Introducing MySQL's performance optimization tool Explain

MySQL Tutorial Column introduces the performance optimization artifact Explain

##More related free learning recommendations:

mysql Tutorial (Video)

Introduction

MySQL provides an EXPLAIN command, which can analyze the

SELECT statement and output SELECT for execution Detailed information for developers to optimize.EXPLAIN command usage is very simple, just add Explain before the SELECT statement, for example:

EXPLAIN SELECT * from user_info WHERE  id < 300;

Prepare

In order to receive To facilitate the demonstration of the use of EXPLAIN, first we need to create two tables for testing and add corresponding data:

CREATE TABLE `user_info` (
  `id`   BIGINT(20)  NOT NULL AUTO_INCREMENT,
  `name` VARCHAR(50) NOT NULL DEFAULT '',
  `age`  INT(11)              DEFAULT NULL,
  PRIMARY KEY (`id`),
  KEY `name_index` (`name`)
)
  ENGINE = InnoDB
  DEFAULT CHARSET = utf8

INSERT INTO user_info (name, age) VALUES ('xys', 20);
INSERT INTO user_info (name, age) VALUES ('a', 21);
INSERT INTO user_info (name, age) VALUES ('b', 23);
INSERT INTO user_info (name, age) VALUES ('c', 50);
INSERT INTO user_info (name, age) VALUES ('d', 15);
INSERT INTO user_info (name, age) VALUES ('e', 20);
INSERT INTO user_info (name, age) VALUES ('f', 21);
INSERT INTO user_info (name, age) VALUES ('g', 23);
INSERT INTO user_info (name, age) VALUES ('h', 50);
INSERT INTO user_info (name, age) VALUES ('i', 15);

CREATE TABLE `order_info` (
  `id`           BIGINT(20)  NOT NULL AUTO_INCREMENT,
  `user_id`      BIGINT(20)           DEFAULT NULL,
  `product_name` VARCHAR(50) NOT NULL DEFAULT '',
  `productor`    VARCHAR(30)          DEFAULT NULL,
  PRIMARY KEY (`id`),
  KEY `user_product_detail_index` (`user_id`, `product_name`, `productor`)
)
  ENGINE = InnoDB
  DEFAULT CHARSET = utf8

INSERT INTO order_info (user_id, product_name, productor) VALUES (1, 'p1', 'WHH');
INSERT INTO order_info (user_id, product_name, productor) VALUES (1, 'p2', 'WL');
INSERT INTO order_info (user_id, product_name, productor) VALUES (1, 'p1', 'DX');
INSERT INTO order_info (user_id, product_name, productor) VALUES (2, 'p1', 'WHH');
INSERT INTO order_info (user_id, product_name, productor) VALUES (2, 'p5', 'WL');
INSERT INTO order_info (user_id, product_name, productor) VALUES (3, 'p3', 'MA');
INSERT INTO order_info (user_id, product_name, productor) VALUES (4, 'p1', 'WHH');
INSERT INTO order_info (user_id, product_name, productor) VALUES (6, 'p1', 'WHH');
INSERT INTO order_info (user_id, product_name, productor) VALUES (9, 'p8', 'TE');

EXPLAIN output format

The output content of the EXPLAIN command is roughly as follows:

mysql> explain select * from user_info where id = 2\G
*************************** 1. row ***************************
           id: 1
  select_type: SIMPLE
        table: user_info
   partitions: NULL
         type: const
possible_keys: PRIMARY
          key: PRIMARY
      key_len: 8
          ref: const
         rows: 1
     filtered: 100.00
        Extra: NULL
1 row in set, 1 warning (0.00 sec)

The meaning of each column is as follows:

id: The identifier of the SELECT query. Each SELECT will automatically be assigned a unique identifier.
• select_type: SELECT query Type.
• table: Which table is being queried
• partitions: Matching partition
• type: join type
• possible_keys: Possible keys in this query Selected index
• key: The exact index used in this query.
• ref: Which field or constant is used together with key
• rows: Displays the total number of this query How many rows were scanned. This is an estimate.
• filtered: Indicates the percentage of data filtered by this query condition
• extra: Additional information

Continue Let’s focus on the more important fields.

select_type

select_type represents the type of query, and its common values ​​​​are:

SIMPLE, indicates that this query does not contain a UNION query or subquery
• PRIMARY, indicates that this query is the outermost query
• UNION, indicates that this query is the second query of UNION or subsequent query
• DEPENDENT UNION, the second or subsequent query statement in UNION, depends on the outer query
• UNION RESULT, the result of UNION
• SUBQUERY, The first SELECT in the subquery
• DEPENDENT SUBQUERY: The first SELECT in the subquery depends on the outer query. That is, the subquery depends on the result of the outer query.

