Single-table syntax:
DELETE [LOW_PRIORITY] [QUICK] [IGNORE] FROMtbl_name
[WHEREwhere_condition
] [ORDER BY ...] [LIMITrow_count
]
Multiple-table syntax:
DELETE [LOW_PRIORITY] [QUICK] [IGNORE]tbl_name
[.*] [,tbl_name
[.*]] ... FROMtable_references
[WHEREwhere_condition
]
Or:
DELETE [LOW_PRIORITY] [QUICK] [IGNORE] FROMtbl_name
[.*] [,tbl_name
[.*]] ... USINGtable_references
[WHEREwhere_condition
]
For the single-table syntax, the DELETE
statement deletes rows from tbl_name
and returns the number of rows deleted. The
WHERE
clause, if given, specifies the
conditions that identify which rows to delete. With no
WHERE
clause, all rows are deleted. If the
ORDER BY
clause is specified, the rows are
deleted in the order that is specified. The
LIMIT
clause places a limit on the number of
rows that can be deleted.
For the multiple-table syntax, DELETE
deletes
from each tbl_name
the rows that
satisfy the conditions. In this case, ORDER
BY
and LIMIT
cannot be used.
where_condition
is an expression that
evaluates to true for each row to be deleted. It is specified as
described in Section 13.2.7, “SELECT
Syntax”.
As stated, a DELETE
statement with no
WHERE
clause deletes all rows. A faster way
to do this, when you do not want to know the number of deleted
rows, is to use TRUNCATE TABLE
. See
Section 13.2.9, “TRUNCATE
Syntax”.
If you delete the row containing the maximum value for an
AUTO_INCREMENT
column, the value is reused
later for a BDB
table, but not for a
MyISAM
or InnoDB
table. If
you delete all rows in the table with DELETE FROM
(without a
tbl_name
WHERE
clause) in
AUTOCOMMIT
mode, the sequence starts over for
all storage engines except InnoDB
and
MyISAM
. There are some exceptions to this
behavior for InnoDB
tables, as discussed in
Section 14.2.6.3, “How AUTO_INCREMENT
Columns Work in InnoDB
”.
For MyISAM
and BDB
tables,
you can specify an AUTO_INCREMENT
secondary
column in a multiple-column key. In this case, reuse of values
deleted from the top of the sequence occurs even for
MyISAM
tables. See
Section 3.6.9, “Using AUTO_INCREMENT
”.
The DELETE
statement supports the following
modifiers:
If you specify LOW_PRIORITY
, the server
delays execution of the DELETE
until no
other clients are reading from the table.
For MyISAM
tables, if you use the
QUICK
keyword, the storage engine does
not merge index leaves during delete, which may speed up
some kinds of delete operations.
The IGNORE
keyword causes MySQL to ignore
all errors during the process of deleting rows. (Errors
encountered during the parsing stage are processed in the
usual manner.) Errors that are ignored due to the use of
OPTION
are returned as warnings.
The speed of delete operations may also be affected by factors
discussed in Section 7.2.18, “Speed of DELETE
Statements”.
In MyISAM
tables, deleted rows are maintained
in a linked list and subsequent INSERT
operations reuse old row positions. To reclaim unused space and
reduce file sizes, use the OPTIMIZE TABLE
statement or the myisamchk utility to
reorganize tables. OPTIMIZE TABLE
is easier,
but myisamchk is faster. See
Section 13.5.2.5, “OPTIMIZE TABLE
Syntax”, and
Section 8.3, “myisamchk — MyISAM Table-Maintenance Utility”.
The QUICK
modifier affects whether index
leaves are merged for delete operations. DELETE
QUICK
is most useful for applications where index
values for deleted rows are replaced by similar index values
from rows inserted later. In this case, the holes left by
deleted values are reused.
DELETE QUICK
is not useful when deleted
values lead to undef-filled index blocks spanning a range of
index values for which new inserts occur again. In this case,
use of QUICK
can lead to wasted space in the
index that remains unreclaimed. Here is an example of such a
scenario:
Create a table that contains an indexed
AUTO_INCREMENT
column.
Insert many rows into the table. Each insert results in an index value that is added to the high end of the index.
Delete a block of rows at the low end of the column range
using DELETE QUICK
.
In this scenario, the index blocks associated with the deleted
index values become undef-filled but are not merged with other
index blocks due to the use of QUICK
. They
remain undef-filled when new inserts occur, because new rows do
not have index values in the deleted range. Furthermore, they
remain undef-filled even if you later use
DELETE
without QUICK
,
unless some of the deleted index values happen to lie in index
blocks within or adjacent to the undef-filled blocks. To reclaim
unused index space under these circumstances, use
OPTIMIZE TABLE
.
If you are going to delete many rows from a table, it might be
faster to use DELETE QUICK
followed by
OPTIMIZE TABLE
. This rebuilds the index
rather than performing many index block merge operations.
The MySQL-specific LIMIT
option to
row_count
DELETE
tells the server the maximum number of
rows to be deleted before control is returned to the client.
This can be used to ensure that a given
DELETE
statement does not take too much time.
You can simply repeat the DELETE
statement
until the number of affected rows is less than the
LIMIT
value.
If the DELETE
statement includes an
ORDER BY
clause, the rows are deleted in the
order specified by the clause. This is really useful only in
conjunction with LIMIT
. For example, the
following statement finds rows matching the
WHERE
clause, sorts them by
timestamp_column
, and deletes the first
(oldest) one:
DELETE FROM somelog WHERE user = 'jcole' ORDER BY timestamp_column LIMIT 1;
You can specify multiple tables in a DELETE
statement to delete rows from one or more tables depending on
the particular condition in the WHERE
clause.
However, you cannot use ORDER BY
or
LIMIT
in a multiple-table
DELETE
. The
table_references
clause lists the
tables involved in the join. Its syntax is described in
Section 13.2.7.1, “JOIN
Syntax”.
For the first multiple-table syntax, only matching rows from the
tables listed before the FROM
clause are
deleted. For the second multiple-table syntax, only matching
rows from the tables listed in the FROM
clause (before the USING
clause) are deleted.
The effect is that you can delete rows from many tables at the
same time and have additional tables that are used only for
searching:
DELETE t1, t2 FROM t1, t2, t3 WHERE t1.id=t2.id AND t2.id=t3.id;
Or:
DELETE FROM t1, t2 USING t1, t2, t3 WHERE t1.id=t2.id AND t2.id=t3.id;
These statements use all three tables when searching for rows to
delete, but delete matching rows only from tables
t1
and t2
.
The preceding examples show inner joins that use the comma
operator, but multiple-table DELETE
statements can use any type of join allowed in
SELECT
statements, such as LEFT
JOIN
.
