=1 , @2='daiiy' , @3=2 , @4='guangzhou' , WHERE @1=1 ; UPDATE db01.t1 SET @1=2 , @2='tom' , @3=1 , @4='shanghai' , WHERE @1=2 ; UPDATE db01.t1 SET @1=3 , @2='liany' , @3=2 , @4='beijing' , WHERE @1=3 ; [root@localhost mysql]#
将文件中的@1,@2,@3,@4替换为t1表中id，name，sex，address字段，并删除最后字段的”,”号
[root@localhost mysql]# sed -i 's/@1/id/g;s/@2/name/g;s/@3/sex/g;s/@4/address/g' recover.sql [root@localhost mysql]# sed -i -r 's/(address=.*),/\1/g' recover.sql [root@localhost mysql]# cat recover.sql UPDATE db01.t1 SET id=1 , name='daiiy' , sex=2 , address='guangzhou' WHERE id=1 ; UPDATE db01.t1 SET id=2 , name='tom' , sex=1 , address='shanghai' WHERE id=2 ; UPDATE db01.t1 SET id=3 , name='liany' , sex=2 , address='beijing' WHERE id=3 ; [root@localhost mysql]#
7.到这里日志就处理好了，现在导入即可（导入数据后，解锁表）；
mysql> source recover.sql; Query OK, 1 row affected (0.12 sec) Rows matched: 1 Changed: 1 Warnings: 0 Query OK, 1 row affected (0.00 sec) Rows matched: 1 Changed: 1 Warnings: 0 Query OK, 1 row affected (0.01 sec) Rows matched: 1 Changed: 1 Warnings: 0 mysql> select * from t1; +----+-------+-----+-----------+ | id | name | sex | address | +----+-------+-----+-----------+ | 1 | daiiy | m | guangzhou | | 2 | tom | f | shanghai | | 3 | liany | m | beijing | | 4 | lilu | m | zhuhai | +----+-------+-----+-----------+ 4 rows in set (0.00 sec) mysql>
可以看见数据已经完全恢复，这种方法的优点是快速，方便。
二. delete 忘加where条件误删除恢复(binglog格式必须是ROW) 其实这和update忘加条件差不多，不过这处理更简单,这里就用上面那张表做测试吧 1.模拟误删除数据
mysql> select * from t1; +----+-------+-----+-----------+ | id | name | sex | address | +----+-------+-----+-----------+ | 1 | daiiy | m | guangzhou | | 2 | tom | f | shanghai | | 3 | liany | m | beijing | | 4 | lilu | m | zhuhai | +----+-------+-----+-----------+ 4 rows in set (0.00 sec) mysql> delete from t1; Query OK, 4 rows affected (0.03 sec) mysql> select * from t1; Empty set (0.00 sec) mysql>
2.在binglog中去查找相关记录
[root@localhost mysql]# mysqlbinlog --no-defaults --base64-output=decode-rows -v -v mysql-bin.000024 | sed -n '/### DELETE FROM db01.t1/,/COMMIT/p' > delete.txt [root@localhost mysql]# cat delete.txt ### DELETE FROM db01.t1 ### WHERE ### @1=1 /* INT meta=0 nullable=0 is_null=0 */ ### @2='daiiy' /* STRING(60) meta=65084 nullable=0 is_null=0 */ ### @3=2 /* ENUM(1 byte) meta=63233 nullable=0 is_null=0 */ ### @4='guangzhou' /* VARSTRING(90) meta=90 nullable=0 is_null=0 */ ### DELETE FROM db01.t1 ### WHERE ### @1=2 /* INT meta=0 nullable=0 is_null=0 */ ### @2='tom' /* STRING(60) meta=65084 nullable=0 is_null=0 */ ### @3=1 /* ENUM(1 byte) meta=63233 nullable=0 is_null=0 */ ### @4='shanghai' /* VARSTRING(90) meta=90 nullable=0 is_null=0 */ ### DELETE FROM db01.t1 ### WHERE ### @1=3 /* INT meta=0 nullable=0 is_null=0 */ ### @2='liany' /* STRING(60) meta=65084 nullable=0 is_null=0 */ ### @3=2 /* ENUM(1 byte) meta=63233 nullable=0 is_null=0 */ ### @4='beijing' /* VARSTRING(90) meta=90 nullable=0 is_null=0 */ ### DELETE FROM db01.t1 ### WHERE ### @1=4 /* INT meta=0 nullable=0 is_null=0 */ ### @2='lilu' /* STRING(60) meta=65084 nullable=0 is_null=0 */ ### @3=2 /* ENUM(1 byte) meta=63233 nullable=0 is_null=0 */ ### @4='zhuhai' /* VARSTRING(90) meta=90 nullable=0 is_null=0 */ # at 2719 #140305 11:41:00 server id 1 end_log_pos 2746 Xid = 78 COMMIT/*!*/; [root@localhost mysql]#
3.将记录转换为SQL语句
[root@localhost mysql]# cat delete.txt | sed -n '/###/p' | sed 's/### //g;s/\/\*.*/,/g;s/DELETE FROM/INSERT INTO/g;s/WHERE/SELECT/g;' | sed -r 's/(@4.*),/\1;/g' | sed 's/@[1-9]=//g' > t1.sql [root@localhost mysql]# cat t1.sql INSERT INTO db01.t1 SELECT 1 , 'daiiy' , 2 , 'guangzhou' ; INSERT INTO db01.t1 SELECT 2 , 'tom' , 1 , 'shanghai' ; INSERT INTO db01.t1 SELECT 3 , 'liany' , 2 , 'beijing' ; INSERT INTO db01.t1 SELECT 4 , 'lilu' , 2 , 'zhuhai' ; [root@localhost mysql]#
4.导入数据，验证数据完整性
mysql> source t1.sql; Query OK, 1 row affected (0.00 sec) Records: 1 Duplicates: 0 Warnings: 0 Query OK, 1 row affected (0.02 sec) Records: 1 Duplicates: 0 Warnings: 0 Query OK, 1 row affected (0.02 sec) Records: 1 Duplicates: 0 Warnings: 0 Query OK, 1 row affected (0.01 sec) Records: 1 Duplicates: 0 Warnings: 0 mysql> select * from t1; ERROR 1046 (3D000): No database selected mysql> select * from db01.t1; +----+-------+-----+-----------+ | id | name | sex | address | +----+-------+-----+-----------+ | 1 | daiiy | m | guangzhou | | 2 | tom | f | shanghai | | 3 | liany | m | beijing | | 4 | lilu | m | zhuhai | +----+-------+-----+-----------+ 4 rows in set (0.00 sec) mysql>
到这里数据就完整回来了。将binglog格式设置为row有利有弊，好处是记录了每一行的实际变化，在主从复制时也不容易出问题。但是由于记录每行的变化，会占用大量磁盘，主从复制时带宽占用会有所消耗。到底是使用row还是mixed，需要在实际工作中自己去衡量，但从整体上来说，binglog的格式设置为row，都是不二的选择。
总结：
所以在数据库操作的过程中我们需要格外小心，当然开发那边我们需要做好权限的控制，不过有一个参数可以解决我们的问题，让我们不用担心类似的问题发生：
在[mysql]段落开启这个参数：
safe-updates
这样当我们在做DML操作时忘记加where条件时，mysqld服务器是不会执行操作的：
mysql> select * from t1; +----+------------------+ | id | name | +----+------------------+ | 1 | yayun | | 2 | atlas | | 3 | mysql | | 6 | good yayun heheh | +----+------------------+ 4 rows in set (0.00 sec) mysql> delete from t1; ERROR 1175 (HY000): You are using safe update mode and you tried to update a table without a WHERE that uses a KEY column mysql>
