mysql explain type connection type example-Mysql Tutorial-php.cn

Home

Database

Mysql Tutorial

mysql explain type connection type example

黄舟

Feb 13, 2017 am 10:57 AM

mysql

For obtaining the MySQL execution plan, we can view it through the explain method. The explain method seems simple, but it actually contains a lot of content, especially the type in the output result. Type column. Understanding these different types is very important for our SQL optimization. This article only describes the type column in the explian output results and gives its demonstration.

For a full description of explian output, please refer to: MySQL EXPLAIN SQL output information description

1. The value of the type column in the EXPLAIN statement

type：
    连接类型
    system          表只有一行    const           表最多只有一行匹配，通用用于主键或者唯一索引比较时
    eq_ref          每次与之前的表合并行都只在该表读取一行，这是除了system，const之外最好的一种，
                    特点是使用=，而且索引的所有部分都参与join且索引是主键或非空唯一键的索引
    ref             如果每次只匹配少数行，那就是比较好的一种，使用=或<=>，可以是左覆盖索引或非主键或非唯一键
    fulltext        全文搜索
    ref_or_null     与ref类似，但包括NULL
    index_merge     表示出现了索引合并优化(包括交集，并集以及交集之间的并集)，但不包括跨表和全文索引。
                    这个比较复杂，目前的理解是合并单表的范围索引扫描（如果成本估算比普通的range要更优的话）
    unique_subquery 在in子查询中，就是value in (select...)把形如“select unique_key_column”的子查询替换。
                    PS：所以不一定in子句中使用子查询就是低效的！
    index_subquery  同上，但把形如”select non_unique_key_column“的子查询替换
    range           常数值的范围    index           a.当查询是索引覆盖的，即所有数据均可从索引树获取的时候（Extra中有Using Index）；
                    b.以索引顺序从索引中查找数据行的全表扫描（无 Using Index）；
                    c.如果Extra中Using Index与Using Where同时出现的话，则是利用索引查找键值的意思；
                    d.如单独出现，则是用读索引来代替读行，但不用于查找
    all             全表扫描

2. Connection Type part example

1、all-- 环境描述
(root@localhost) [sakila]> show variables like &#39;version&#39;;
+---------------+--------+
| Variable_name | Value  |
+---------------+--------+
| version       | 5.6.26 |
+---------------+--------+
MySQL采取全表遍历的方式来返回数据行，等同于Oracle的full table scan
(root@localhost) [sakila]> explain select count(description) from film;
+----+-------------+-------+------+---------------+------+---------+------+------+-------+
| id | select_type | table | type | possible_keys | key  | key_len | ref  | rows | Extra |
+----+-------------+-------+------+---------------+------+---------+------+------+-------+
|  1 | SIMPLE      | film  | ALL  | NULL          | NULL | NULL    | NULL | 1000 | NULL  |
+----+-------------+-------+------+---------------+------+---------+------+------+-------+
2、index
MySQL采取索引全扫描的方式来返回数据行，等同于Oracle的full index scan
(root@localhost) [sakila]> explain select title from film \G
*************************** 1. row ***************************           
id: 1  
select_type: SIMPLE        
table: film         
type: indexpossible_keys: NULL
          key: idx_title      
          key_len: 767          
          ref: NULL         
          rows: 1000        
          Extra: Using index1 row in set (0.00 sec)

3、  range
索引范围扫描，对索引的扫描开始于某一点，返回匹配值域的行，常见于between、<、>等的查询
等同于Oracle的index range scan
(root@localhost) [sakila]> explain select * from payment where customer_id>300 and customer_id<400\G
*************************** 1. row ***************************           
id: 1  
select_type: SIMPLE        
table: payment         
type: rangepossible_keys: idx_fk_customer_id          
key: idx_fk_customer_id      
key_len: 2          
ref: NULL         
rows: 2637        
Extra: Using where1 row in set (0.00 sec)

(root@localhost) [sakila]> explain select * from payment where customer_id in (200,300,400)\G
*************************** 1. row ***************************
           id: 1
  select_type: SIMPLE        
  table: payment         
  type: rangepossible_keys: idx_fk_customer_id          
  key: idx_fk_customer_id      
  key_len: 2          
  ref: NULL         
  rows: 86        
  Extra: Using index condition1 row in set (0.00 sec)

4、ref
非唯一性索引扫描或者，返回匹配某个单独值的所有行。常见于使用非唯一索引即唯一索引的非唯一前缀进行的查找
(root@localhost) [sakila]> explain select * from payment where customer_id=305\G
*************************** 1. row ***************************
           id: 1
  select_type: SIMPLE        
  table: payment         
  type: refpossible_keys: idx_fk_customer_id          
  key: idx_fk_customer_id      
  key_len: 2          
  ref: const         
  rows: 25        
  Extra: 1 row in set (0.00 sec)

idx_fk_customer_id为表payment上的外键索引，且存在多个不不唯一的值，如下查询
(root@localhost) [sakila]> select customer_id,count(*) from payment group by customer_id
    -> limit 2;
+-------------+----------+
| customer_id | count(*) |+-------------+----------+
|           1 |       32 ||           2 |       27 |
+-------------+----------+-- 下面是非唯一前缀索引使用ref的示例
(root@localhost) [sakila]> create index idx_fisrt_last_name on customer(first_name,last_name);
Query OK, 599 rows affected (0.09 sec)
Records: 599  Duplicates: 0  Warnings: 0(root@localhost) [sakila]> select first_name,count(*) from customer group by first_name 
    -> having count(*)>1 limit 2;
+------------+----------+| first_name | count(*) |
+------------+----------+| JAMIE      |        2 || JESSIE     |        2 |
+------------+----------+2 rows in set (0.00 sec)

(root@localhost) [sakila]> explain select first_name from customer where first_name=&#39;JESSIE&#39;\G
*************************** 1. row ***************************           
id: 1  select_type: SIMPLE        
table: customer         
type: refpossible_keys: idx_fisrt_last_name          
key: idx_fisrt_last_name      
key_len: 137          
ref: const         
rows: 2        
Extra: Using where; Using index1 row in set (0.00 sec)

(root@localhost) [sakila]> alter table customer drop index idx_fisrt_last_name;
Query OK, 599 rows affected (0.03 sec)
Records: 599  Duplicates: 0  Warnings: 0--下面演示出现在join是ref的示例
(root@localhost) [sakila]> explain select b.*,a.* from payment a inner join    -> customer b on a.customer_id=b.customer_id\G
*************************** 1. row ***************************           
id: 1  
select_type: SIMPLE        
table: b         
type: ALLpossible_keys: PRIMARY
          key: NULL
      key_len: NULL          
      ref: NULL         
      rows: 599        
      Extra: NULL
      *************************** 2. row ***************************           
      id: 1  
      select_type: SIMPLE        
      table: a         
      type: refpossible_keys: idx_fk_customer_id          
      key: idx_fk_customer_id      
      key_len: 2          
      ref: sakila.b.customer_id         
      rows: 13        
      Extra: NULL2 rows in set (0.01 sec)

5、eq_ref
类似于ref，其差别在于使用的索引为唯一索引，对于每个索引键值，表中只有一条记录与之匹配。
多见于主键扫描或者索引唯一扫描。
(root@localhost) [sakila]> explain select * from film a join film_text b 
    -> on a.film_id=b.film_id;
+----+-------------+-------+--------+---------------+---------+---------+------------------+------+-------------+
| id | select_type | table | type   | possible_keys | key     | key_len | ref         | rows | Extra       |
+----+-------------+-------+--------+---------------+---------+---------+------------------+------+-------------+
|  1 | SIMPLE      | b     | ALL    | PRIMARY       | NULL    | NULL    | NULL    | 1000 | NULL    |
|  1 | SIMPLE      | a     | eq_ref | PRIMARY       | PRIMARY | 2       | sakila.b.film_id |    1 | Using where |
+----+-------------+-------+--------+---------------+---------+---------+------------------+------+-------------+
(root@localhost) [sakila]> explain select title from film where film_id=5;
+----+-------------+-------+-------+---------------+---------+---------+-------+------+-------+
| id | select_type | table | type  | possible_keys | key     | key_len | ref   | rows | Extra |
+----+-------------+-------+-------+---------------+---------+---------+-------+------+-------+|  1 | SIMPLE      
| film  | const | PRIMAR   | PRIMARY | 2       | const |    1 | NULL  |
+----+-------------+-------+-------+---------------+---------+---------+-------+------+-------+6、const、system：
当MySQL对查询某部分进行优化，这个匹配的行的其他列值可以转换为一个常量来处理。
如将主键或者唯一索引置于where列表中，MySQL就能将该查询转换为一个常量
(root@localhost) [sakila]> create table t1(id int,ename varchar(20) unique);
Query OK, 0 rows affected (0.05 sec)

(root@localhost) [sakila]> insert into t1 values(1,&#39;robin&#39;),(2,&#39;jack&#39;),(3,&#39;henry&#39;);
Query OK, 3 rows affected (0.00 sec)
Records: 3  Duplicates: 0  Warnings: 0

(root@localhost) [sakila]> explain select * from (select * from t1 where ename=&#39;robin&#39;)x;
+----+-------------+------------+--------+---------------+-------+---------+-------+------+-------+
| id | select_type | table      | type   | possible_keys | key   | key_len | ref   | rows | Extra |
+----+-------------+------------+--------+---------------+-------+---------+-------+------+-------+
|  1 | PRIMARY     | <derived2> | system | NULL          | NULL  | NULL    | NULL  |    1 | NULL  |
|  2 | DERIVED     | t1         | const  | ename         | ename | 23      | const |    1 | NULL  |
+----+-------------+------------+--------+---------------+-------+---------+-------+------+-------+
2 rows in set (0.00 sec)

7、type=NULL
MySQL不用访问表或者索引就可以直接得到结果
(root@localhost) [sakila]> explain select sysdate();+----+-------------+-------+------+---------------+------+---------+------+------+----------------+
| id | select_type | table | type | possible_keys | key  | key_len | ref  | rows | Extra          |
+----+-------------+-------+------+---------------+------+---------+------+------+----------------+
|  1 | SIMPLE      | NULL  | NULL | NULL          | NULL | NULL    | NULL | NULL | No tables used |
+----+-------------+-------+------+---------------+------+---------+------+------+----------------+
1 row in set (0.00 sec)

For obtaining the MySQL execution plan, we can view it through the explain method. The explain method seems simple, but actually contains a lot of content. Especially the type column in the output result. Understanding these different types is very important for our SQL optimization. This article only describes the type column in the explian output results and gives its demonstration.

For a full description of explian output, please refer to: MySQL EXPLAIN SQL output information description

1. The value of the type column in the EXPLAIN statement

type：
    连接类型
    system          表只有一行    const           表最多只有一行匹配，通用用于主键或者唯一索引比较时
    eq_ref          每次与之前的表合并行都只在该表读取一行，这是除了system，const之外最好的一种，
                    特点是使用=，而且索引的所有部分都参与join且索引是主键或非空唯一键的索引
    ref             如果每次只匹配少数行，那就是比较好的一种，使用=或<=>，可以是左覆盖索引或非主键或非唯一键
    fulltext        全文搜索
    ref_or_null     与ref类似，但包括NULL
    index_merge     表示出现了索引合并优化(包括交集，并集以及交集之间的并集)，但不包括跨表和全文索引。
                    这个比较复杂，目前的理解是合并单表的范围索引扫描（如果成本估算比普通的range要更优的话）
    unique_subquery 在in子查询中，就是value in (select...)把形如“select unique_key_column”的子查询替换。
                    PS：所以不一定in子句中使用子查询就是低效的！
    index_subquery  同上，但把形如”select non_unique_key_column“的子查询替换
    range           常数值的范围    index           a.当查询是索引覆盖的，即所有数据均可从索引树获取的时候（Extra中有Using Index）；
                    b.以索引顺序从索引中查找数据行的全表扫描（无 Using Index）；
                    c.如果Extra中Using Index与Using Where同时出现的话，则是利用索引查找键值的意思；
                    d.如单独出现，则是用读索引来代替读行，但不用于查找
    all             全表扫描

2. Connection Type part example

1、all-- 环境描述
(root@localhost) [sakila]> show variables like &#39;version&#39;;
+---------------+--------+
| Variable_name | Value  |
+---------------+--------+
| version       | 5.6.26 |
+---------------+--------+MySQL采取全表遍历的方式来返回数据行，等同于Oracle的full table scan
(root@localhost) [sakila]> explain select count(description) from film;
+----+-------------+-------+------+---------------+------+---------+------+------+-------+
| id | select_type | table | type | possible_keys | key  | key_len | ref  | rows | Extra |
+----+-------------+-------+------+---------------+------+---------+------+------+-------+
|  1 | SIMPLE      | film  | ALL  | NULL          | NULL | NULL    | NULL | 1000 | NULL  |
+----+-------------+-------+------+---------------+------+---------+------+------+-------+
2、index
MySQL采取索引全扫描的方式来返回数据行，等同于Oracle的full index scan
(root@localhost) [sakila]> explain select title from film \G
*************************** 1. row ***************************           
id: 1  
select_type: SIMPLE        
table: film         
type: indexpossible_keys: NULL
          key: idx_title      
          key_len: 767          
          ref: NULL         
          rows: 1000        
          Extra: Using index1 row in set (0.00 sec)

3、  range
索引范围扫描，对索引的扫描开始于某一点，返回匹配值域的行，常见于between、<、>等的查询
等同于Oracle的index range scan
(root@localhost) [sakila]> explain select * from payment where customer_id>300 and customer_id<400\G
*************************** 1. row ***************************           
id: 1  
select_type: SIMPLE        
table: payment         
type: rangepossible_keys: idx_fk_customer_id          
key: idx_fk_customer_id      
key_len: 2          
ref: NULL         
rows: 2637        
Extra: Using where1 row in set (0.00 sec)

(root@localhost) [sakila]> explain select * from payment where customer_id in (200,300,400)\G
*************************** 1. row ***************************
           id: 1
  select_type: SIMPLE        
  table: payment         
  type: rangepossible_keys: idx_fk_customer_id          
  key: idx_fk_customer_id      
  key_len: 2          
  ref: NULL         
  rows: 86        
  Extra: Using index condition1 row in set (0.00 sec)

4、ref
非唯一性索引扫描或者，返回匹配某个单独值的所有行。常见于使用非唯一索引即唯一索引的非唯一前缀进行的查找
(root@localhost) [sakila]> explain select * from payment where customer_id=305\G
*************************** 1. row ***************************
           id: 1
  select_type: SIMPLE        
  table: payment         
  type: refpossible_keys: idx_fk_customer_id          
  key: idx_fk_customer_id      
  key_len: 2          
  ref: const         
  rows: 25        
  Extra: 1 row in set (0.00 sec)

idx_fk_customer_id为表payment上的外键索引，且存在多个不不唯一的值，如下查询
(root@localhost) [sakila]> select customer_id,count(*) from payment group by customer_id
    -> limit 2;
+-------------+----------+
| customer_id | count(*) |+-------------+----------+
|           1 |       32 ||           2 |       27 |
+-------------+----------+-- 下面是非唯一前缀索引使用ref的示例
(root@localhost) [sakila]> create index idx_fisrt_last_name on customer(first_name,last_name);
Query OK, 599 rows affected (0.09 sec)
Records: 599  Duplicates: 0  Warnings: 0(root@localhost) [sakila]> select first_name,count(*) from customer group by first_name 
    -> having count(*)>1 limit 2;
+------------+----------+| first_name | count(*) |
+------------+----------+| JAMIE      |        2 || JESSIE     |        2 |
+------------+----------+2 rows in set (0.00 sec)

(root@localhost) [sakila]> explain select first_name from customer where first_name=&#39;JESSIE&#39;\G
*************************** 1. row ***************************           
id: 1  
select_type: SIMPLE        
table: customer         
type: refpossible_keys: idx_fisrt_last_name          
key: idx_fisrt_last_name      
key_len: 137          
ref: const         
rows: 2        
Extra: Using where; Using index1 row in set (0.00 sec)