The syntax allows .*
after the table names
for compatibility with Access.
If you use a multiple-table DELETE
statement
involving InnoDB
tables for which there are
foreign key constraints, the MySQL optimizer might process
tables in an order that differs from that of their parent/child
relationship. In this case, the statement fails and rolls back.
Instead, you should delete from a single table and rely on the
ON DELETE
capabilities that
InnoDB
provides to cause the other tables to
be modified accordingly.
Note: If you provide an alias for a table, you must use the alias when referring to the table:
DELETE t1 FROM test AS t1, test2 WHERE ...
Cross-database deletes are supported for multiple-table deletes, but in this case, you must refer to the tables without using aliases. For example:
DELETE test1.tmp1, test2.tmp2 FROM test1.tmp1, test2.tmp2 WHERE ...
Currently, you cannot delete from a table and select from the same table in a subquery.
DOexpr
[,expr
] ...
DO
executes the expressions but does not
return any results. In most respects, DO
is
shorthand for SELECT
, but has the advantage that it is slightly faster
when you do not care about the result.
expr
,
...
DO
is useful primarily with functions that
have side effects, such as RELEASE_LOCK()
.
HANDLERtbl_name
OPEN [ ASalias
] HANDLERtbl_name
READindex_name
{ = | >= | <= | < } (value1
,value2
,...) [ WHEREwhere_condition
] [LIMIT ... ] HANDLERtbl_name
READindex_name
{ FIRST | NEXT | PREV | LAST } [ WHEREwhere_condition
] [LIMIT ... ] HANDLERtbl_name
READ { FIRST | NEXT } [ WHEREwhere_condition
] [LIMIT ... ] HANDLERtbl_name
CLOSE
The HANDLER
statement provides direct access
to table storage engine interfaces. It is available for
MyISAM
and InnoDB
tables.
The HANDLER ... OPEN
statement opens a table,
making it accessible via subsequent HANDLER ...
READ
statements. This table object is not shared by
other threads and is not closed until the thread calls
HANDLER ... CLOSE
or the thread terminates.
If you open the table using an alias, further references to the
open table with other HANDLER
statements must
use the alias rather than the table name.
The first HANDLER ... READ
syntax fetches a
row where the index specified satisfies the given values and the
WHERE
condition is met. If you have a
multiple-column index, specify the index column values as a
comma-separated list. Either specify values for all the columns
in the index, or specify values for a leftmost prefix of the
index columns. Suppose that an index my_idx
includes three columns named col_a
,
col_b
, and col_c
, in that
order. The HANDLER
statement can specify
values for all three columns in the index, or for the columns in
a leftmost prefix. For example:
HANDLER ... READ my_idx = (col_a_val,col_b_val,col_c_val) ... HANDLER ... READ my_idx = (col_a_val,col_b_val) ... HANDLER ... READ my_idx = (col_a_val) ...
To employ the HANDLER
interface to refer to a
table's PRIMARY KEY
, use the quoted
identifier `PRIMARY`
:
HANDLER tbl_name
READ `PRIMARY` ...
The second HANDLER ... READ
syntax fetches a
row from the table in index order that matches the
WHERE
condition.
The third HANDLER ... READ
syntax fetches a
row from the table in natural row order that matches the
WHERE
condition. It is faster than
HANDLER
when a full
table scan is desired. Natural row order is the order in which
rows are stored in a tbl_name
READ
index_name
MyISAM
table data file.
This statement works for InnoDB
tables as
well, but there is no such concept because there is no separate
data file.
Without a LIMIT
clause, all forms of
HANDLER ... READ
fetch a single row if one is
available. To return a specific number of rows, include a
LIMIT
clause. It has the same syntax as for
the SELECT
statement. See
Section 13.2.7, “SELECT
Syntax”.
HANDLER ... CLOSE
closes a table that was
opened with HANDLER ... OPEN
.
HANDLER
is a somewhat low-level statement.
For example, it does not provide consistency. That is,
HANDLER ... OPEN
does
not take a snapshot of the table, and does
not lock the table. This means that after a
HANDLER ... OPEN
statement is issued, table
data can be modified (by the current thread or other threads)
and these modifications might be only partially visible to
HANDLER ... NEXT
or HANDLER ...
PREV
scans.
There are several reasons to use the HANDLER
interface instead of normal SELECT
statements:
HANDLER
is faster than
SELECT
:
A designated storage engine handler object is allocated
for the HANDLER ... OPEN
. The object
is reused for subsequent HANDLER
statements for that table; it need not be reinitialized
for each one.
There is less parsing involved.
There is no optimizer or query-checking overhead.
The table does not have to be locked between two handler requests.
The handler interface does not have to provide a
consistent look of the data (for example, dirty reads
are allowed), so the storage engine can use
optimizations that SELECT
does not
normally allow.
For applications that use a low-level
ISAM
-like interface,
HANDLER
makes it much easier to port them
to MySQL.
HANDLER
enables you to traverse a
database in a manner that is difficult (or even impossible)
to accomplish with SELECT
. The
HANDLER
interface is a more natural way
to look at data when working with applications that provide
an interactive user interface to the database.
INSERT [LOW_PRIORITY | DELAYED | HIGH_PRIORITY] [IGNORE] [INTO]tbl_name
[(col_name
,...)] VALUES ({expr
| DEFAULT},...),(...),... [ ON DUPLICATE KEY UPDATEcol_name
=expr
, ... ]
Or:
INSERT [LOW_PRIORITY | DELAYED | HIGH_PRIORITY] [IGNORE] [INTO]tbl_name
SETcol_name
={expr
| DEFAULT}, ... [ ON DUPLICATE KEY UPDATEcol_name
=expr
, ... ]
Or:
INSERT [LOW_PRIORITY | HIGH_PRIORITY] [IGNORE] [INTO]tbl_name
[(col_name
,...)] SELECT ... [ ON DUPLICATE KEY UPDATEcol_name
=expr
, ... ]
INSERT
inserts new rows into an existing
table. The INSERT ... VALUES
and
INSERT ... SET
forms of the statement insert
rows based on explicitly specified values. The INSERT
... SELECT
form inserts rows selected from another
table or tables. INSERT ... SELECT
is
discussed further in Section 13.2.4.1, “INSERT ... SELECT
Syntax”.
You can use REPLACE
instead of
INSERT
to overwrite old rows.
REPLACE
is the counterpart to INSERT
IGNORE
in the treatment of new rows that contain
unique key values that duplicate old rows: The new rows are used
to replace the old rows rather than being discarded. See
Section 13.2.6, “REPLACE
Syntax”.
tbl_name
is the table into which rows
should be inserted. The columns for which the statement provides
values can be specified as follows:
You can provide a comma-separated list of column names
following the table name. In this case, a value for each
named column must be provided by the
VALUES
list or the
SELECT
statement.
