MySQL 读懂执行计划

1.输出列

Column	JSON Name	Meaning
id	select_id	The SELECT identifier
select_type	None	The SELECT type
table	table_name	The table for the output row
partitions	partitions	The matching partitions
type	access_type	The join type
possible_keys	possible_keys	The possible indexes to choose
key	key	The index actually chosen
key_len	key_length	The length of the chosen key
ref	ref	The columns compared to the index
rows	rows	Estimate of rows to be examined
filtered	filtered	Percentage of rows filtered by table condition
Extra	None	Additional information

二 具体解释

id

The SELECT identifier. This is the sequential number of the SELECT within the query. The value can be NULL if the row refers to the union result of other rows.

select_type

select_type Value	JSON Name	Meaning
SIMPLE	None	Simple SELECT (not using UNION or subqueries)
PRIMARY	None	Outermost SELECT
UNION	None	Second or later SELECT statement in a UNION
DEPENDENT UNION	dependent (true)	Second or later SELECT statement in a UNION, dependent on outer query
UNION RESULT	union_result	Result of a UNION.
SUBQUERY	None	First SELECT in subquery
DEPENDENT SUBQUERY	dependent (true)	First SELECT in subquery, dependent on outer query
DERIVED	None	Derived table
MATERIALIZED	materialized_from_subquery	Materialized subquery
UNCACHEABLE SUBQUERY	cacheable (false)	A subquery for which the result cannot be cached and must be re-evaluated for each row of the outer query
UNCACHEABLE UNION	cacheable (false)	The second or later select in a UNION that belongs to an uncacheable subquery (see UNCACHEABLE SUBQUERY)

DEPENDENT typically signifies the use of a correlated subquery.DEPENDENT SUBQUERY evaluation differs from UNCACHEABLE SUBQUERY evaluation. For DEPENDENT SUBQUERY, the subquery is re-evaluated only once for each set of different values of the variables from its outer context. For UNCACHEABLE SUBQUERY, the subquery is re-evaluated for each row of the outer context. Cacheability of subqueries differs from caching of query results in the query cache.Subquery caching occurs during query execution, whereas the query cache is used to store results only after query execution finishes. When you specify FORMAT=JSON with EXPLAIN, the output has no single property directly equivalent to select_type; the query_block property corresponds to a given SELECT. Properties equivalent to most of the SELECT subquery types just shown are available (an example being materialized_from_subquery for MATERIALIZED), and are displayed when appropriate. There are no JSON equivalents for SIMPLE or PRIMARY. The select_type value for non-SELECT statements displays the statement type for affected tables. For example, select_type is DELETE for DELETE statements. 

table

The name of the table to which the row of output refers. This can also be one of the following values:

• <unionm,n>: The row refers to the union of the rows with id values of M and N.

• : The row refers to the derived table result for the row with an id value of N. A derived table may result, for example, from a subquery in the FROM clause.

• : The row refers to the result of a materialized subquery for the row with an id value of N. 

partitions

The partitions from which records would be matched by the query. The value is NULL for nonpartitioned tables.

possible_keys

The possible_keys column indicates the indexes from which MySQL can choose to find the rows in this table. Note that this column is totally independent of the order of the tables as displayed in the output from EXPLAIN. That means that some of the keys in possible_keys might not be usable in practice with the generated table order. If this column is NULL (or undefined in JSON-formatted output), there are no relevant indexes. In this case, you may be able to improve the performance of your query by examining the WHERE clause to check whether it refers to some column or columns that would be suitable for indexing. If so, create an appropriate index and check the query with EXPLAIN again.

type

The join type.后面将展开介绍。

key

The key column indicates the key (index) that MySQL actually decided to use. If MySQL decides to use one of the possible_keys indexes to look up rows, that index is listed as the key value. It is possible that key will name an index that is not present in the possible_keys value. This can happen if none of the possible_keys indexes are suitable for looking up rows, but all the columns selected by the query are columns of some other index. That is, the named index covers the selected columns, so although it is not used to determine which rows to retrieve, an index scan is more efficient than a data row scan. For InnoDB, a secondary index might cover the selected columns even if the query also selects the primary key because InnoDB stores the primary key value with each secondary index. If key is NULL, MySQL found no index to use for executing the query more efficiently. To force MySQL to use or ignore an index listed in the possible_keys column, use FORCE INDEX, USE INDEX, or IGNORE INDEX in your query

key_len

The key_len column indicates the length of the key that MySQL decided to use. The value of key_len enables you to determine how many parts of a multiple-part key MySQL actually uses. If the key column says NULL, the key_len column also says NULL. Due to the key storage format, the key length is one greater for a column that can be NULL than for a NOT NULL column.

ref

The ref column shows which columns or constants are compared to the index named in the key column to select rows from the table. If the value is func, the value used is the result of some function. To see which function, use SHOW WARNINGS following EXPLAIN to see the extended EXPLAIN output. The function might actually be an operator such as an arithmetic operator.

rows

The rows column indicates the number of rows MySQL believes it must examine to execute the query. For InnoDB tables, this number is an estimate, and may not always be exact.

filtered

The filtered column indicates an estimated percentage of table rows that will be filtered by the table condition. The maximum value is 100, which means no filtering of rows occurred. Values decreasing from 100 indicate increasing amounts of filtering. rows shows the estimated number of rows examined and rows × filtered shows the number of rows that will be joined with the following table. For example, if rows is 1000 and filtered is 50.00 (50%), the number of rows to be joined with the following table is 1000 × 50% = 500.

