求助：MySQL如何按天分区

求助：MySQL如何按天分区

所谓按天，不过是日期精确到天而已。
错误的按日期分区例子最直观的方法，就是直接用年月日这种日期格式来进行常规的分区：
mysql> create table rms (d date) -> partition by range (d) -> (partition p0 values less than ('1995-01-01'), -> partition p1 VALUES LESS THAN ('2010-01-01'));
上面的例子中，就是直接用"Y-m-d"的格式来对一个table进行分区，可惜想当然往往不能奏效，会得到一个错误信息:ERROR 1064 (42000): VALUES value must be of same type as partition function near '),partition p1 VALUES LESS THAN ('2010-01-01'))' at line 3上述分区方式没有成功，而且明显的不经济，老练的DBA会用整型数值来进行分区：

mysql> CREATE TABLE part_date1 -> ( c1 int default NULL, -> c2 varchar(30) default NULL, -> c3 date default NULL) engine=myisam -> partition by range (cast(date_format(c3,'%Y%m%d') as signed)) -> (PARTITION p0 VALUES LESS THAN (19950101), -> PARTITION p1 VALUES LESS THAN (19960101) , -> PARTITION p2 VALUES LESS THAN (19970101) , -> PARTITION p3 VALUES LESS THAN (19980101) , -> PARTITION p4 VALUES LESS THAN (19990101) , -> PARTITION p5 VALUES LESS THAN (20000101) , -> PARTITION p6 VALUES LESS THAN (20010101) , -> PARTITION p7 VALUES LESS THAN (20020101) , -> PARTITION p8 VALUES LESS THAN (20030101) , -> PARTITION p9 VALUES LESS THAN (20040101) , -> PARTITION p10 VALUES LESS THAN (20100101), -> PARTITION p11 VALUES LESS THAN MAXVALUE );
Query OK, 0 rows affected (0.01 sec)搞定？接着往下分析

mysql> explain partitions -> select count(*) from part_date1 where -> c3> '1995-01-01' and c3 <'1995-12-31'\G *************************** 1. row *************************** id: 1 select_type: SIMPLE table: part_date1 partitions: p0,p1,p2,p3,p4,p5,p6,p7,p8,p9,p10,p11 type: ALL possible_keys: NULL key: NULL key_len: NULL ref: NULL rows: 8100000 Extra: Using where 1 row in set (0.00 sec)
万恶的mysql居然对上面的sql使用全表扫描，而不是按照我们的日期分区分块查询。原文中解释到MYSQL的优化器并不认这种日期形式的分区，花了大量的篇幅来引诱俺走上歧路，过分。正确的日期分区例子mysql优化器支持以下两种内置的日期函数进行分区：
TO_DAYS()YEAR()看个例子：
mysql> CREATE TABLE part_date3 -> ( c1 int default NULL, -> c2 varchar(30) default NULL, -> c3 date default NULL) engine=myisam -> partition by range (to_days(c3)) -> (PARTITION p0 VALUES LESS THAN (to_days('1995-01-01')), -> PARTITION p1 VALUES LESS THAN (to_days('1996-01-01')) , -> PARTITION p2 VALUES LESS THAN (to_days('1997-01-01')) , -> PARTITION p3 VALUES LESS THAN (to_days('1998-01-01')) , -> PARTITION p4 VALUES LESS THAN (to_days('1999-01-01')) , -> PARTITION p5 VALUES LESS THAN (to_days('2000-01-01')) , -> PARTITION p6 VALUES LESS THAN (to_days('2001-01-01')) , -> PARTITION p7 VALUES LESS THAN (to_days('2002-01-01')) , -> PARTITION p8 VALUES LESS THAN (to_days('2003-01-01')) , -> PARTITION p9 VALUES LESS THAN (to_days('2004-01-01')) , -> PARTITION p10 VALUES LESS THAN (to_days('2010-01-01')), -> PARTITION p11 VALUES LESS THAN MAXVALUE );
Query OK, 0 rows affected (0.00 sec)以to_days()函数分区成功，我们分析一下看看：
mysql> explain partitions -> select count(*) from part_date3 where -> c3> date '1995-01-01' and c3 <date '1995-12-31'\G *************************** 1. row *************************** id: 1 select_type: SIMPLE table: part_date3 partitions: p1 type: ALL possible_keys: NULL key: NULL key_len: NULL ref: NULL rows: 808431 Extra: Using where 1 row in set (0.00 sec)可以看到，mysql优化器这次不负众望，仅仅在p1分区进行查询。在这种情况下查询，真的能够带来提升查询效率么？下面分别对这次建立的part_date3和之前分区失败的part_date1做一个查询对比：
mysql> select count(*) from part_date3 where -> c3> date '1995-01-01' and c3 <date '1995-12-31'; +----------+ | count(*) | +----------+ | 805114 | +----------+ 1 row in set (4.11 sec) mysql> select count(*) from part_date1 where -> c3> date '1995-01-01' and c3 <date '1995-12-31'; +----------+ | count(*) | +----------+ | 805114 | +----------+ 1 row in set (40.33 sec)可以看到，分区正确的话query花费时间为4秒，而分区错误则花费时间40秒（相当于没有分区），效率有90％的提升！所以我们千万要正确的使用分区功能，分区后务必用explain验证，这样才能获得真正的性能提升。注意：在mysql5.1中建立分区表的语句中，只能包含下列函数：
ABS()
CEILING() and FLOOR() （在使用这2个函数的建立分区表的前提是使用函数的分区键是INT类型），例如

mysql> CREATE TABLE t (c FLOAT) PARTITION BY LIST( FLOOR(c) )( -> PARTITION p0 VALUES IN (1,3,5), -> PARTITION p1 VALUES IN (2,4,6) -> );; ERROR 1491 (HY000): The PARTITION function returns the wrong type mysql> CREATE TABLE t (c int) PARTITION BY LIST( FLOOR(c) )( -> PARTITION p0 VALUES IN (1,3,5), -> PARTITION p1 VALUES IN (2,4,6) -> ); Query OK, 0 rows affected (0.01 sec) DAY() DAYOFMONTH() DAYOFWEEK() DAYOFYEAR() DATEDIFF() EXTRACT() HOUR() MICROSECOND() MINUTE() MOD() MONTH() QUARTER() SECOND() TIME_TO_SEC() TO_DAYS() WEEKDAY() YEAR() YEARWEEK()2018-01-20