If you do not specify a list of column names for
INSERT ... VALUES
or INSERT ...
SELECT
, values for every column in the table must
be provided by the VALUES
list or the
SELECT
statement. If you do not know the
order of the columns in the table, use DESCRIBE
to find out.
tbl_name
The SET
clause indicates the column names
explicitly.
Column values can be given in several ways:
If you are not running in strict SQL mode, any column not explicitly given a value is set to its default (explicit or implicit) value. For example, if you specify a column list that does not name all the columns in the table, unnamed columns are set to their default values. Default value assignment is described in Section 11.1.4, “Data Type Default Values”. See also Section 1.9.6.2, “Constraints on Invalid Data”.
If you want an INSERT
statement to
generate an error unless you explicitly specify values for
all columns that do not have a default value, you should use
strict mode. See Section 5.2.5, “The Server SQL Mode”.
Use the keyword DEFAULT
to set a column
explicitly to its default value. This makes it easier to
write INSERT
statements that assign
values to all but a few columns, because it enables you to
avoid writing an incomplete VALUES
list
that does not include a value for each column in the table.
Otherwise, you would have to write out the list of column
names corresponding to each value in the
VALUES
list.
You can also use
DEFAULT(
as a more general form that can be used in expressions to
produce a given column's default value.
col_name
)
If both the column list and the VALUES
list are empty, INSERT
creates a row with
each column set to its default value:
INSERT INTO tbl_name
() VALUES();
In strict mode, an error occurs if any column doesn't have a default value. Otherwise, MySQL uses the implicit default value for any column that does not have an explicitly defined default.
You can specify an expression
expr
to provide a column value.
This might involve type conversion if the type of the
expression does not match the type of the column, and
conversion of a given value can result in different inserted
values depending on the data type. For example, inserting
the string '1999.0e-2'
into an
INT
, FLOAT
,
DECIMAL(10,6)
, or YEAR
column results in the values 1999
,
19.9921
, 19.992100
,
and 1999
being inserted, respectively.
The reason the value stored in the INT
and YEAR
columns is
1999
is that the string-to-integer
conversion looks only at as much of the initial part of the
string as may be considered a valid integer or year. For the
floating-point and fixed-point columns, the
string-to-floating-point conversion considers the entire
string a valid floating-point value.
An expression expr
can refer to
any column that was set earlier in a value list. For
example, you can do this because the value for
col2
refers to col1
,
which has previously been assigned:
INSERT INTO tbl_name
(col1,col2) VALUES(15,col1*2);
But the following is not legal, because the value for
col1
refers to col2
,
which is assigned after col1
:
INSERT INTO tbl_name
(col1,col2) VALUES(col2*2,15);
One exception involves columns that contain
AUTO_INCREMENT
values. Because the
AUTO_INCREMENT
value is generated after
other value assignments, any reference to an
AUTO_INCREMENT
column in the assignment
returns a 0
.
INSERT
statements that use
VALUES
syntax can insert multiple rows. To do
this, include multiple lists of column values, each enclosed
within parentheses and separated by commas. Example:
INSERT INTO tbl_name
(a,b,c) VALUES(1,2,3),(4,5,6),(7,8,9);
The values list for each row must be enclosed within parentheses. The following statement is illegal because the number of values in the list does not match the number of column names:
INSERT INTO tbl_name
(a,b,c) VALUES(1,2,3,4,5,6,7,8,9);
The rows-affected value for an INSERT
can be
obtained using the mysql_affected_rows()
C
API function. See Section 22.2.3.1, “mysql_affected_rows()
”.
If you use an INSERT ... VALUES
statement
with multiple value lists or INSERT ...
SELECT
, the statement returns an information string in
this format:
Records: 100 Duplicates: 0 Warnings: 0
Records
indicates the number of rows
processed by the statement. (This is not necessarily the number
of rows actually inserted because Duplicates
can be non-zero.) Duplicates
indicates the
number of rows that could not be inserted because they would
duplicate some existing unique index value.
Warnings
indicates the number of attempts to
insert column values that were problematic in some way. Warnings
can occur under any of the following conditions:
Inserting NULL
into a column that has
been declared NOT NULL
. For multiple-row
INSERT
statements or INSERT INTO
... SELECT
statements, the column is set to the
implicit default value for the column data type. This is
0
for numeric types, the empty string
(''
) for string types, and the
“zero” value for date and time types.
INSERT INTO ... SELECT
statements are
handled the same way as multiple-row inserts because the
server does not examine the result set from the
SELECT
to see whether it returns a single
row. (For a single-row INSERT
, no warning
occurs when NULL
is inserted into a
NOT NULL
column. Instead, the statement
fails with an error.)
Setting a numeric column to a value that lies outside the column's range. The value is clipped to the closest endpoint of the range.
Assigning a value such as '10.34 a'
to a
numeric column. The trailing non-numeric text is stripped
off and the remaining numeric part is inserted. If the
string value has no leading numeric part, the column is set
to 0
.
Inserting a string into a string column
(CHAR
, VARCHAR
,
TEXT
, or BLOB
) that
exceeds the column's maximum length. The value is truncated
to the column's maximum length.
Inserting a value into a date or time column that is illegal for the data type. The column is set to the appropriate zero value for the type.
If you are using the C API, the information string can be
obtained by invoking the mysql_info()
function. See Section 22.2.3.34, “mysql_info()
”.
If INSERT
inserts a row into a table that has
an AUTO_INCREMENT
column, you can find the
value used for that column by using the SQL
LAST_INSERT_ID()
function. From within the C
API, use the mysql_insert_id()
function.
However, you should note that the two functions do not always
behave identically. The behavior of INSERT
statements with respect to AUTO_INCREMENT
columns is discussed further in
Section 12.9.3, “Information Functions”, and
Section 22.2.3.36, “mysql_insert_id()
”.
The INSERT
statement supports the following
modifiers:
If you use the DELAYED
keyword, the
server puts the row or rows to be inserted into a buffer,
and the client issuing the INSERT DELAYED
statement can then continue immediately. If the table is in
use, the server holds the rows. When the table is free, the
server begins inserting rows, checking periodically to see
whether there are any new read requests for the table. If
there are, the delayed row queue is suspended until the
table becomes free again. See
Section 13.2.4.2, “INSERT DELAYED
Syntax”.
DELAYED
is ignored with INSERT
... SELECT
or INSERT ... ON DUPLICATE KEY
UPDATE
.
