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 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;

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;

See Section 7.2.7, “IS NULL Optimization”.

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. For more information, see Section 7.2.6, “Index Merge Optimization”.

unique_subquery

This type replaces 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 non-unique 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, 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

This join type is the same as ALL, except that only the index tree is scanned. This usually is faster than ALL because the index file usually is smaller than the data file.

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 allow row retrieval from the table based on constant values or column values from earlier tables.

Distinct

MySQL is looking for distinct values, so it stops searching for more rows for the current row combination after it has found the first matching row.

Not exists

MySQL was able to do a LEFT JOIN optimization on the query and does not examine more rows in this table for the previous row combination after it finds one row that matches the LEFT JOIN criteria. Here is an example of the type of query that can be optimized this way:

SELECT * FROM t1 LEFT JOIN t2 ON t1.id=t2.id
  WHERE t2.id IS NULL;

Assume that t2.id is defined as NOT NULL. In this case, MySQL scans t1 and looks up the rows in t2 using the values of t1.id. If MySQL finds a matching row in t2, it knows that t2.id can never be NULL, and does not scan through the rest of the rows in t2 that have the same id value. In other words, for each row in t1, MySQL needs to do only a single lookup in t2, regardless of how many rows actually match in t2.

range checked for each record (index map: N)

MySQL found no good index to use, but found that some of indexes might be used after column values from preceding tables are known. For each row combination in the preceding tables, MySQL checks whether it is possible to use a range or index_merge access method to retrieve rows. This is not very fast, but is faster than performing a join with no index at all. The applicability criteria are as described in Section 7.2.5, “Range Optimization”, and Section 7.2.6, “Index Merge Optimization”, with the exception that all column values for the preceding table are known and considered to be constants.

Using filesort

MySQL must do an extra pass to find out how to retrieve the rows in sorted order. The sort is done by going through all rows according to the join type and storing the sort key and pointer to the row for all rows that match the WHERE clause. The keys then are sorted and the rows are retrieved in sorted order. See Section 7.2.12, “ORDER BY Optimization”.

Using index

The column information is retrieved from the table using only information in the index tree without having to do an additional seek to read the actual row. This strategy can be used when the query uses only columns that are part of a single index.

Using temporary

To resolve the query, MySQL needs to create a temporary table to hold the result. This typically happens if the query contains GROUP BY and ORDER BY clauses that list columns differently.

Using where

A WHERE clause is used to restrict which rows to match against the next table or send to the client. Unless you specifically intend to fetch or examine all rows from the table, you may have something wrong in your query if the Extra value is not Using where and the table join type is ALL or index.

If you want to make your queries as fast as possible, you should look out for Extra values of Using filesort and Using temporary.

Using sort_union(...), Using union(...), Using intersect(...)

These indicate how index scans are merged for the index_merge join type. See Section 7.2.6, “Index Merge Optimization”, for more information.

Using index for group-by

Similar to the Using index way of accessing a table, Using index for group-by indicates that MySQL found an index that can be used to retrieve all columns of a GROUP BY or DISTINCT query without any extra disk access to the actual table. Additionally, the index is used in the most efficient way so that for each group, only a few index entries are read. For details, see Section 7.2.13, “GROUP BY Optimization”.

Using where with pushed condition

This item applies to NDB Cluster tables only. It means that MySQL Cluster is using condition pushdown to improve the efficiency of a direct comparison (=) between a non-indexed column and a constant. In such cases, the condition is “pushed down” to the cluster's data nodes where it is evaluated in all partitions simultaneously. This eliminates the need to send non-matching rows over the network, and can speed up such queries by a factor of 5 to 10 times over cases where condition pushdown could be but is not used.

Suppose that you have a Cluster table defined as follows:

CREATE TABLE t1 (
    a INT, 
    b INT, 
    KEY(a)
) ENGINE=NDBCLUSTER;

In this case, condition pushdown can be used with a query such as this one:

SELECT a,b FROM t1 WHERE b = 10;

This can be seen in the output of EXPLAIN SELECT, as shown here:

mysql> EXPLAIN SELECT a,b FROM t1 WHERE b = 10\G
*************************** 1. row ***************************
           id: 1
  select_type: SIMPLE
        table: t1
         type: ALL
possible_keys: NULL
          key: NULL
      key_len: NULL
          ref: NULL
         rows: 10
        Extra: Using where with pushed condition

Condition pushdown cannot be used with either of these two queries:

SELECT a,b FROM t1 WHERE a = 10;
SELECT a,b FROM t1 WHERE b + 1 = 10;

With regard to the first of these two queries, condition pushdown is not applicable because an index exists on column a. In the case of the second query, a condition pushdown cannot be employed because the comparison involving the non-indexed column b is an indirect one. (However, it would apply if you were to reduce b + 1 = 10 to b = 9 in the WHERE clause.)

However, a condition pushdown may also be employed when an indexed column column is compared with a constant using a > or < operator:

mysql> EXPLAIN SELECT a,b FROM t1 WHERE a<2\G
*************************** 1. row ***************************
           id: 1
  select_type: SIMPLE
        table: t1
         type: range
possible_keys: a
          key: a
      key_len: 5
          ref: NULL
         rows: 2
        Extra: Using where with pushed condition

With regard to condition pushdown, keep in mind that: