如何在不扫描所有行的情况下在我的索引列上使用查询限制?

How to use Limit in query on my index column without scan all rows?

这是我的 table :

在我的table

我的 table 有 90,000 行相同的 ID 等于 5。我想前 3 行 ID 等于 5 我的查询是这样的

Select * from mytable where ID=5 Limit 3;

ID 列是索引列所以我认为 mysql 只扫描前 3 行,但 mysql 扫描大约 42000 行。

这里解释查询:

任何避免所有行扫描的可能性。

请给我一些解决方案

提前致谢

我模拟了这个场景。

  • 使用
  • 创建了 table

   CREATE TABLE mytable (
        Clustering_key INT NOT NULL AUTO_INCREMENT,
        ID INT NOT NULL,
        Data text NOT NULL,
        Position INT NOT NULL,
        PRIMARY KEY (Clustering_key),
        KEY(ID),
        KEY(Position)
    )

  • 插入数据

    INSERT INTO mytable (ID,Data,Position) VALUES (5,CONCAT("Data-",5), 7);
    INSERT INTO mytable (ID,Data,Position) VALUES (5,CONCAT("Data-",5), 26);
    INSERT INTO mytable (ID,Data,Position) VALUES (5,CONCAT("Data-",51), 27);
    INSERT INTO mytable (ID,Data,Position) VALUES (5,CONCAT("Data-",56), 28);
    INSERT INTO mytable (ID,Data,Position) VALUES (5,CONCAT("Data-",57), 31);

  • 解释

    mysql> explain Select * from mytable where ID=5 Limit 3
    +----+-------------+---------+------------+------+---------------+------+---------+-------+------+----------+-------+
    | id | select_type | table   | partitions | type | possible_keys | key  | key_len | ref   | rows | filtered | Extra |
    +----+-------------+---------+------------+------+---------------+------+---------+-------+------+----------+-------+
    |  1 | SIMPLE      | mytable | NULL       | ref  | ID            | ID   | 4       | const |    5 |   100.00 | NULL  |
    +----+-------------+---------+------------+------+---------------+------+---------+-------+------+----------+-------+
    1 row in set, 1 warning (0.00 sec)

是的,explain 显示检查的行是 5,而不是 3。 但似乎这只是一个误导性信息。 运行-time rows_examined 的确切数量可以通过以下步骤为所有查询启用慢日志(设置 long_query_time=0)来验证。

注意:您必须仅在您自己的测试数据库中设置 long_query_time=0。并且您必须在测试后将参数重置回之前的值。


     - set GLOBAL slow_query_log=1;
     - set global long_query_time=0;
     - set session long_query_time=0;
     mysql> show variables like '%slow%';
    +---------------------------+-------------------------------------------------+
    | Variable_name             | Value                                           |
    +---------------------------+-------------------------------------------------+
    | log_slow_admin_statements | OFF                                             |
    | log_slow_slave_statements | OFF                                             |
    | slow_launch_time          | 2                                               |
    | slow_query_log            | ON                                              |
    | slow_query_log_file       | /usr/local/mysql/data/slow.log                  |
    +---------------------------+-------------------------------------------------+
    5 rows in set (0.10 sec)
    mysql> select @@long_query_time;
    +-------------------+
    | @@long_query_time |
    +-------------------+
    |          0.000000 |
    +-------------------+
    
And then in the terminal, executing the query
<pre>
mysql> Select * from mytable where ID=5 Limit 3;
+----------------+----+---------+----------+
| Clustering_key | ID | Data    | Position |
+----------------+----+---------+----------+
|              5 |  5 | Data-5  |        7 |
|          26293 |  5 | Data-5  |       26 |
|          26294 |  5 | Data-51 |       27 |
+----------------+----+---------+----------+
3 rows in set (0.00 sec)

mysql> Select * from mytable where ID=5 Limit 1;

通过检查上面打印的slow_query_log_file来检查慢日志/usr/local/mysql/data/slow.log

您可以找到以下信息。


    # Time: 2019-04-26T01:48:19.890846Z
    # User@Host: root[root] @ localhost []  Id:  5124
    # Query_time: 0.000575  Lock_time: 0.000146 Rows_sent: 3  Rows_examined: 3 
    SET timestamp=1556243299;
    Select * from mytable where ID=5 Limit 3;
    # Time: 2019-04-26T01:48:34.672888Z
    # User@Host: root[root] @ localhost []  Id:  5124
    # Query_time: 0.000182  Lock_time: 0.000074 Rows_sent: 1  Rows_examined: 1 
    SET timestamp=1556243314;
    Select * from mytable where ID=5 Limit 1;

运行时间Rows_exmained值等于limit参数的值。 测试在 MySQL 5.7.18.

上完成

------------------------------------另一种验证方式------ --------------------------



    mysql> show status like '%Innodb_rows_read%';
    +------------------+-------+
    | Variable_name    | Value |
    +------------------+-------+
    | Innodb_rows_read | 13    |
    +------------------+-------+
    1 row in set (0.00 sec)

    mysql> Select * from mytable where ID=5 Limit 1;
    +----------------+----+--------+----------+
    | Clustering_key | ID | Data   | Position |
    +----------------+----+--------+----------+
    |              5 |  5 | Data-5 |        7 |
    +----------------+----+--------+----------+
    1 row in set (0.00 sec)

    mysql> show status like '%Innodb_rows_read%';
    +------------------+-------+
    | Variable_name    | Value |
    +------------------+-------+
    | Innodb_rows_read | 14    |
    +------------------+-------+
    1 row in set (0.00 sec)

你可以看到 Innodb_rows_read 只是增加了 1 限制 1。 如果您执行完整的 table 扫描查询,您可以看到该值将增加 table.

的计数

    mysql> select count(*) from mytable;
    +----------+
    | count(*) |
    +----------+
    |   126296 |
    +----------+
    1 row in set (0.05 sec)

    mysql> show status like '%Innodb_rows_read%';
    +------------------+--------+
    | Variable_name    | Value  |
    +------------------+--------+
    | Innodb_rows_read | 505204 |
    +------------------+--------+
    1 row in set (0.00 sec)

    mysql> Select * from mytable where Data="Data-5";
    +----------------+----+--------+----------+
    | Clustering_key | ID | Data   | Position |
    +----------------+----+--------+----------+
    |              5 |  5 | Data-5 |        7 |
    |          26293 |  5 | Data-5 |       26 |
    |          26301 |  5 | Data-5 |        7 |
    +----------------+----+--------+----------+
    3 rows in set (0.09 sec)

    mysql> show status like '%Innodb_rows_read%';
    +------------------+--------+
    | Variable_name    | Value  |
    +------------------+--------+
    | Innodb_rows_read | 631500 |
    +------------------+--------+
    1 row in set (0.00 sec)

两种方式都证实了限制的 explain 似乎提供了有关所检查行的误导性信息。