If you use the LOW_PRIORITY
keyword,
execution of the INSERT
is delayed until
no other clients are reading from the table. This includes
other clients that began reading while existing clients are
reading, and while the INSERT
LOW_PRIORITY
statement is waiting. It is possible,
therefore, for a client that issues an INSERT
LOW_PRIORITY
statement to wait for a very long
time (or even forever) in a read-heavy environment. (This is
in contrast to INSERT DELAYED
, which lets
the client continue at once. Note that
LOW_PRIORITY
should normally not be used
with MyISAM
tables because doing so
disables concurrent inserts. See
Section 7.3.3, “Concurrent Inserts”.
If you specify HIGH_PRIORITY
, it
overrides the effect of the
--low-priority-updates
option if the server
was started with that option. It also causes concurrent
inserts not to be used.
If you use the IGNORE
keyword, errors
that occur while executing the INSERT
statement are treated as warnings instead. For example,
without IGNORE
, a row that duplicates an
existing UNIQUE
index or PRIMARY
KEY
value in the table causes a duplicate-key
error and the statement is aborted. With
IGNORE
, the row still is not inserted,
but no error is issued. Data conversions that would trigger
errors abort the statement if IGNORE
is
not specified. With IGNORE
, invalid
values are adjusted to the closest values and inserted;
warnings are produced but the statement does not abort. You
can determine with the mysql_info()
C API
function how many rows were actually inserted into the
table.
If you specify ON DUPLICATE KEY UPDATE
,
and a row is inserted that would cause a duplicate value in
a UNIQUE
index or PRIMARY
KEY
, an UPDATE
of the old row
is performed. See Section 13.2.4.3, “INSERT ... ON DUPLICATE KEY UPDATE
Syntax”.
INSERT [LOW_PRIORITY | HIGH_PRIORITY] [IGNORE] [INTO]tbl_name
[(col_name
,...)] SELECT ... [ ON DUPLICATE KEY UPDATEcol_name
=expr
, ... ]
With INSERT ... SELECT
, you can quickly
insert many rows into a table from one or many tables. For
example:
INSERT INTO tbl_temp2 (fld_id) SELECT tbl_temp1.fld_order_id FROM tbl_temp1 WHERE tbl_temp1.fld_order_id > 100;
The following conditions hold for a INSERT ...
SELECT
statements:
Specify IGNORE
to ignore rows that
would cause duplicate-key violations.
DELAYED
is ignored with INSERT
... SELECT
.
The target table of the INSERT
statement may appear in the FROM
clause
of the SELECT
part of the query. (This
was not possible in some older versions of MySQL.) In this
case, MySQL creates a temporary table to hold the rows
from the SELECT
and then inserts those
rows into the target table.
AUTO_INCREMENT
columns work as usual.
To ensure that the binary log can be used to re-create the
original tables, MySQL does not allow concurrent inserts
for INSERT ... SELECT
statements.
Currently, you cannot insert into a table and select from the same table in a subquery.
In the values part of ON DUPLICATE KEY
UPDATE
, you can refer to columns in other tables, as
long as you do not use GROUP BY
in the
SELECT
part. One side effect is that you
must qualify non-unique column names in the values part.
INSERT DELAYED ...
The DELAYED
option for the
INSERT
statement is a MySQL extension to
standard SQL that is very useful if you have clients that
cannot or need not wait for the INSERT
to
complete. This is a common situation when you use MySQL for
logging and you also periodically run
SELECT
and UPDATE
statements that take a long time to complete.
When a client uses INSERT DELAYED
, it gets
an okay from the server at once, and the row is queued to be
inserted when the table is not in use by any other thread.
Another major benefit of using INSERT
DELAYED
is that inserts from many clients are
bundled together and written in one block. This is much faster
than performing many separate inserts.
Note that INSERT DELAYED
is slower than a
normal INSERT
if the table is not otherwise
in use. There is also the additional overhead for the server
to handle a separate thread for each table for which there are
delayed rows. This means that you should use INSERT
DELAYED
only when you are really sure that you need
it.
The queued rows are held only in memory until they are
inserted into the table. This means that if you terminate
mysqld forcibly (for example, with
kill -9
) or if mysqld
dies unexpectedly, any queued rows that have not
been written to disk are lost.
There are some constraints on the use of
DELAYED
:
INSERT DELAYED
works only with
MyISAM
, MEMORY
, and
ARCHIVE
tables. See
Section 14.1, “The MyISAM
Storage Engine”,
Section 14.4, “The MEMORY
(HEAP
) Storage Engine”, and
Section 14.8, “The ARCHIVE
Storage Engine”.
For MyISAM
tables, if there are no free
blocks in the middle of the data file, concurrent
SELECT
and INSERT
statements are supported. Under these circumstances, you
very seldom need to use INSERT DELAYED
with MyISAM
.
INSERT DELAYED
should be used only for
INSERT
statements that specify value
lists. The server ignores DELAYED
for
INSERT ... SELECT
or INSERT
... ON DUPLICATE KEY UPDATE
statements.
Because the INSERT DELAYED
statement
returns immediately, before the rows are inserted, you
cannot use LAST_INSERT_ID()
to get the
AUTO_INCREMENT
value that the statement
might generate.
DELAYED
rows are not visible to
SELECT
statements until they actually
have been inserted.
DELAYED
is ignored on slave replication
servers because it could cause the slave to have different
data than the master.
The following describes in detail what happens when you use
the DELAYED
option to
INSERT
or REPLACE
. In
this description, the “thread” is the thread that
received an INSERT DELAYED
statement and
“handler” is the thread that handles all
INSERT DELAYED
statements for a particular
table.
When a thread executes a DELAYED
statement for a table, a handler thread is created to
process all DELAYED
statements for the
table, if no such handler already exists.
The thread checks whether the handler has previously
acquired a DELAYED
lock; if not, it
tells the handler thread to do so. The
DELAYED
lock can be obtained even if
other threads have a READ
or
WRITE
lock on the table. However, the
handler waits for all ALTER TABLE
locks
or FLUSH TABLES
statements to finish,
to ensure that the table structure is up to date.
The thread executes the INSERT
statement, but instead of writing the row to the table, it
puts a copy of the final row into a queue that is managed
by the handler thread. Any syntax errors are noticed by
the thread and reported to the client program.
The client cannot obtain from the server the number of
duplicate rows or the AUTO_INCREMENT
value for the resulting row, because the
INSERT
returns before the insert
operation has been completed. (If you use the C API, the
mysql_info()
function does not return
anything meaningful, for the same reason.)
The binary log is updated by the handler thread when the row is inserted into the table. In case of multiple-row inserts, the binary log is updated when the first row is inserted.
Each time that delayed_insert_limit
rows are written, the handler checks whether any
SELECT
statements are still pending. If
so, it allows these to execute before continuing.
When the handler has no more rows in its queue, the table
is unlocked. If no new INSERT DELAYED
statements are received within
delayed_insert_timeout
seconds, the
handler terminates.
