1. checksum table.
checksum table 会对表一行一行进行计算，直到计算出最终的 checksum 结果。比如对表 n4 进行校验（记录数 157W，大小为 4G）
[ytt]>desc n4;
+-------+--------------+------+-----+---------+-------+
| Field | Type | Null | Key | Default | Extra |
+-------+--------------+------+-----+---------+-------+
| id | int(11) | YES | | NULL | |
| r1 | char(36) | YES | | NULL | |
| r2 | varchar(100) | YES | | NULL | |
| r3 | datetime | YES | | NULL | |
| r4 | text | YES | | NULL | |
+-------+--------------+------+-----+---------+-------+
5 rows in set (0.00 sec)
[ytt]>select count(*) from n4;
+----------+
| count(*) |
+----------+
| 1572864 |
+----------+
1 row in set (6.89 sec)
[ytt]>checksum table n4;
+--------+-----------+
| Table | Checksum |
+--------+-----------+
| ytt.n4 | 874125175 |
+--------+-----------+
1 row in set (8.24 sec)
我自己笔记本上的测试结果，速度挺快。
不过 checksum 的限制比较多。罗列如下，
A、不能对视图进行校验。
[ytt]>checksum table v_n3;
+----------+----------+
| Table | Checksum |
+----------+----------+
| ytt.v_n3 | NULL |
+----------+----------+
1 row in set, 1 warning (0.00 sec)
[ytt]>show warnings;
+-------+------+------------------------------+
| Level | Code | Message |
+-------+------+------------------------------+
| Error | 1347 | 'ytt.v_n3' is not BASE TABLE |
+-------+------+------------------------------+
1 row in set (0.00 sec)
B、字段顺序不同，校验结果也会不一致。
[ytt]>desc n3;
+-------+---------+------+-----+---------+-------+
| Field | Type | Null | Key | Default | Extra |
+-------+---------+------+-----+---------+-------+
| id | int(11) | NO | | NULL | |
| r1 | int(11) | YES | | NULL | |
+-------+---------+------+-----+---------+-------+
2 rows in set (0.00 sec)
[ytt]>desc n5;
+-------+---------+------+-----+---------+-------+
| Field | Type | Null | Key | Default | Extra |
+-------+---------+------+-----+---------+-------+
| r1 | int(11) | YES | | NULL | |
| id | int(11) | NO | | NULL | |
+-------+---------+------+-----+---------+-------+
2 rows in set (0.00 sec)
[ytt]>checksum table n3,n5;
+--------+------------+
| Table | Checksum |
+--------+------------+
| ytt.n3 | 1795175396 |
| ytt.n5 | 838415794 |
+--------+------------+
2 rows in set (0.00 sec)
C、CHAR(100) 和 VARCHAR(100) 存储相同的字符，校验结果也会不一致。
[ytt]>desc n6;
+-------+--------------+------+-----+---------+-------+
| Field | Type | Null | Key | Default | Extra |
+-------+--------------+------+-----+---------+-------+
| id | int(11) | NO | | NULL | |
| r1 | int(11) | YES | | NULL | |
| s1 | varchar(100) | YES | | NULL | |
+-------+--------------+------+-----+---------+-------+
3 rows in set (0.00 sec)
[ytt]>desc n3;
+-------+-----------+------+-----+---------+-------+
| Field | Type | Null | Key | Default | Extra |
+-------+-----------+------+-----+---------+-------+
| id | int(11) | NO | | NULL | |
| r1 | int(11) | YES | | NULL | |
| s1 | char(100) | YES | | NULL | |
+-------+-----------+------+-----+---------+-------+
3 rows in set (0.00 sec)
[ytt]>select * from n6;
Empty set (0.00 sec)
[ytt]>insert into n6 select * from n3;
Query OK, 8 rows affected (0.01 sec)
Records: 8 Duplicates: 0 Warnings: 0
[ytt]>checksum table n3,n6;
+--------+------------+
| Table | Checksum |
+--------+------------+
| ytt.n3 | 2202684200 |
| ytt.n6 | 455222236 |
+--------+------------+
2 rows in set (0.00 sec)
D、在执行 checksum 同时，会对表所有行加共享读锁。
E、还有就是 MySQL 版本不同，有可能校验结果不一致。比如手册上说的，MySQL 5.6.5 之后的版本对时间类型的存储格式有变化，导致校验结果不一致。那 checksum 的 限制这么多，我们是不是有其方法来突破所有限制呢？比如说可以模拟 checksum table 的原理来手工计算。
2. 自己计算 checksum 值。
这里用了 MySQL 自身的几个特性：session 变量；通用表达式；窗口函数以及 MySQL 的 concat_ws 函数实现非常简单。比如我们用 sha 函数来计算校验值。
[ytt]>set @crc='';
Query OK, 0 rows affected (0.00 sec)
[ytt]>
[ytt]>with ytt (r,rn) as
-> (
-> select @crc:= sha(concat_ws('#',@crc,id,r1,r2,r3,r4)) as r, row_number() over() as rn
-> from n4
-> )
-> select 'n4' tablename, r checksum from ytt where rn = 1572864 ;
+-----------+------------------------------------------+
| tablename | checksum |
+-----------+------------------------------------------+
| n4 | a9711af93399e0d195a53f4148adea46ab684d30 |
+-----------+------------------------------------------+
1 row in set, 1 warning (16.46 sec)
如果在 MySQL 老版本运行，可以利用 MySQL 的黑洞引擎，改下 SQL 如下：
[ytt]>create table tmp_checksum (checksum varchar(100)) engine blackhole;
Query OK, 0 rows affected (0.08 sec)
[ytt]>
[ytt]>set @crc='';insert into tmp_checksum
Query OK, 0 rows affected (0.00 sec)
-> select @crc:= sha(concat_ws('#',@crc,id,r1,r2,r3,r4)) as r from n4;
Query OK, 1572864 rows affected, 1 warning (20.11 sec)
Records: 1572864 Duplicates: 0 Warnings: 1
[ytt]>select 'n4' tablename,@crc checksum;
+-----------+------------------------------------------+
| tablename | checksum |
+-----------+------------------------------------------+
| n4 | a9711af93399e0d195a53f4148adea46ab684d30 |
+-----------+------------------------------------------+
1 row in set (0.00 sec)
总结
对于表要计算校验数据一致性的需求，首选第二种自己写 SQL 的方法。