:: 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 = or
<=> 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 13.1.2, “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 13.2.7, “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 5.8.3, “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.
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