(root@localhost) [sakila]> alter table customer drop index idx_fisrt_last_name;
Query OK, 599 rows affected (0.03 sec)
Records: 599  Duplicates: 0  Warnings: 0--下面演示出现在join是ref的示例
(root@localhost) [sakila]> explain select b.*,a.* from payment a inner join    
-> customer b on a.customer_id=b.customer_id\G
*************************** 1. row ***************************           
id: 1  
select_type: 
SIMPLE        
table: b         
type: ALLpossible_keys: PRIMARY
          key: NULL
      key_len: NULL          
      ref: NULL         
      rows: 599        
      Extra: NULL
      *************************** 2. row ***************************           
      id: 1  
      select_type: SIMPLE        
      table: a         
      type: refpossible_keys: idx_fk_customer_id          
      key: idx_fk_customer_id      
      key_len: 2          
      ref: sakila.b.customer_id         
      rows: 13        
      Extra: NULL2 rows in set (0.01 sec)

5、eq_ref
类似于ref，其差别在于使用的索引为唯一索引，对于每个索引键值，表中只有一条记录与之匹配。
多见于主键扫描或者索引唯一扫描。
(root@localhost) [sakila]> explain select * from film a join film_text b 
    -> on a.film_id=b.film_id;
+----+-------------+-------+--------+---------------+---------+---------+------------------+------+-------------+
| id | select_type | table | type   | possible_keys | key     | key_len | ref              | rows | Extra       |
+----+-------------+-------+--------+---------------+---------+---------+------------------+------+-------------+
|  1 | SIMPLE      | b     | ALL    | PRIMARY       | NULL    | NULL    | NULL          | 1000 | NULL   |
|  1 | SIMPLE      | a     | eq_ref | PRIMARY       | PRIMARY | 2       | sakila.b.film_id |    1 | Using where |
+----+-------------+-------+--------+---------------+---------+---------+------------------+------+-------------+
(root@localhost) [sakila]> explain select title from film where film_id=5;
+----+-------------+-------+-------+---------------+---------+---------+-------+------+-------+
| id | select_type | table | type  | possible_keys | key     | key_len | ref   | rows | Extra |
+----+-------------+-------+-------+---------------+---------+---------+-------+------+-------+
|  1 | SIMPLE      | film  | const | PRIMARY       | PRIMARY | 2       | const |    1 | NULL  |
+----+-------------+-------+-------+---------------+---------+---------+-------+------+-------+
6、const、system：
当MySQL对查询某部分进行优化，这个匹配的行的其他列值可以转换为一个常量来处理。
如将主键或者唯一索引置于where列表中，MySQL就能将该查询转换为一个常量
(root@localhost) [sakila]> create table t1(id int,ename varchar(20) unique);
Query OK, 0 rows affected (0.05 sec)

(root@localhost) [sakila]> insert into t1 values(1,&#39;robin&#39;),(2,&#39;jack&#39;),(3,&#39;henry&#39;);
Query OK, 3 rows affected (0.00 sec)
Records: 3  Duplicates: 0  Warnings: 0

(root@localhost) [sakila]> explain select * from (select * from t1 where ename=&#39;robin&#39;)x;
+----+-------------+------------+--------+---------------+-------+---------+-------+------+-------+
| id | select_type | table      | type   | possible_keys | key   | key_len | ref   | rows | Extra |
+----+-------------+------------+--------+---------------+-------+---------+-------+------+-------+|  
1 | PRIMARY     | <derived2> | system | NULL          | NULL  | NULL    | NULL  |    1 | NULL  ||  
2 | DERIVED     | t1         | const  | ename         | ename | 2
3      | const |    1 | NULL  |
+----+-------------+------------+--------+---------------+-------+---------+-------+------+-------+
2 rows in set (0.00 sec)

7、type=NULL
MySQL不用访问表或者索引就可以直接得到结果
(root@localhost) [sakila]> explain select sysdate();
+----+-------------+-------+------+---------------+------+---------+------+------+----------------+
| id | select_type | table | type | possible_keys | key  | key_len | ref  | rows | Extra          |
+----+-------------+-------+------+---------------+------+---------+------+------+----------------+
|  1 | SIMPLE      | NULL  | NULL | NULL          | NULL | NULL    | NULL | NULL | No tables used |
+----+-------------+-------+------+---------------+------+---------+------+------+----------------+
1 row in set (0.00 sec)

The above is the content of mysql explain type connection type example. For more related content, please pay attention to the PHP Chinese website (www.php.cn)!

