时间:2021-07-01 10:21:17 帮助过:26人阅读
生成数据,本次准备生成1kw条记录
/* 调用存储过程 */ mysql> call sp_createNum(10000000); Query OK, 1611392 rows affected (32.07 sec)
如果逐条循环,那时间相当长,大家可以自行测试,参考链接 效率提升16800倍的连续整数生成方法
生成3张表innodb表,如下:
nums_1表只有字符串主键字段
/* 生成只有一个字符串类型字段主键的表nums_1 */ mysql> create table nums_1 (p1 varchar(32) primary key ) engine=innodb; Query OK, 0 rows affected (0.01 sec) /* 导入数据,将id通过md5函数转换为字符串 */ mysql> insert into nums_1 select md5(id) from nums; Query OK, 10000000 rows affected (1 min 12.63 sec) Records: 10000000 Duplicates: 0 Warnings: 0
nums_2表有5个字段 ,其中主键为字符串类型字段的p1,其他字段为整型的id,非空的c1,可为空的c2,可为空的c3。
其中c1,c2字段内容完全一致,差别是字段约束不一样(c1不可为空,c2可为空),c3与c1,c2的差别在于c1中aa开头的值在c3中为null,其他内容一样。
/* 创建表nums_2 */ mysql> create table nums_2(p1 varchar(32) primary key ,id int ,c1 varchar(10) not null, c2 varchar(10),c3 varchar(10)) engine=innodb; Query OK, 0 rows affected (1.03 sec) /*导入数据 */ mysql> insert into nums_2(id,p1,c1,c2,c3) select id,md5(id),left(md5(id),10),left(md5(id),10),if(,left(md5(id),10) like ‘aa%‘,null,,left(md5(id),10)) from nums; Query OK, 10000000 rows affected (5 min 6.68 sec) Records: 10000000 Duplicates: 0 Warnings: 0
nums_3表的内容与nums_2完全一样,区别在于主键字段不一样,c3表为整型的id
/* 创建表nums_3 */ mysql> create table nums_3(p1 varchar(32) ,id int primary key ,c1 varchar(10) not null, c2 varchar(10),c3 varchar(10)) engine=innodb; Query OK, 0 rows affected (0.01 sec) /* 因为内容完全一致,直接从nums_2 中导入 */ mysql> insert into nums_3 select * from nums_2; Query OK, 10000000 rows affected (3 min 18.81 sec) Records: 10000000 Duplicates: 0 Warnings: 0
再创建一张MyISAM的表,表结构及内容均与nums_2也一致,只是引擎为MyISAM。
/* 创建MyISAM引擎的nums_4表*/ mysql> create table nums_4(p1 varchar(32) not null primary key ,id int ,c1 varchar(10) not null, c2 varchar(10),c3 varchar(10)) engine=MyISAM; Query OK, 0 rows affected (0.00 sec) /* 直接从nums_2表导入数据 */ mysql> insert into nums_4 select * from nums_2; Query OK, 10000000 rows affected (3 min 16.78 sec) Records: 10000000 Duplicates: 0 Warnings: 0
查询一张表的数据量有如下几种:
查询大致数据量,可以查统计信息,2.1中会介绍具体方法
精确查找数据量,则可以通过count(主键字段),count(*), count(1) [这里的1可以替换为任意常量]
如果只是查一张表大致有多少数据,尤其是很大的表 只是查询其表属于什么量级的(百万、千万还是上亿条),可以直接查询统计信息,查询方式有如下几种:
查询索引信息,其中Cardinality 为大致数据量(查看主键PRIMARY行的值,如果为多列的复合主键,则查看最后一列的Cardinality 值)
mysql> show index from nums_2; +--------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+ | Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment | Index_comment | +--------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+ | nums_2 | 0 | PRIMARY | 1 | p1 | A | 9936693 | NULL | NULL | | BTREE | | | +--------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+ 1 row in set (0.00 sec)
查看表状态,其中Rows为大致数据量
mysql> show table status like ‘nums_2‘; +--------+--------+---------+------------+---------+----------------+-------------+-----------------+--------------+-----------+----------------+---------------------+-------------+------------+-----------------+----------+----------------+---------+ | Name | Engine | Version | Row_format | Rows | Avg_row_length | Data_length | Max_data_length | Index_length | Data_free | Auto_increment | Create_time | Update_time | Check_time | Collation | Checksum | Create_options | Comment | +--------+--------+---------+------------+---------+----------------+-------------+-----------------+--------------+-----------+----------------+---------------------+-------------+------------+-----------------+----------+----------------+---------+ | nums_2 | InnoDB | 10 | Dynamic | 9936693 | 111 | 1105182720 | 0 | 2250178560 | 4194304 | NULL | 2020-04-04 19:31:34 | NULL | NULL | utf8_general_ci | NULL | | | +--------+--------+---------+------------+---------+----------------+-------------+-----------------+--------------+-----------+----------------+---------------------+-------------+------------+-----------------+----------+----------------+---------+ 1 row in set (0.00 sec)
直接查看STATISTICS或TABLES表,内容与查看索引信息或表状态类似,其中TABLE_ROWS的内容为大致的数据量
mysql> select * from information_schema.tables where table_schema=‘testdb‘ and table_name like ‘nums_2‘; +---------------+--------------+------------+------------+--------+---------+------------+------------+----------------+-------------+-----------------+--------------+-----------+----------------+---------------------+-------------+------------+-----------------+----------+----------------+---------------+ | TABLE_CATALOG | TABLE_SCHEMA | TABLE_NAME | TABLE_TYPE | ENGINE | VERSION | ROW_FORMAT | TABLE_ROWS | AVG_ROW_LENGTH | DATA_LENGTH | MAX_DATA_LENGTH | INDEX_LENGTH | DATA_FREE | AUTO_INCREMENT | CREATE_TIME | UPDATE_TIME | CHECK_TIME | TABLE_COLLATION | CHECKSUM | CREATE_OPTIONS | TABLE_COMMENT | +---------------+--------------+------------+------------+--------+---------+------------+------------+----------------+-------------+-----------------+--------------+-----------+----------------+---------------------+-------------+------------+-----------------+----------+----------------+---------------+ | def | testdb | nums_2 | BASE TABLE | InnoDB | 10 | Dynamic | 9936693 | 111 | 1105182720 | 0 | 2250178560 | 4194304 | NULL | 2020-04-04 19:31:34 | NULL | NULL | utf8_general_ci | NULL | | | +---------------+--------------+------------+------------+--------+---------+------------+------------+----------------+-------------+-----------------+--------------+-----------+----------------+---------------------+-------------+------------+-----------------+----------+----------------+---------------+ 1 row in set (0.00 sec)
注意:
mysql> select * from information_schema.tables where table_schema=‘testdb‘ and table_name like ‘nums_4‘; +---------------+--------------+------------+------------+--------+---------+------------+------------+----------------+-------------+-----------------+--------------+-----------+----------------+---------------------+---------------------+---------------------+-----------------+----------+----------------+---------------+ | TABLE_CATALOG | TABLE_SCHEMA | TABLE_NAME | TABLE_TYPE | ENGINE | VERSION | ROW_FORMAT | TABLE_ROWS | AVG_ROW_LENGTH | DATA_LENGTH | MAX_DATA_LENGTH | INDEX_LENGTH | DATA_FREE | AUTO_INCREMENT | CREATE_TIME | UPDATE_TIME | CHECK_TIME | TABLE_COLLATION | CHECKSUM | CREATE_OPTIONS | TABLE_COMMENT | +---------------+--------------+------------+------------+--------+---------+------------+------------+----------------+-------------+-----------------+--------------+-----------+----------------+---------------------+---------------------+---------------------+-----------------+----------+----------------+---------------+ | def | testdb | nums_4 | BASE TABLE | MyISAM | 10 | Dynamic | 10000000 | 75 | 759686336 | 281474976710655 | 854995968 | 0 | NULL | 2020-04-04 19:20:23 | 2020-04-04 19:21:45 | 2020-04-04 19:23:45 | utf8_general_ci | NULL | | | +---------------+--------------+------------+------------+--------+---------+------------+------------+----------------+-------------+-----------------+--------------+-----------+----------------+---------------------+---------------------+---------------------+-----------------+----------+----------------+---------------+ 1 row in set (0.00 sec)
因为2.1中innodb的表查询的结果都是统计值,非准备值,实际工作中大多数情况下需要统计精确值,那么查询精确值的方法有如下几种,且所有引擎的表都适用。
count(主键)
mysql> select count(p1) from nums_2; +-----------+ | count(p1) | +-----------+ | 10000000 | +-----------+ 1 row in set (1.60 sec)
count(1)
其中的1可以是任意常量,例如 count(2),count(‘a‘)等
mysql> select count(1) from nums_2; +----------+ | count(1) | +----------+ | 10000000 | +----------+ 1 row in set (1.45 sec)
count(*)
mysql> select count(*) from nums_2; +----------+ | count(*) | +----------+ | 10000000 | +----------+ 1 row in set (1.52 sec)
对比 count(主键) count(1) count(*) count(非空字段) count(可为空字段) 性能对比
如果想精确查询一张MyISAM表的数据量,使用 count(主键) count(1) count(*) 效率均一致,直接查出准确结果,耗时几乎为0s
mysql> select count(p1) from nums_4; +-----------+ | count(p1) | +-----------+ | 10000000 | +-----------+ 1 row in set (0.00 sec) mysql> select count(1) from nums_4; +----------+ | count(1) | +----------+ | 10000000 | +----------+ 1 row in set (0.00 sec) mysql> select count(*) from nums_4; +----------+ | count(*) | +----------+ | 10000000 | +----------+ 1 row in set (0.00 sec)
执行计划也均一致,可以看出没有通过主键或其他索引扫描的方式统计
mysql> explain select count(*) from nums_4; +----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+------------------------------+ | id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra | +----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+------------------------------+ | 1 | SIMPLE | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | Select tables optimized away | +----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+------------------------------+ 1 row in set, 1 warning (0.00 sec) mysql> explain select count(p1) from nums_4; +----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+------------------------------+ | id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra | +----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+------------------------------+ | 1 | SIMPLE | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | Select tables optimized away | +----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+------------------------------+ 1 row in set, 1 warning (0.00 sec) mysql> explain select count(1) from nums_4; +----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+------------------------------+ | id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra | +----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+------------------------------+ | 1 | SIMPLE | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | Select tables optimized away | +----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+------------------------------+ 1 row in set, 1 warning (0.00 sec)
小结:
MyISAM的方法查整表数据量效率情况为 count(主键)= count(1) = count(*)
查询部分数据的时候则无法直接从统计信息获取,因此耗时情况大致如下:
mysql> select count(p1) from nums_4 where p1 like ‘aa%‘; +-----------+ | count(p1) | +-----------+ | 39208 | +-----------+ 1 row in set (0.14 sec) mysql> select count(1) from nums_4 where p1 like ‘aa%‘; +----------+ | count(1) | +----------+ | 39208 | +----------+ 1 row in set (0.13 sec) mysql> select count(*) from nums_4 where p1 like ‘aa%‘; +----------+ | count(*) | +----------+ | 39208 | +----------+ 1 row in set (0.13 sec)
执行计划其实均一样:
mysql> explain select count(1) from nums_4 where p1 like ‘aa%‘; +----+-------------+--------+------------+-------+---------------+---------+---------+------+-------+----------+--------------------------+ | id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra | +----+-------------+--------+------------+-------+---------------+---------+---------+------+-------+----------+--------------------------+ | 1 | SIMPLE | nums_4 | NULL | range | PRIMARY | PRIMARY | 98 | NULL | 42603 | 100.00 | Using where; Using index | +----+-------------+--------+------------+-------+---------------+---------+---------+------+-------+----------+--------------------------+ 1 row in set, 1 warning (0.00 sec)
小结: MyISAM引擎表统计部分数据的时候直接得出数据量,也许扫描数据进行统计,几种写法效率相近。
innodb引擎因为要支持MVCC,因此不能整表数据量持久化保存,每次查询均需遍历统计,但是不同的写法,查询效率是有差别的,后面将进行不同维度进行对比。
通过 count(主键),count(1) , count(*) 对比查询效率
mysql> select count(p1) from nums_2 ; +-----------+ | count(p1) | +-----------+ | 10000000 | +-----------+ 1 row in set (1.68 sec) mysql> select count(1) from nums_2 ; +----------+ | count(1) | +----------+ | 10000000 | +----------+ 1 row in set (1.37 sec) mysql> select count(*) from nums_2 ; +----------+ | count(*) | +----------+ | 10000000 | +----------+ 1 row in set (1.38 sec)
简单的对比发现,查询性能结果为 count(主键) < count(1) ≈ count(*)
但是查看执行计划都是如下情况
mysql> explain select count(p1) from nums_2; +----+-------------+--------+------------+-------+---------------+---------+---------+------+---------+----------+-------------+ | id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra | +----+-------------+--------+------------+-------+---------------+---------+---------+------+---------+----------+-------------+ | 1 | SIMPLE | nums_2 | NULL | index | NULL | PRIMARY | 98 | NULL | 9936693 | 100.00 | Using index | +----+-------------+--------+------------+-------+---------------+---------+---------+------+---------+----------+-------------+ 1 row in set, 1 warning (0.00 sec
但是查询效