If more than delayed_queue_size
rows
are pending in a specific handler queue, the thread
requesting INSERT DELAYED
waits until
there is room in the queue. This is done to ensure that
mysqld does not use all memory for the
delayed memory queue.
The handler thread shows up in the MySQL process list with
delayed_insert
in the
Command
column. It is killed if you
execute a FLUSH TABLES
statement or
kill it with KILL
. However,
before exiting, it first stores all queued rows into the
table. During this time it does not accept any new
thread_id
INSERT
statements from other threads.
If you execute an INSERT DELAYED
statement after this, a new handler thread is created.
Note that this means that INSERT
DELAYED
statements have higher priority than
normal INSERT
statements if there is an
INSERT DELAYED
handler running. Other
update statements have to wait until the INSERT
DELAYED
queue is empty, someone terminates the
handler thread (with KILL
), or
someone executes a thread_id
FLUSH TABLES
.
The following status variables provide information about
INSERT DELAYED
statements:
Status Variable | Meaning |
Delayed_insert_threads | Number of handler threads |
Delayed_writes | Number of rows written with INSERT DELAYED |
Not_flushed_delayed_rows | Number of rows waiting to be written |
You can view these variables by issuing a SHOW
STATUS
statement or by executing a
mysqladmin extended-status command.
If you specify ON DUPLICATE KEY UPDATE
, and
a row is inserted that would cause a duplicate value in a
UNIQUE
index or PRIMARY
KEY
, an UPDATE
of the old row is
performed. For example, if column a
is
declared as UNIQUE
and contains the value
1
, the following two statements have
identical effect:
INSERT INTO table (a,b,c) VALUES (1,2,3) ON DUPLICATE KEY UPDATE c=c+1; UPDATE table SET c=c+1 WHERE a=1;
The rows-affected value is 1 if the row is inserted as a new record and 2 if an existing record is updated.
If column b
is also unique, the
INSERT
is equivalent to this
UPDATE
statement instead:
UPDATE table SET c=c+1 WHERE a=1 OR b=2 LIMIT 1;
If a=1 OR b=2
matches several rows, only
one row is updated. In general, you
should try to avoid using an ON DUPLICATE
KEY
clause on tables with multiple unique indexes.
You can use the
VALUES(
function in the col_name
)UPDATE
clause to refer to
column values from the INSERT
portion of
the INSERT ... UPDATE
statement. In other
words,
VALUES(
in the col_name
)UPDATE
clause refers to the value of
col_name
that would be inserted,
had no duplicate-key conflict occurred. This function is
especially useful in multiple-row inserts. The
VALUES()
function is meaningful only in
INSERT ... UPDATE
statements and returns
NULL
otherwise. Example:
INSERT INTO table (a,b,c) VALUES (1,2,3),(4,5,6) ON DUPLICATE KEY UPDATE c=VALUES(a)+VALUES(b);
That statement is identical to the following two statements:
INSERT INTO table (a,b,c) VALUES (1,2,3) ON DUPLICATE KEY UPDATE c=3; INSERT INTO table (a,b,c) VALUES (4,5,6) ON DUPLICATE KEY UPDATE c=9;
The DELAYED
option is ignored when you use
ON DUPLICATE KEY UPDATE
.
LOAD DATA [LOW_PRIORITY | CONCURRENT] [LOCAL] INFILE 'file_name
' [REPLACE | IGNORE] INTO TABLEtbl_name
[FIELDS [TERMINATED BY 'string
'] [[OPTIONALLY] ENCLOSED BY 'char
'] [ESCAPED BY 'char
'] ] [LINES [STARTING BY 'string
'] [TERMINATED BY 'string
'] ] [IGNOREnumber
LINES] [(col_name_or_user_var
,...)] [SETcol_name
=expr
,...)]
The LOAD DATA INFILE
statement reads rows
from a text file into a table at a very high speed. The filename
must be given as a literal string.
LOAD DATA INFILE
is the complement of
SELECT ... INTO OUTFILE
. (See
Section 13.2.7, “SELECT
Syntax”.) To write data from a table to a file,
use SELECT ... INTO OUTFILE
. To read the file
back into a table, use LOAD DATA INFILE
. The
syntax of the FIELDS
and
LINES
clauses is the same for both
statements. Both clauses are optional, but
FIELDS
must precede LINES
if both are specified.
For more information about the efficiency of
INSERT
versus LOAD DATA
INFILE
and speeding up LOAD DATA
INFILE
, see Section 7.2.16, “Speed of INSERT
Statements”.
The character set indicated by the
character_set_database
system variable is
used to interpret the information in the file. SET
NAMES
and the setting of
character_set_client
do not affect
interpretation of input.
Note that it is currently not possible to load data files that
use the ucs2
character set.
As of MySQL 5.0.19, the
character_set_filesystem
system variable
controls the interpretation of the filename.
You can also load data files by using the
mysqlimport utility; it operates by sending a
LOAD DATA INFILE
statement to the server. The
--local
option causes
mysqlimport to read data files from the
client host. You can specify the --compress
option to get better performance over slow networks if the
client and server support the compressed protocol. See
Section 8.14, “mysqlimport — A Data Import Program”.
If you use LOW_PRIORITY
, execution of the
LOAD DATA
statement is delayed until no other
clients are reading from the table.
If you specify CONCURRENT
with a
MyISAM
table that satisfies the condition for
concurrent inserts (that is, it contains no free blocks in the
middle), other threads can retrieve data from the table while
LOAD DATA
is executing. Using this option
affects the performance of LOAD DATA
a bit,
even if no other thread is using the table at the same time.
The LOCAL
keyword, if specified, is
interpreted with respect to the client end of the connection:
If LOCAL
is specified, the file is read
by the client program on the client host and sent to the
server. The file can be given as a full pathname to specify
its exact location. If given as a relative pathname, the
name is interpreted relative to the directory in which the
client program was started.
If LOCAL
is not specified, the file must
be located on the server host and is read directly by the
server. The server uses the following rules to locate the
file:
If the filename is an absolute pathname, the server uses it as given.
If the filename is a relative pathname with one or more leading components, the server searches for the file relative to the server's data directory.
If a filename with no leading components is given, the server looks for the file in the database directory of the default database.
Note that, in the non-LOCAL
case, these rules
mean that a file named as ./myfile.txt
is
read from the server's data directory, whereas the file named as
myfile.txt
is read from the database
directory of the default database. For example, if
db1
is the default database, the following
LOAD DATA
statement reads the file
data.txt
from the database directory for
db1
, even though the statement explicitly
loads the file into a table in the db2
database:
LOAD DATA INFILE 'data.txt' INTO TABLE db2.my_table;
Windows pathnames are specified using forward slashes rather than backslashes. If you do use backslashes, you must double them.
