:: DEVELOPER ZONE
EXPLAIN tbl_name
Or:
EXPLAIN SELECT select_options
The EXPLAIN statement can be used either as a synonym for
DESCRIBE or as a way to obtain information about how MySQL executes
a SELECT statement:
The EXPLAIN syntax is synonymous with tbl_nameDESCRIBE
or
tbl_nameSHOW COLUMNS FROM .
tbl_name
When you precede a SELECT statement with the keyword EXPLAIN,
MySQL explains how it would process the SELECT, providing
information about how tables are joined and in which order.
This section provides information about the second use of EXPLAIN.
With the help of EXPLAIN, you can see when you must add indexes
to tables to get a faster SELECT that uses indexes to find
records.
If you have a problem with incorrect index usage, you should run
ANALYZE TABLE to update table statistics such as cardinality of
keys, which can affect the choices the optimizer makes. See Section 13.5.2.1, “ANALYZE TABLE Syntax”.
You can also see whether the optimizer joins the tables in an optimal order.
To force the optimizer to use a join order corresponding to the order
in which the tables are named in the SELECT statement, begin the
statement with SELECT STRAIGHT_JOIN rather than just SELECT.
EXPLAIN returns a row of information for each table used in the
SELECT statement. The tables are listed in the output in the order
that MySQL would read them while processing the query. MySQL resolves
all joins using a single-sweep
multi-join method. This means that MySQL reads a row from the first
table, then finds a matching row in the second table, then in the third table,
and so on. When all tables are processed, it outputs the selected columns and
backtracks through the table list until a table is found for which there are
more matching rows. The next row is read from this table and the process
continues with the next table.
In MySQL version 4.1, the EXPLAIN output format was changed to work
better with constructs such as UNION statements, subqueries, and
derived tables. Most notable is the addition of two new columns: id
and select_type. You do not see these columns when using servers
older than MySQL 4.1.
Each output row from EXPLAIN provides information about one table, and
each row consists of the following columns:
id
The SELECT identifier. This is the sequential number of the
SELECT within the query.
select_type
The type of SELECT, which can be any of the following:
SIMPLE
Simple SELECT (not using UNION or subqueries)
PRIMARY
Outermost SELECT
UNION
Second or later SELECT statement in a UNION
DEPENDENT UNION
Second or later SELECT statement in a UNION, dependent on outer
query
UNION RESULT
Result of a UNION.
SUBQUERY
First SELECT in subquery
DEPENDENT SUBQUERY
First SELECT in subquery, dependent on outer query
DERIVED
Derived table SELECT (subquery in FROM clause)
table
The table to which the row of output refers.
type
The join type. The different join types are listed here, 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 with constant values. In the
following queries, tbl_name can be used as a const table:
SELECT * FROMtbl_nameWHEREprimary_key=1; SELECT * FROMtbl_nameWHEREprimary_key_part1=1 ANDprimary_key_part2=2;
eq_ref
One row is read from this table for each combination of rows from
the previous tables. Other than the 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 * FROMref_table,other_tableWHEREref_table.key_column=other_table.column; SELECT * FROMref_table,other_tableWHEREref_table.key_column_part1=other_table.columnANDref_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 =
operator.
In the following examples, MySQL can use a ref join to process
ref_table:
SELECT * FROMref_tableWHEREkey_column=expr; SELECT * FROMref_table,other_tableWHEREref_table.key_column=other_table.column; SELECT * FROMref_table,other_tableWHEREref_table.key_column_part1=other_table.columnANDref_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 new for MySQL 4.1.1 and is mostly used when resolving
subqueries.
In the following examples, MySQL can use a ref_or_null join to process
ref_table:
SELECT * FROMref_tableWHEREkey_column=exprORkey_columnIS NULL;
index_merge
This join type indicates that the Index Merge optimization is used.
In this case, the key column 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:
valueIN (SELECTprimary_keyFROMsingle_tableWHEREsome_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:
valueIN (SELECTkey_columnFROMsingle_tableWHEREsome_expr)
range
Only rows that are in a given range are retrieved, using an index to
select the rows. The key column 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 for when a key column is compared to a
constant using any of the =, <>, >, >=, <,
<=, IS NULL, <=>, BETWEEN, or IN operators:
SELECT * FROMtbl_nameWHEREkey_column= 10; SELECT * FROMtbl_nameWHEREkey_columnBETWEEN 10 and 20; SELECT * FROMtbl_nameWHEREkey_columnIN (10,20,30); SELECT * FROMtbl_nameWHEREkey_part1= 10 ANDkey_part2IN (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.
possible_keys
The possible_keys column indicates which indexes MySQL could use 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, 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 see 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.
See Section 13.2.2, “ALTER TABLE Syntax”.
