介绍
RANGE分区基于一个给定的连续区间范围,早期版本RANGE主要是基于整数的分区。在5.7版本中DATE、DATETIME列也可以使用RANGE分区,同时在5.5以上的版本提供了基于非整形的RANGE COLUMN分区。RANGE分区必须的连续的且不能重叠。使用
“VALUES LESS THAN ()” 来定义分区区间,非整形的范围值需要使用单引号,并且可以使用MAXVALUE作为分区的最高值。
本文将给大家介绍MySQL 5.5 range分区增加删除处理的相关内容,分享给大家供大家参考学习,下面来看看详细的介绍:
一、删除分区
##查看要处理的分区的数据量,并导出作为备份 mysql> select count(*) from baby_account_change_log where updated_time >'2016-12-01 00:00:00' and updated_time <'2017-01-01 00:00:00'; +----------+ count(*) +----------+ 66252 +----------+ 1 row in set (0.23 sec) ##导出备份 mysql> select * into outfile '/tmp/baby_account_change_log_p1.sql' from baby_account_change_log where updated_time >'2016-12-01 00:00:00' and updated_time <'2017-01-01 00:00:00' limit 100000000000; Query OK, 66252 rows affected (2.71 sec) ##确认要处理分区 mysql> explain partitions select count(*) from baby_account_change_log where updated_time >'2016-12-01 00:00:00' and updated_time <'2017-01-01 00:00:00'; +----+-------------+-------------------------------+------------+-------+---------------+---------+---------+------+-------+--------------------------+ id select_type table partitions type possible_keys key key_len ref rows Extra +----+-------------+-------------------------------+------------+-------+---------------+---------+---------+------+-------+--------------------------+ 1 SIMPLE baby_account_change_log p1 index NULL PRIMARY 8 NULL 66252 Using where; Using index +----+-------------+-------------------------------+------------+-------+---------------+---------+---------+------+-------+--------------------------+ ##删除分区 mysql> alter table baby_account_change_log drop partition p0; Query OK, 0 rows affected (0.01 sec)
二、增加分区
#错误提示删除存储最大值分区 mysql> alter table baby_account_change_log add partition(PARTITION p13 VALUES LESS THAN (unix_timestamp('2017-12-31 23:59:59'))); ERROR 1481 (HY000): MAXVALUE can only be used in last partition definition #删除存储最大值分区 mysql> alter table baby_account_change_log drop partition p12; ##增加新的分区 mysql> alter table baby_account_change_log add partition(PARTITION p12 VALUES LESS THAN (unix_timestamp('2017-12-31 23:59:59')));
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