The most common query type should be

SIMPLE. For example, when our query has no subquery and no UNION query, it is usually the SIMPLE type, for example:

mysql> explain select * from user_info where id = 2\G
*************************** 1. row ***************************
           id: 1
  select_type: SIMPLE
        table: user_info
   partitions: NULL
         type: const
possible_keys: PRIMARY
          key: PRIMARY
      key_len: 8
          ref: const
         rows: 1
     filtered: 100.00
        Extra: NULL
1 row in set, 1 warning (0.00 sec)

If we use a UNION query, the results output by EXPLAIN are similar to the following:

mysql> EXPLAIN (SELECT * FROM user_info  WHERE id IN (1, 2, 3))
    -> UNION
    -> (SELECT * FROM user_info WHERE id IN (3, 4, 5));
+----+--------------+------------+------------+-------+---------------+---------+---------+------+------+----------+-----------------+
| id | select_type  | table      | partitions | type  | possible_keys | key     | key_len | ref  | rows | filtered | Extra           |
+----+--------------+------------+------------+-------+---------------+---------+---------+------+------+----------+-----------------+
|  1 | PRIMARY      | user_info  | NULL       | range | PRIMARY       | PRIMARY | 8       | NULL |    3 |   100.00 | Using where     |
|  2 | UNION        | user_info  | NULL       | range | PRIMARY       | PRIMARY | 8       | NULL |    3 |   100.00 | Using where     |
| NULL | UNION RESULT | <union1,2> | NULL       | ALL   | NULL          | NULL    | NULL    | NULL | NULL |     NULL | Using temporary |
+----+--------------+------------+------------+-------+---------------+---------+---------+------+------+----------+-----------------+
3 rows in set, 1 warning (0.00 sec)

table

indicates the table or derived table involved in the query

type## The

#type

field is more important. It provides an important basis for judging whether the query is efficient. Through the type field, we judge that this query is a full table scan Or index scan etc. type Common types

type Common values ​​are:

system: There is only one entry in the table Data. This type is a special

const
• type.const: Equivalent query scan for primary key or unique index, only returns one row of data at most. const query is very fast because it only Just read it once.
For example, the query below uses the primary key index, so
• type
  is of type const.

  mysql> explain select * from user_info where id = 2\G
  *************************** 1. row ***************************
             id: 1
    select_type: SIMPLE
          table: user_info
     partitions: NULL
           type: const
  possible_keys: PRIMARY
            key: PRIMARY
        key_len: 8
            ref: const
           rows: 1
       filtered: 100.00
          Extra: NULL
  1 row in set, 1 warning (0.00 sec)

eq_ref: This type usually appears in multi-table join queries, which means that each result in the front table can only match one row of results in the back table. And the comparison operation of the query is usually

=
• , query efficiency is higher. For example:

  mysql> EXPLAIN SELECT * FROM user_info, order_info WHERE user_info.id = order_info.user_id\G
  *************************** 1. row ***************************
             id: 1
    select_type: SIMPLE
          table: order_info
     partitions: NULL
           type: index
  possible_keys: user_product_detail_index
            key: user_product_detail_index
        key_len: 314
            ref: NULL
           rows: 9
       filtered: 100.00
          Extra: Using where; Using index
  *************************** 2. row ***************************
             id: 1
    select_type: SIMPLE
          table: user_info
     partitions: NULL
           type: eq_ref
  possible_keys: PRIMARY
            key: PRIMARY
        key_len: 8
            ref: test.order_info.user_id
           rows: 1
       filtered: 100.00
          Extra: NULL
  2 rows in set, 1 warning (0.00 sec)

ref: This type usually appears in join queries of multiple tables, for non-unique or non-primary key indexes, or when

is used The leftmost prefix
• is the query of the rule index.For example, in the following example, the ref
  type of query is used:

  mysql> EXPLAIN SELECT * FROM user_info, order_info WHERE user_info.id = order_info.user_id AND order_info.user_id = 5\G
  *************************** 1. row ***************************
             id: 1
    select_type: SIMPLE
          table: user_info
     partitions: NULL
           type: const
  possible_keys: PRIMARY
            key: PRIMARY
        key_len: 8
            ref: const
           rows: 1
       filtered: 100.00
          Extra: NULL
  *************************** 2. row ***************************
             id: 1
    select_type: SIMPLE
          table: order_info
     partitions: NULL
           type: ref
  possible_keys: user_product_detail_index
            key: user_product_detail_index
        key_len: 9
            ref: const
           rows: 1
       filtered: 100.00
          Extra: Using index
  2 rows in set, 1 warning (0.01 sec)

range: means Use index range query to obtain some data records in the table through the index field range. This type usually appears in =, <>, >, >=, <, <=, IS NULL, <=> , BETWEEN, IN() operation.