To see what indexes a table has, use SHOW INDEX FROM .
tbl_name
key
The key column indicates the key (index) that MySQL actually decided
to use. The key is NULL if no index was chosen. 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.
See Section 13.1.7, “SELECT Syntax”.
For MyISAM and BDB tables, running ANALYZE TABLE
helps the optimizer choose better indexes. For MyISAM tables,
myisamchk --analyze does the same. See Section 13.5.2.1, “ANALYZE TABLE Syntax” and Section 5.7.3, “Table Maintenance and Crash Recovery”.
key_len
The key_len column indicates the length of the key that MySQL
decided to use. The length is NULL if the key column says
NULL. Note that the value of key_len allows you to determine
how many parts of a multiple-part key MySQL actually uses.
ref
The ref column shows which columns or constants are used with the
key to select rows from the table.
rows
The rows column indicates the number of rows MySQL
believes it must examine to execute the query.
Extra
This column contains additional information about how MySQL resolves the query. Here is an explanation of the different text strings that can appear in this column:
Distinct
MySQL 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: #)
MySQL found no good index to use, but found that some of indexes might
be used once 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. 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.
This is not very fast, but is faster than performing a join with no index at all.
Using filesort
MySQL needs to 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 7.2.10, “How MySQL Optimizes ORDER BY”.
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 7.2.11, “How MySQL Optimizes GROUP BY”.
You can get a good indication of how good a join is by taking the
product of the values in the rows column of the EXPLAIN
output. This should tell you roughly how many rows MySQL must examine to
execute the query. If you restrict queries with the max_join_size
system variable, this product also is used to determine which multiple-table
SELECT statements to execute.
See Section 7.5.2, “Tuning Server Parameters”.
The following example shows how a multiple-table join can be optimized
progressively based on the information provided by EXPLAIN.
Suppose that you have the SELECT statement shown here and you plan to
examine it using EXPLAIN:
EXPLAIN SELECT tt.TicketNumber, tt.TimeIn,
tt.ProjectReference, tt.EstimatedShipDate,
tt.ActualShipDate, tt.ClientID,
tt.ServiceCodes, tt.RepetitiveID,
tt.CurrentProcess, tt.CurrentDPPerson,
tt.RecordVolume, tt.DPPrinted, et.COUNTRY,
et_1.COUNTRY, do.CUSTNAME
FROM tt, et, et AS et_1, do
WHERE tt.SubmitTime IS NULL
AND tt.ActualPC = et.EMPLOYID
AND tt.AssignedPC = et_1.EMPLOYID
AND tt.ClientID = do.CUSTNMBR;
For this example, make the following assumptions:
The columns being compared have been declared as follows:
| Table | Column | Column Type |
tt |
ActualPC |
CHAR(10)
|
tt |
AssignedPC |
CHAR(10)
|
tt |
ClientID |
CHAR(10)
|
et |
EMPLOYID |
CHAR(15)
|
do |
CUSTNMBR |
CHAR(15)
|
The tables have the following indexes:
| Table | Index |
tt |
ActualPC
|
tt |
AssignedPC
|
tt |
ClientID
|
et |
EMPLOYID (primary key)
|
do |
CUSTNMBR (primary key)
|
The tt.ActualPC values are not evenly distributed.
Initially, before any optimizations have been performed, the EXPLAIN
statement produces the following information:
table type possible_keys key key_len ref rows Extra
et ALL PRIMARY NULL NULL NULL 74
do ALL PRIMARY NULL NULL NULL 2135
et_1 ALL PRIMARY NULL NULL NULL 74
tt ALL AssignedPC, NULL NULL NULL 3872
ClientID,
ActualPC
range checked for each record (key map: 35)
Because type is ALL for each table, this output indicates
that MySQL is generating a Cartesian product of all the tables; that is,
every combination of rows. This takes quite a long time, because the
product of the number of rows in each table must be examined. For the case
at hand, this product is 74 * 2135 * 74 * 3872 = 45,268,558,720 rows.
If the tables were bigger, you can only imagine how long it would take.
One problem here is that MySQL can use indexes on columns more efficiently
if they are declared the same. (For ISAM tables, indexes may not be
used at all unless the columns are declared the same.) In this context,
VARCHAR and CHAR are the same unless they are declared as
different lengths. Because tt.ActualPC is declared as CHAR(10)
and et.EMPLOYID is declared as CHAR(15), there is a length
mismatch.
To fix this disparity between column lengths, use ALTER TABLE to
lengthen ActualPC from 10 characters to 15 characters:
mysql> ALTER TABLE tt MODIFY ActualPC VARCHAR(15);
tt.ActualPC and et.EMPLOYID are both VARCHAR(15).