三.Join Types

The type column of EXPLAIN output describes how tables are joined. In JSON-formatted output, these are found as values of the access_type property. The following list describes the join types, ordered from the best type to the worst:

system

The table has only one row (= system table). This is a special case of the const join type.

const

The table has at most one matching row, which is read at the start of the query. Because there is only one row, values from the column in this row can be regarded as constants by the rest of the optimizer. const tables are very fast because they are read only once. const is used when you compare all parts of a PRIMARY KEY or UNIQUE index to constant values. In the following queries, tbl_name can be used as a const table:

SELECT * FROM tbl_name WHERE primary_key=1;
SELECT * FROM tbl_name
 WHERE primary_key_part1=1 AND primary_key_part2=2;

eq_ref

One row is read from this table for each combination of rows from the previous tables. Other than the system and const types, this is the best possible join type. It is used when all parts of an index are used by the join and the index is a PRIMARY KEY or UNIQUE NOT NULL index. eq_ref can be used for indexed columns that are compared using the = operator. The comparison value can be a constant or an expression that uses columns from tables that are read before this table. In the following examples, MySQL can use an eq_ref join to process ref_table:

SELECT * FROM ref_table,other_table
 WHERE ref_table.key_column=other_table.column;
SELECT * FROM ref_table,other_table
 WHERE ref_table.key_column_part1=other_table.column
 AND ref_table.key_column_part2=1;

ref

All rows with matching index values are read from this table for each combination of rows from the previous tables. ref is used if the join uses only a leftmost prefix of the key or if the key is not a PRIMARY KEY or UNIQUE index (in other words, if the join cannot select a single row based on the key value). If the key that is used matches only a few rows, this is a good join type.ref can be used for indexed columns that are compared using the = or <=> operator. In the following examples, MySQL can use a ref join to process ref_table:

SELECT * FROM ref_table WHERE key_column=expr;
SELECT * FROM ref_table,other_table
 WHERE ref_table.key_column=other_table.column;
SELECT * FROM ref_table,other_table
 WHERE ref_table.key_column_part1=other_table.column
 AND ref_table.key_column_part2=1;

fulltext

The join is performed using a FULLTEXT index.

ref_or_null

This join type is like ref, but with the addition that MySQL does an extra search for rows that contain NULL values. This join type optimization is used most often in resolving subqueries. In the following examples, MySQL can use a ref_or_null join to process ref_table:

SELECT * FROM ref_table
 WHERE key_column=expr OR key_column IS NULL;

index_merge

This join type indicates that the Index Merge optimization is used. In this case, the key column in the output row contains a list of indexes used, and key_len contains a list of the longest key parts for the indexes used.

unique_subquery

This type replaces eq_ref for some IN subqueries of the following form:

value IN (SELECT primary_key FROM single_table WHERE some_expr)

unique_subquery is just an index lookup function that replaces the subquery completely for better efficiency.

index_subquery

This join type is similar to unique_subquery. It replaces IN subqueries, but it works for nonunique indexes in subqueries of the following form:

value IN (SELECT key_column FROM single_table WHERE some_expr)

range

Only rows that are in a given range are retrieved, using an index to select the rows. The key column in the output row indicates which index is used. The key_len contains the longest key part that was used. The ref column is NULL for this type. range can be used when a key column is compared to a constant using any of the =, <>, >, >=, <, <=, IS NULL, <=>, BETWEEN, LIKE, or IN() operators:

SELECT * FROM tbl_name
 WHERE key_column = 10;
SELECT * FROM tbl_name
 WHERE key_column BETWEEN 10 and 20;
SELECT * FROM tbl_name
WHERE key_column IN (10,20,30);
SELECT * FROM tbl_name
 WHERE key_part1 = 10 AND key_part2 IN (10,20,30);

index

The index join type is the same as ALL, except that the index tree is scanned. This occurs two ways:

• If the index is a covering index for the queries and can be used to satisfy all data required from the table, only the index tree is scanned. In this case, the Extra column says Using index. An index-only scan usually is faster than ALL because the size of the index usually is smaller than the table data.

• A full table scan is performed using reads from the index to look up data rows in index order. Uses index does not appear in the Extra column.

MySQL can use this join type when the query uses only columns that are part of a single index.

ALL

A full table scan is done for each combination of rows from the previous tables. This is normally not good if the table is the first table not marked const, and usually very bad in all other cases. Normally, you can avoid ALL by adding indexes that enable row retrieval from the table based on constant values or column values from earlier tables.