When
• type
  is range, then the ref field output by EXPLAIN is NULL, and key_len The field is the longest of the indexes used in this query. For example, the following example is a range query:
  

  mysql> EXPLAIN SELECT *
      ->         FROM user_info
      ->         WHERE id BETWEEN 2 AND 8 \G
  *************************** 1. row ***************************
             id: 1
    select_type: SIMPLE
          table: user_info
     partitions: NULL
           type: range
  possible_keys: PRIMARY
            key: PRIMARY
        key_len: 8
            ref: NULL
           rows: 7
       filtered: 100.00
          Extra: Using where
  1 row in set, 1 warning (0.00 sec)

index: means full index scan (full index scan), similar to the ALL type, except that the ALL type is a full table scan, while the index type only scans all indexes, without scanning the data.

The index type usually appears when: the data to be queried is directly in It can be obtained from the index tree without scanning the data. When this is the case, the Extra field will display
• Using index
  .
For example:

mysql> EXPLAIN SELECT name FROM  user_info \G
*************************** 1. row ***************************
           id: 1
  select_type: SIMPLE
        table: user_info
   partitions: NULL
         type: index
possible_keys: NULL
          key: name_index
      key_len: 152
          ref: NULL
         rows: 10
     filtered: 100.00
        Extra: Using index
1 row in set, 1 warning (0.00 sec)

In the above example, the name field we query happens to be an index, so we can meet the query needs by getting the data directly from the index, without querying the data in the table. Therefore, in this case, type The value is

index

, and the value of Extra is Using index.<ul><li>ALL: 表示全表扫描, 这个类型的查询是性能最差的查询之一. 通常来说, 我们的查询不应该出现 ALL 类型的查询, 因为这样的查询在数据量大的情况下, 对数据库的性能是巨大的灾难. 如一个查询是 ALL 类型查询, 那么一般来说可以对相应的字段添加索引来避免.<br>下面是一个全表扫描的例子, 可以看到, 在全表扫描时, possible_keys 和 key 字段都是 NULL, 表示没有使用到索引, 并且 rows 十分巨大, 因此整个查询效率是十分低下的.</li></ul> <pre class="brush:php;toolbar:false">mysql&gt; EXPLAIN SELECT age FROM  user_info WHERE age = 20 \G *************************** 1. row ***************************            id: 1   select_type: SIMPLE         table: user_info    partitions: NULL          type: ALL possible_keys: NULL           key: NULL       key_len: NULL           ref: NULL          rows: 10      filtered: 10.00         Extra: Using where 1 row in set, 1 warning (0.00 sec)</pre> <h4>type 类型的性能比较</h4> <p>通常来说, 不同的 type 类型的性能关系如下:<br><code>ALL < index < range ~ index_merge < ref < eq_ref < const < system
ALL 类型因为是全表扫描, 因此在相同的查询条件下, 它是速度最慢的.
而 index 类型的查询虽然不是全表扫描, 但是它扫描了所有的索引, 因此比 ALL 类型的稍快.
后面的几种类型都是利用了索引来查询数据, 因此可以过滤部分或大部分数据, 因此查询效率就比较高了.

possible_keys

possible_keys 表示 MySQL 在查询时, 能够使用到的索引. 注意, 即使有些索引在 possible_keys 中出现, 但是并不表示此索引会真正地被 MySQL 使用到. MySQL 在查询时具体使用了哪些索引, 由 key 字段决定.

key

此字段是 MySQL 在当前查询时所真正使用到的索引.

key_len

表示查询优化器使用了索引的字节数. 这个字段可以评估组合索引是否完全被使用, 或只有最左部分字段被使用到.
key_len 的计算规则如下:

• 字符串
• char(n): n 字节长度
• varchar(n): 如果是 utf8 编码, 则是 3 * n + 2字节; 如果是 utf8mb4 编码, 则是 4 * n + 2 字节.
• 数值类型:
• TINYINT: 1字节
• SMALLINT: 2字节
• MEDIUMINT: 3字节
• INT: 4字节
• BIGINT: 8字节
• 时间类型
• DATE: 3字节
• TIMESTAMP: 4字节
• DATETIME: 8字节
• 字段属性: NULL 属性 占用一个字节. 如果一个字段是 NOT NULL 的, 则没有此属性.