For security reasons, when reading text files located on the
server, the files must either reside in the database directory
or be readable by all. Also, to use LOAD DATA
INFILE
on server files, you must have the
FILE
privilege. See
Section 5.8.3, “Privileges Provided by MySQL”.
Using LOCAL
is a bit slower than letting the
server access the files directly, because the contents of the
file must be sent over the connection by the client to the
server. On the other hand, you do not need the
FILE
privilege to load local files.
LOCAL
works only if your server and your
client both have been enabled to allow it. For example, if
mysqld was started with
--local-infile=0
, LOCAL
does
not work. See Section 5.7.4, “Security Issues with LOAD DATA LOCAL
”.
On Unix, if you need LOAD DATA
to read from a
pipe, you can use the following technique (here we load the
listing of the /
directory into a table):
mkfifo /mysql/db/x/x chmod 666 /mysql/db/x/x find / -ls > /mysql/db/x/x mysql -e "LOAD DATA INFILE 'x' INTO TABLE x" x
The REPLACE
and IGNORE
keywords control handling of input rows that duplicate existing
rows on unique key values:
If you specify REPLACE
, input rows
replace existing rows. In other words, rows that have the
same value for a primary key or unique index as an existing
row. See Section 13.2.6, “REPLACE
Syntax”.
If you specify IGNORE
, input rows that
duplicate an existing row on a unique key value are skipped.
If you do not specify either option, the behavior depends on
whether the LOCAL
keyword is specified.
Without LOCAL
, an error occurs when a
duplicate key value is found, and the rest of the text file
is ignored. With LOCAL
, the default
behavior is the same as if IGNORE
is
specified; this is because the server has no way to stop
transmission of the file in the middle of the operation.
If you want to ignore foreign key constraints during the load
operation, you can issue a SET
FOREIGN_KEY_CHECKS=0
statement before executing
LOAD DATA
.
If you use LOAD DATA INFILE
on an empty
MyISAM
table, all non-unique indexes are
created in a separate batch (as for REPAIR
TABLE
). Normally, this makes LOAD DATA
INFILE
much faster when you have many indexes. In some
extreme cases, you can create the indexes even faster by turning
them off with ALTER TABLE ... DISABLE KEYS
before loading the file into the table and using ALTER
TABLE ... ENABLE KEYS
to re-create the indexes after
loading the file. See Section 7.2.16, “Speed of INSERT
Statements”.
For both the LOAD DATA INFILE
and
SELECT ... INTO OUTFILE
statements, the
syntax of the FIELDS
and
LINES
clauses is the same. Both clauses are
optional, but FIELDS
must precede
LINES
if both are specified.
If you specify a FIELDS
clause, each of its
subclauses (TERMINATED BY
,
[OPTIONALLY] ENCLOSED BY
, and
ESCAPED BY
) is also optional, except that you
must specify at least one of them.
If you specify no FIELDS
clause, the defaults
are the same as if you had written this:
FIELDS TERMINATED BY '\t' ENCLOSED BY '' ESCAPED BY '\\'
If you specify no LINES
clause, the defaults
are the same as if you had written this:
LINES TERMINATED BY '\n' STARTING BY ''
In other words, the defaults cause LOAD DATA
INFILE
to act as follows when reading input:
Look for line boundaries at newlines.
Do not skip over any line prefix.
Break lines into fields at tabs.
Do not expect fields to be enclosed within any quoting characters.
Interpret occurrences of tab, newline, or
‘\
’ preceded by
‘\
’ as literal characters
that are part of field values.
Conversely, the defaults cause SELECT ... INTO
OUTFILE
to act as follows when writing output:
Write tabs between fields.
Do not enclose fields within any quoting characters.
Use ‘\
’ to escape instances
of tab, newline, or ‘\
’ that
occur within field values.
Write newlines at the ends of lines.
Backslash is the MySQL escape character within strings, so to
write FIELDS ESCAPED BY '\\'
, you must
specify two backslashes for the value to be interpreted as a
single backslash.
Note: If you have generated the
text file on a Windows system, you might have to use
LINES TERMINATED BY '\r\n'
to read the file
properly, because Windows programs typically use two characters
as a line terminator. Some programs, such as
WordPad, might use \r
as a
line terminator when writing files. To read such files, use
LINES TERMINATED BY '\r'
.
If all the lines you want to read in have a common prefix that
you want to ignore, you can use LINES STARTING BY
'
to skip
over the prefix, and anything before it. If
a line does not include the prefix, the entire line is skipped.
Suppose that you issue the following statement:
prefix_string
'
LOAD DATA INFILE '/tmp/test.txt' INTO TABLE test FIELDS TERMINATED BY ',' LINES STARTING BY 'xxx';
If the data file looks like this:
xxx"abc",1 something xxx"def",2 "ghi",3
The resulting rows will be ("abc",1)
and
("def",2)
. The third row in the file is
skipped because it does not contain the prefix.
The IGNORE
option can be used to ignore lines at the start
of the file. For example, you can use number
LINESIGNORE 1
LINES
to skip over an initial header line containing
column names:
LOAD DATA INFILE '/tmp/test.txt' INTO TABLE test IGNORE 1 LINES;
When you use SELECT ... INTO OUTFILE
in
tandem with LOAD DATA INFILE
to write data
from a database into a file and then read the file back into the
database later, the field- and line-handling options for both
statements must match. Otherwise, LOAD DATA
INFILE
will not interpret the contents of the file
properly. Suppose that you use SELECT ... INTO
OUTFILE
to write a file with fields delimited by
commas:
SELECT * INTO OUTFILE 'data.txt' FIELDS TERMINATED BY ',' FROM table2;
To read the comma-delimited file back in, the correct statement would be:
LOAD DATA INFILE 'data.txt' INTO TABLE table2 FIELDS TERMINATED BY ',';
If instead you tried to read in the file with the statement
shown following, it wouldn't work because it instructs
LOAD DATA INFILE
to look for tabs between
fields:
LOAD DATA INFILE 'data.txt' INTO TABLE table2 FIELDS TERMINATED BY '\t';
The likely result is that each input line would be interpreted as a single field.
LOAD DATA INFILE
can be used to read files
obtained from external sources. For example, many programs can
export data in comma-separate values (CSV) format, such that
lines have fields separated by commas and enclosed within double
quotes. If lines in such a file are terminated by newlines, the
statement shown here illustrates the field- and line-handling
options you would use to load the file:
LOAD DATA INFILE 'data.txt' INTO TABLE tbl_name
FIELDS TERMINATED BY ',' ENCLOSED BY '"'
LINES TERMINATED BY '\n';
Any of the field- or line-handling options can specify an empty
string (''
). If not empty, the
FIELDS [OPTIONALLY] ENCLOSED BY
and
FIELDS ESCAPED BY
values must be a single
character. The FIELDS TERMINATED BY
,
LINES STARTING BY
, and LINES
TERMINATED BY
values can be more than one character.