Statement

The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn

How to Grant Permissions to New MySQL UsersMay 09, 2025 am 12:16 AM

TograntpermissionstonewMySQLusers,followthesesteps:1)AccessMySQLasauserwithsufficientprivileges,2)CreateanewuserwiththeCREATEUSERcommand,3)UsetheGRANTcommandtospecifypermissionslikeSELECT,INSERT,UPDATE,orALLPRIVILEGESonspecificdatabasesortables,and4)

How to Add Users in MySQL: A Step-by-Step GuideMay 09, 2025 am 12:14 AM

ToaddusersinMySQLeffectivelyandsecurely,followthesesteps:1)UsetheCREATEUSERstatementtoaddanewuser,specifyingthehostandastrongpassword.2)GrantnecessaryprivilegesusingtheGRANTstatement,adheringtotheprincipleofleastprivilege.3)Implementsecuritymeasuresl

MySQL: Adding a new user with complex permissionsMay 09, 2025 am 12:09 AM

ToaddanewuserwithcomplexpermissionsinMySQL,followthesesteps:1)CreatetheuserwithCREATEUSER'newuser'@'localhost'IDENTIFIEDBY'password';.2)Grantreadaccesstoalltablesin'mydatabase'withGRANTSELECTONmydatabase.TO'newuser'@'localhost';.3)Grantwriteaccessto'

MySQL: String Data Types and CollationsMay 09, 2025 am 12:08 AM

The string data types in MySQL include CHAR, VARCHAR, BINARY, VARBINARY, BLOB, and TEXT. The collations determine the comparison and sorting of strings. 1.CHAR is suitable for fixed-length strings, VARCHAR is suitable for variable-length strings. 2.BINARY and VARBINARY are used for binary data, and BLOB and TEXT are used for large object data. 3. Sorting rules such as utf8mb4_unicode_ci ignores upper and lower case and is suitable for user names; utf8mb4_bin is case sensitive and is suitable for fields that require precise comparison.

MySQL: What length should I use for VARCHARs?May 09, 2025 am 12:06 AM

The best MySQLVARCHAR column length selection should be based on data analysis, consider future growth, evaluate performance impacts, and character set requirements. 1) Analyze the data to determine typical lengths; 2) Reserve future expansion space; 3) Pay attention to the impact of large lengths on performance; 4) Consider the impact of character sets on storage. Through these steps, the efficiency and scalability of the database can be optimized.

MySQL BLOB : are there any limits?May 08, 2025 am 12:22 AM

MySQLBLOBshavelimits:TINYBLOB(255bytes),BLOB(65,535bytes),MEDIUMBLOB(16,777,215bytes),andLONGBLOB(4,294,967,295bytes).TouseBLOBseffectively:1)ConsiderperformanceimpactsandstorelargeBLOBsexternally;2)Managebackupsandreplicationcarefully;3)Usepathsinst

MySQL : What are the best tools to automate users creation?May 08, 2025 am 12:22 AM

The best tools and technologies for automating the creation of users in MySQL include: 1. MySQLWorkbench, suitable for small to medium-sized environments, easy to use but high resource consumption; 2. Ansible, suitable for multi-server environments, simple but steep learning curve; 3. Custom Python scripts, flexible but need to ensure script security; 4. Puppet and Chef, suitable for large-scale environments, complex but scalable. Scale, learning curve and integration needs should be considered when choosing.

MySQL: Can I search inside a blob?May 08, 2025 am 12:20 AM

Yes,youcansearchinsideaBLOBinMySQLusingspecifictechniques.1)ConverttheBLOBtoaUTF-8stringwithCONVERTfunctionandsearchusingLIKE.2)ForcompressedBLOBs,useUNCOMPRESSbeforeconversion.3)Considerperformanceimpactsanddataencoding.4)Forcomplexdata,externalproc

See all articles