我们来举两个简单的栗子:

mysql> EXPLAIN SELECT * FROM order_info WHERE user_id < 3 AND product_name = &#39;p1&#39; AND productor = &#39;WHH&#39; \G
*************************** 1. row ***************************
           id: 1
  select_type: SIMPLE
        table: order_info
   partitions: NULL
         type: range
possible_keys: user_product_detail_index
          key: user_product_detail_index
      key_len: 9
          ref: NULL
         rows: 5
     filtered: 11.11
        Extra: Using where; Using index
1 row in set, 1 warning (0.00 sec)

上面的例子是从表 order_info 中查询指定的内容, 而我们从此表的建表语句中可以知道, 表 order_info 有一个联合索引:

KEY `user_product_detail_index` (`user_id`, `product_name`, `productor`)

不过此查询语句 WHERE user_id < 3 AND product_name = &#39;p1&#39; AND productor = &#39;WHH&#39; 中, 因为先进行 user_id 的范围查询, 而根据 最左前缀匹配 原则, 当遇到范围查询时, 就停止索引的匹配, 因此实际上我们使用到的索引的字段只有 user_id, 因此在 EXPLAIN 中, 显示的 key_len 为 9. 因为 user_id 字段是 BIGINT, 占用 8 字节, 而 NULL 属性占用一个字节, 因此总共是 9 个字节. 若我们将user_id 字段改为 BIGINT(20) NOT NULL DEFAULT '0', 则 key_length 应该是8.

上面因为 最左前缀匹配 原则, 我们的查询仅仅使用到了联合索引的 user_id 字段, 因此效率不算高.

接下来我们来看一下下一个例子:

mysql> EXPLAIN SELECT * FROM order_info WHERE user_id = 1 AND product_name = 'p1' \G;
*************************** 1. row ***************************
           id: 1
  select_type: SIMPLE
        table: order_info
   partitions: NULL
         type: ref
possible_keys: user_product_detail_index
          key: user_product_detail_index
      key_len: 161
          ref: const,const
         rows: 2
     filtered: 100.00
        Extra: Using index
1 row in set, 1 warning (0.00 sec)<p>这次的查询中, 我们没有使用到范围查询, key_len 的值为 161. 为什么呢? 因为我们的查询条件 <code>WHERE user_id = 1 AND product_name = 'p1'</code> 中, 仅仅使用到了联合索引中的前两个字段, 因此 <code>keyLen(user_id) + keyLen(product_name) = 9 + 50 * 3 + 2 = 161</code></p>
<h3>rows</h3>
<p>rows 也是一个重要的字段. MySQL 查询优化器根据统计信息, 估算 SQL 要查找到结果集需要扫描读取的数据行数.<br>这个值非常直观显示 SQL 的效率好坏, 原则上 rows 越少越好.</p>
<h3>Extra</h3>
<p>EXplain 中的很多额外的信息会在 Extra 字段显示, 常见的有以下几种内容:</p>
<ul><li>Using filesort<br>当 Extra 中有 <code>Using filesort</code> 时, 表示 MySQL 需额外的排序操作, 不能通过索引顺序达到排序效果. 一般有 <code>Using filesort</code>, 都建议优化去掉, 因为这样的查询 CPU 资源消耗大.<br>例如下面的例子:</li></ul>
<pre class="brush:php;toolbar:false">mysql> EXPLAIN SELECT * FROM order_info ORDER BY product_name \G
*************************** 1. row ***************************
           id: 1
  select_type: SIMPLE
        table: order_info
   partitions: NULL
         type: index
possible_keys: NULL
          key: user_product_detail_index
      key_len: 253
          ref: NULL
         rows: 9
     filtered: 100.00
        Extra: Using index; Using filesort
1 row in set, 1 warning (0.00 sec)

我们的索引是

KEY `user_product_detail_index` (`user_id`, `product_name`, `productor`)

但是上面的查询中根据 product_name 来排序, 因此不能使用索引进行优化, 进而会产生 Using filesort.
如果我们将排序依据改为 ORDER BY user_id, product_name, 那么就不会出现 Using filesort 了. 例如:

mysql> EXPLAIN SELECT * FROM order_info ORDER BY user_id, product_name \G
*************************** 1. row ***************************
           id: 1
  select_type: SIMPLE
        table: order_info
   partitions: NULL
         type: index
possible_keys: NULL
          key: user_product_detail_index
      key_len: 253
          ref: NULL
         rows: 9
     filtered: 100.00
        Extra: Using index
1 row in set, 1 warning (0.00 sec)

• Using index
  "覆盖索引扫描", 表示查询在索引树中就可查找所需数据, 不用扫描表数据文件, 往往说明性能不错
• Using temporary
  查询有使用临时表, 一般出现于排序, 分组和多表 join 的情况, 查询效率不高, 建议优化.

相关免费推荐：编程视频课程

The above is the detailed content of Introducing MySQL's performance optimization tool Explain. For more information, please follow other related articles on the PHP Chinese website!