For example, to write lines that are terminated by carriage
return/linefeed pairs, or to read a file containing such lines,
specify a LINES TERMINATED BY '\r\n'
clause.
To read a file containing jokes that are separated by lines
consisting of %%
, you can do this
CREATE TABLE jokes (a INT NOT NULL AUTO_INCREMENT PRIMARY KEY, joke TEXT NOT NULL); LOAD DATA INFILE '/tmp/jokes.txt' INTO TABLE jokes FIELDS TERMINATED BY '' LINES TERMINATED BY '\n%%\n' (joke);
FIELDS [OPTIONALLY] ENCLOSED BY
controls
quoting of fields. For output (SELECT ... INTO
OUTFILE
), if you omit the word
OPTIONALLY
, all fields are enclosed by the
ENCLOSED BY
character. An example of such
output (using a comma as the field delimiter) is shown here:
"1","a string","100.20" "2","a string containing a , comma","102.20" "3","a string containing a \" quote","102.20" "4","a string containing a \", quote and comma","102.20"
If you specify OPTIONALLY
, the
ENCLOSED BY
character is used only to enclose
values from columns that have a string data type (such as
CHAR
, BINARY
,
TEXT
, or ENUM
):
1,"a string",100.20 2,"a string containing a , comma",102.20 3,"a string containing a \" quote",102.20 4,"a string containing a \", quote and comma",102.20
Note that occurrences of the ENCLOSED BY
character within a field value are escaped by prefixing them
with the ESCAPED BY
character. Also note that
if you specify an empty ESCAPED BY
value, it
is possible to inadvertently generate output that cannot be read
properly by LOAD DATA INFILE
. For example,
the preceding output just shown would appear as follows if the
escape character is empty. Observe that the second field in the
fourth line contains a comma following the quote, which
(erroneously) appears to terminate the field:
1,"a string",100.20 2,"a string containing a , comma",102.20 3,"a string containing a " quote",102.20 4,"a string containing a ", quote and comma",102.20
For input, the ENCLOSED BY
character, if
present, is stripped from the ends of field values. (This is
true regardless of whether OPTIONALLY
is
specified; OPTIONALLY
has no effect on input
interpretation.) Occurrences of the ENCLOSED
BY
character preceded by the ESCAPED
BY
character are interpreted as part of the current
field value.
If the field begins with the ENCLOSED BY
character, instances of that character are recognized as
terminating a field value only if followed by the field or line
TERMINATED BY
sequence. To avoid ambiguity,
occurrences of the ENCLOSED BY
character
within a field value can be doubled and are interpreted as a
single instance of the character. For example, if
ENCLOSED BY '"'
is specified, quotes are
handled as shown here:
"The ""BIG"" boss" -> The "BIG" boss The "BIG" boss -> The "BIG" boss The ""BIG"" boss -> The ""BIG"" boss
FIELDS ESCAPED BY
controls how to write or
read special characters. If the FIELDS ESCAPED
BY
character is not empty, it is used to prefix the
following characters on output:
The FIELDS ESCAPED BY
character
The FIELDS [OPTIONALLY] ENCLOSED BY
character
The first character of the FIELDS TERMINATED
BY
and LINES TERMINATED BY
values
ASCII 0
(what is actually written
following the escape character is ASCII
‘0
’, not a zero-valued byte)
If the FIELDS ESCAPED BY
character is empty,
no characters are escaped and NULL
is output
as NULL
, not \N
. It is
probably not a good idea to specify an empty escape character,
particularly if field values in your data contain any of the
characters in the list just given.
For input, if the FIELDS ESCAPED BY
character
is not empty, occurrences of that character are stripped and the
following character is taken literally as part of a field value.
The exceptions are an escaped ‘0
’
or ‘N
’ (for example,
\0
or \N
if the escape
character is ‘\
’). These
sequences are interpreted as ASCII NUL (a zero-valued byte) and
NULL
. The rules for NULL
handling are described later in this section.
For more information about
‘\
’-escape syntax, see
Section 9.1, “Literal Values”.
In certain cases, field- and line-handling options interact:
If LINES TERMINATED BY
is an empty string
and FIELDS TERMINATED BY
is non-empty,
lines are also terminated with FIELDS TERMINATED
BY
.
If the FIELDS TERMINATED BY
and
FIELDS ENCLOSED BY
values are both empty
(''
), a fixed-row (non-delimited) format
is used. With fixed-row format, no delimiters are used
between fields (but you can still have a line terminator).
Instead, column values are read and written using a field
width wide enough to hold all values in the field. For
TINYINT
, SMALLINT
,
MEDIUMINT
, INT
, and
BIGINT
, the field widths are 4, 6, 8, 11,
and 20, respectively, no matter what the declared display
width is.
LINES TERMINATED BY
is still used to
separate lines. If a line does not contain all fields, the
rest of the columns are set to their default values. If you
do not have a line terminator, you should set this to
''
. In this case, the text file must
contain all fields for each row.
Fixed-row format also affects handling of
NULL
values, as described later. Note
that fixed-size format does not work if you are using a
multi-byte character set.
Note: Before MySQL 5.0.6,
fixed-row format used the display width of the column. For
example, INT(4)
was read or written using
a field with a width of 4. However, if the column contained
wider values, they were dumped to their full width, leading
to the possibility of a “ragged” field holding
values of different widths. Using a field wide enough to
hold all values in the field prevents this problem. However,
data files written before this change was made might not be
reloaded correctly with LOAD DATA INFILE
for MySQL 5.0.6 and up. This change also affects data files
read by mysqlimport and written by
mysqldump --tab, which use LOAD
DATA INFILE
and SELECT ... INTO
OUTFILE
.
Handling of NULL
values varies according to
the FIELDS
and LINES
options in use:
For the default FIELDS
and
LINES
values, NULL
is
written as a field value of \N
for
output, and a field value of \N
is read
as NULL
for input (assuming that the
ESCAPED BY
character is
‘\
’).
If FIELDS ENCLOSED BY
is not empty, a
field containing the literal word NULL
as
its value is read as a NULL
value. This
differs from the word NULL
enclosed
within FIELDS ENCLOSED BY
characters,
which is read as the string 'NULL'
.
If FIELDS ESCAPED BY
is empty,
NULL
is written as the word
NULL
.
With fixed-row format (which is used when FIELDS
TERMINATED BY
and FIELDS ENCLOSED
BY
are both empty), NULL
is
written as an empty string. Note that this causes both
NULL
values and empty strings in the
table to be indistinguishable when written to the file
because both are written as empty strings. If you need to be
able to tell the two apart when reading the file back in,
you should not use fixed-row format.
