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mysql 5.1已经到了beta版,官方网站上也陆续有一些文章介绍,比如上次看到的Improving Database Performance with Partitioning。在使用分区的前提下,可以用mysql实现非常大的数据量存储。今天在mysql的站上又看到一篇进阶的文章 —— 按日期分区存储。如果能够实现按日期分区,这对某些时效性很强的数据存储是相当实用的功能。下面是从这篇文章中摘录的一些内容。

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:

CODE:
  1. mysql>  create table rms (d date)
  2.     ->  partition by range (d)
  3.     -> (partition p0 values less than ('1995-01-01'),
  4.     ->  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:

CODE:
  1. mysql> CREATE TABLE part_date1
  2.     ->      (  c1 int default NULL,
  3.     ->  c2 varchar(30) default NULL,
  4.     ->  c3 date default NULL) engine=myisam
  5.     ->      partition by range (cast(date_format(c3,'%Y%m%d') as signed))
  6.     -> (PARTITION p0 VALUES LESS THAN (19950101),
  7.     -> PARTITION p1 VALUES LESS THAN (19960101) ,
  8.     -> PARTITION p2 VALUES LESS THAN (19970101) ,
  9.     -> PARTITION p3 VALUES LESS THAN (19980101) ,
  10.     -> PARTITION p4 VALUES LESS THAN (19990101) ,
  11.     -> PARTITION p5 VALUES LESS THAN (20000101) ,
  12.     -> PARTITION p6 VALUES LESS THAN (20010101) ,
  13.     -> PARTITION p7 VALUES LESS THAN (20020101) ,
  14.     -> PARTITION p8 VALUES LESS THAN (20030101) ,
  15.     -> PARTITION p9 VALUES LESS THAN (20040101) ,
  16.     -> PARTITION p10 VALUES LESS THAN (20100101),
  17.     -> PARTITION p11 VALUES LESS THAN MAXVALUE );
  18. Query OK, 0 rows affected (0.01 sec)

 

搞定?接着往下分析

CODE:
  1. mysql> explain partitions
  2.     -> select count(*) from part_date1 where
  3.     ->      c3> date '1995-01-01' and c3 <date '1995-12-31'\G
  4. *************************** 1. row ***************************
  5.            id: 1
  6.   select_type: SIMPLE
  7.         table: part_date1
  8.    partitions: p0,p1,p2,p3,p4,p5,p6,p7,p8,p9,p10,p11
  9.          type: ALL
  10. possible_keys: NULL
  11.           key: NULL
  12.       key_len: NULL
  13.           ref: NULL
  14.          rows: 8100000
  15.         Extra: Using where
  16. 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:

CODE:
  1. mysql> CREATE TABLE part_date3
  2.     ->      (  c1 int default NULL,
  3.     ->  c2 varchar(30) default NULL,
  4.     ->  c3 date default NULL) engine=myisam
  5.     ->      partition by range (to_days(c3))
  6.     -> (PARTITION p0 VALUES LESS THAN (to_days('1995-01-01')),
  7.     -> PARTITION p1 VALUES LESS THAN (to_days('1996-01-01')) ,
  8.     -> PARTITION p2 VALUES LESS THAN (to_days('1997-01-01')) ,
  9.     -> PARTITION p3 VALUES LESS THAN (to_days('1998-01-01')) ,
  10.     -> PARTITION p4 VALUES LESS THAN (to_days('1999-01-01')) ,
  11.     -> PARTITION p5 VALUES LESS THAN (to_days('2000-01-01')) ,
  12.     -> PARTITION p6 VALUES LESS THAN (to_days('2001-01-01')) ,
  13.     -> PARTITION p7 VALUES LESS THAN (to_days('2002-01-01')) ,
  14.     -> PARTITION p8 VALUES LESS THAN (to_days('2003-01-01')) ,
  15.     -> PARTITION p9 VALUES LESS THAN (to_days('2004-01-01')) ,
  16.     -> PARTITION p10 VALUES LESS THAN (to_days('2010-01-01')),
  17.     -> PARTITION p11 VALUES LESS THAN MAXVALUE );
  18. 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:

CODE:
  1. mysql> explain partitions
  2.     -> select count(*) from part_date3 where
  3.     ->      c3> date '1995-01-01' and c3 <date '1995-12-31'\G
  4. *************************** 1. row ***************************
  5.            id: 1
  6.   select_type: SIMPLE
  7.         table: part_date3
  8.    partitions: p1
  9.          type: ALL
  10. possible_keys: NULL
  11.           key: NULL
  12.       key_len: NULL
  13.           ref: NULL
  14.          rows: 808431
  15.         Extra: Using where
  16. 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:

CODE:
  1. mysql> select count(*) from part_date3 where
  2.     ->      c3> date '1995-01-01' and c3 <date '1995-12-31';
  3. +----------+
  4. | count(*) |
  5. +----------+
  6.  805114 |
  7. +----------+
  8. 1 row in set (4.11 sec)
  9.  
  10. mysql> select count(*) from part_date1 where
  11.     ->      c3> date '1995-01-01' and c3 <date '1995-12-31';
  12. +----------+
  13. | count(*) |
  14. +----------+
  15.  805114 |
  16. +----------+
  17. 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()

posted on 2016-06-07 18:06 SIMONE 阅读(237) 评论(0)  编辑  收藏 所属分类: mysql

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