在數據庫日常維護中,開發人員是最讓人頭痛的,很多時候都會由於SQL語句寫的有問題導致服務器出問題,導致資源耗盡。最危險的操作就是在做DML操作的時候忘加where條件,導致全表更新,這是作為運維或者DBA的我們改如何處理呢?下面我分別針對update和delete操作忘加where條件導致全表更新的處理方法。
一. update 忘加where條件誤操作恢復數據(binglog格式必須是ROW)
1.創建測試用的數據表
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)
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2.插入測試數據
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.現在需要將id等於2的用戶的地址改為zhuhai,update時沒有添加where條件
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.開始恢復,在線上的話,應該比較復雜,要先進行鎖表,以免數據再次被污染。(鎖表,查看正在寫哪個二進制日志)
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.分析二進制日志,並且在其中找到相關記錄,在更新時是address='zhuhai',我們可以在日志中過濾出來。
[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 */
可以看見里面記錄了每一行的變化,這也是binglog格式要一定是row才行的原因。其中@1,@2,@3,@4,分別對應表中id,name,sex,address字段。相信大家看到這里有點明白了吧,對,沒錯,你猜到了,我們將相關記錄轉換為sql語句,重新導入數據庫。
6.處理分析處理的二進制日志
[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]#
這里sed有點復雜,需要童鞋們好好自己研究研究,這里我就不多說了。
[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]#
將文件中的@1,@2,@3,@4替換為t1表中id,name,sex,address字段,並刪除最后字段的","號
[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.到這里日志就處理好了,現在導入即可(導入數據后,解鎖表);
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>
可以看見數據已經完全恢復,這種方法的優點是快速,方便。
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中去查找相關記錄
[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.將記錄轉換為SQL語句
[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.導入數據,驗證數據完整性
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>
到這里數據就完整回來了。將binglog格式設置為row有利有弊,好處是記錄了每一行的實際變化,在主從復制時也不容易出問題。但是由於記錄每行的變化,會占用大量磁盤,主從復制時帶寬占用會有所消耗。到底是使用row還是mixed,需要在實際工作中自己去衡量,但從整體上來說,binglog的格式設置為row,都是不二的選擇。
總結:
所以在數據庫操作的過程中我們需要格外小心,當然開發那邊我們需要做好權限的控制,不過有一個參數可以解決我們的問題,讓我們不用擔心類似的問題發生:
在[mysql]段落開啟這個參數:
safe-updates
這樣當我們在做DML操作時忘記加where條件時,mysqld服務器是不會執行操作的:
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>