Executing the EXPLAIN statement again produces this result:
table type possible_keys key key_len ref rows Extra
tt ALL AssignedPC, NULL NULL NULL 3872 Using
ClientID, where
ActualPC
do ALL PRIMARY NULL NULL NULL 2135
range checked for each record (key map: 1)
et_1 ALL PRIMARY NULL NULL NULL 74
range checked for each record (key map: 1)
et eq_ref PRIMARY PRIMARY 15 tt.ActualPC 1
This is not perfect, but is much better: The product of the rows
values is less by a factor of 74. This version is executed in a couple
of seconds.
A second alteration can be made to eliminate the column length mismatches
for the tt.AssignedPC = et_1.EMPLOYID and tt.ClientID = do.CUSTNMBR comparisons:
mysql> ALTER TABLE tt MODIFY AssignedPC VARCHAR(15),
-> MODIFY ClientID VARCHAR(15);
EXPLAIN produces the output shown here:
table type possible_keys key key_len ref rows Extra
et ALL PRIMARY NULL NULL NULL 74
tt ref AssignedPC, ActualPC 15 et.EMPLOYID 52 Using
ClientID, where
ActualPC
et_1 eq_ref PRIMARY PRIMARY 15 tt.AssignedPC 1
do eq_ref PRIMARY PRIMARY 15 tt.ClientID 1
This is almost as good as it can get.
The remaining problem is that, by default, MySQL assumes that values
in the tt.ActualPC column are evenly distributed, and that is not the
case for the tt table. Fortunately, it is easy to tell MySQL
to analyze the key distribution:
mysql> ANALYZE TABLE tt;
The join is perfect, and EXPLAIN produces this result:
table type possible_keys key key_len ref rows Extra
tt ALL AssignedPC NULL NULL NULL 3872 Using
ClientID, where
ActualPC
et eq_ref PRIMARY PRIMARY 15 tt.ActualPC 1
et_1 eq_ref PRIMARY PRIMARY 15 tt.AssignedPC 1
do eq_ref PRIMARY PRIMARY 15 tt.ClientID 1
Note that the rows column in the output from EXPLAIN is an
educated guess from the MySQL join optimizer. You should check whether the
numbers are even close to the truth. If not, you may get better performance
by using STRAIGHT_JOIN in your SELECT statement and trying
to list the tables in a different order in the FROM clause.
© 1995-2005 MySQL AB. All rights reserved.

User Comments
I think you should say that if the query returns no data, the explain won't work, and will say 'Impossible WHERE noticed after reading const tables'.
EXPLAIN appears to be empirical.
EXPLAIN does not look at
an index and a select and determine the potential use of
the index. Instead EXPLAIN appears to look at the actual
data and determine the actual use of the index. In a development
database this becomes problematic requiring the generations
of representative data. Occasionally it is difficult to predict
how the data will effect the application of an index and it
is not clear that your index does not support your select or
your test data does not exercise the index.
More details of what to expect from EXPLAIN should be included
in the document.
In a 5,500 rows tableset - the following query took 202.30 sec in MySQL Control Center prior to a "analyze table partners; analyze table phones;" query!!
select s.id as id, s.label_text, p.phone_number as phonenumber, f.phone_number as faxnumber from partners as s
left join phones as p on s.aid=p.aid and p.phone_type=0 and p.preferred=1
left join phones as f on s.aid=f.aid and f.phone_type=1 and f.preferred=1
where s.partner_type<3 and s.voided_by=0
So - my 'tip' is to really RTFM very carefully where it says: run analyze table frequently :)
(needless to say that after the analyze query - mySQL provided me with the initial 1,000 rows in just under 500 msecs!!)
When creating query's on large ammounts of data it's smart to take a look at the optimization part of the documentation.
It will help you understand the way MySQL executes query's.
Another good thing to read is this http://dev.mysql.com/doc/mysql/en/Data_size.html
The section contains information regarding keys and such which will also help you to improve SELECT perfomance (in regard to the explain method).
I have to add though that explain might give you a lot of usefull info, (IMHO) it lacks output relevant to single table queries. IE when making a FULLTEXT search on one table useing a multi column FULLTEXT index I get a keylen of 0. I'm not sure if this is the same as NULL (none used). A more precise explanation of what actually is going on would be nice.
To follow up on Andres's post, it should be noted that MySQL 4.0 and 4.1 differ in their use of a ResultSet with EXPLAIN.
In 4.0, you can receive a result with just a mysterious "Comment" column (none of the rest of the columns as described in explain.html) showing why it is angry at you.
In 4.1, you will receive the result set as described and the "Extra" column will contain the error message.
As an example, try the following query on a 4.0 server then on 4.1:
explain select * from mysql.db where 1=0\G
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