Some cases are not supported by LOAD DATA
INFILE
:
Fixed-size rows (FIELDS TERMINATED BY
and
FIELDS ENCLOSED BY
both empty) and
BLOB
or TEXT
columns.
If you specify one separator that is the same as or a prefix
of another, LOAD DATA INFILE
cannot
interpret the input properly. For example, the following
FIELDS
clause would cause problems:
FIELDS TERMINATED BY '"' ENCLOSED BY '"'
If FIELDS ESCAPED BY
is empty, a field
value that contains an occurrence of FIELDS
ENCLOSED BY
or LINES TERMINATED
BY
followed by the FIELDS TERMINATED
BY
value causes LOAD DATA
INFILE
to stop reading a field or line too early.
This happens because LOAD DATA INFILE
cannot properly determine where the field or line value
ends.
The following example loads all columns of the
persondata
table:
LOAD DATA INFILE 'persondata.txt' INTO TABLE persondata;
By default, when no column list is provided at the end of the
LOAD DATA INFILE
statement, input lines are
expected to contain a field for each table column. If you want
to load only some of a table's columns, specify a column list:
LOAD DATA INFILE 'persondata.txt' INTO TABLE persondata (col1,col2,...);
You must also specify a column list if the order of the fields in the input file differs from the order of the columns in the table. Otherwise, MySQL cannot tell how to match input fields with table columns.
Before MySQL 5.0.3, the column list must contain only names of
columns in the table being loaded, and the
SET
clause is not supported. As of MySQL
5.0.3, the column list can contain either column names or user
variables. With user variables, the SET
clause enables you to perform transformations on their values
before assigning the result to columns.
User variables in the SET
clause can be used
in several ways. The following example uses the first input
column directly for the value of t1.column1
,
and assigns the second input column to a user variable that is
subjected to a division operation before being used for the
value of t1.column2
:
LOAD DATA INFILE 'file.txt' INTO TABLE t1 (column1, @var1) SET column2 = @var1/100;
The SET
clause can be used to supply values
not derived from the input file. The following statement sets
column3
to the current date and time:
LOAD DATA INFILE 'file.txt' INTO TABLE t1 (column1, column2) SET column3 = CURRENT_TIMESTAMP;
You can also discard an input value by assigning it to a user variable and not assigning the variable to a table column:
LOAD DATA INFILE 'file.txt' INTO TABLE t1 (column1, @dummy, column2, @dummy, column3);
Use of the column/variable list and SET
clause is subject to the following restrictions:
Assignments in the SET
clause should have
only column names on the left hand side of assignment
operators.
You can use subqueries in the right hand side of
SET
assignments. A subquery that returns
a value to be assigned to a column may be a scalar subquery
only. Also, you cannot use a subquery to select from the
table that is being loaded.
Lines ignored by an IGNORE
clause are not
processed for the column/variable list or
SET
clause.
User variables cannot be used when loading data with fixed-row format because user variables do not have a display width.
When processing an input line, LOAD DATA
splits it into fields and uses the values according to the
column/variable list and the SET
clause, if
they are present. Then the resulting row is inserted into the
table. If there are BEFORE INSERT
or
AFTER INSERT
triggers for the table, they are
activated before or after inserting the row, respectively.
If an input line has too many fields, the extra fields are ignored and the number of warnings is incremented.
If an input line has too few fields, the table columns for which input fields are missing are set to their default values. Default value assignment is described in Section 11.1.4, “Data Type Default Values”.
An empty field value is interpreted differently than if the field value is missing:
For string types, the column is set to the empty string.
For numeric types, the column is set to
0
.
For date and time types, the column is set to the appropriate “zero” value for the type. See Section 11.3, “Date and Time Types”.
These are the same values that result if you assign an empty
string explicitly to a string, numeric, or date or time type
explicitly in an INSERT
or
UPDATE
statement.
TIMESTAMP
columns are set to the current date
and time only if there is a NULL
value for
the column (that is, \N
), or if the
TIMESTAMP
column's default value is the
current timestamp and it is omitted from the field list when a
field list is specified.
LOAD DATA INFILE
regards all input as
strings, so you cannot use numeric values for
ENUM
or SET
columns the
way you can with INSERT
statements. All
ENUM
and SET
values must
be specified as strings.
BIT
values cannot be loaded using binary
notation (for example, b'011010'
). To work
around this, specify the values as regular integers and use the
SET
clause to convert them so that MySQL
performs a numeric type conversion and loads them into the
BIT
column properly:
shell>cat /tmp/bit_test.txt
2 127 shell>mysql test
mysql>LOAD DATA INFILE '/tmp/bit_test.txt'
->INTO TABLE bit_test (@var1) SET b= CAST(@var1 AS SIGNED);
Query OK, 2 rows affected (0.00 sec) Records: 2 Deleted: 0 Skipped: 0 Warnings: 0 mysql>SELECT BIN(b+0) FROM bit_test;
+----------+ | bin(b+0) | +----------+ | 10 | | 1111111 | +----------+ 2 rows in set (0.00 sec)
When the LOAD DATA INFILE
statement finishes,
it returns an information string in the following format:
Records: 1 Deleted: 0 Skipped: 0 Warnings: 0
If you are using the C API, you can get information about the
statement by calling the mysql_info()
function. See Section 22.2.3.34, “mysql_info()
”.
Warnings occur under the same circumstances as when values are
inserted via the INSERT
statement (see
Section 13.2.4, “INSERT
Syntax”), except that LOAD DATA
INFILE
also generates warnings when there are too few
or too many fields in the input row. The warnings are not stored
anywhere; the number of warnings can be used only as an
indication of whether everything went well.
You can use SHOW WARNINGS
to get a list of
the first max_error_count
warnings as
information about what went wrong. See
Section 13.5.4.25, “SHOW WARNINGS
Syntax”.
REPLACE [LOW_PRIORITY | DELAYED] [INTO]tbl_name
[(col_name
,...)] VALUES ({expr
| DEFAULT},...),(...),...
Or:
REPLACE [LOW_PRIORITY | DELAYED] [INTO]tbl_name
SETcol_name
={expr
| DEFAULT}, ...
Or:
REPLACE [LOW_PRIORITY | DELAYED] [INTO]tbl_name
[(col_name
,...)] SELECT ...
REPLACE
works exactly like
INSERT
, except that if an old row in the
table has the same value as a new row for a PRIMARY
KEY
or a UNIQUE
index, the old row
is deleted before the new row is inserted. See
Section 13.2.4, “INSERT
Syntax”.
REPLACE
is a MySQL extension to the SQL
standard. It either inserts, or deletes and
inserts. For another MySQL extension to standard SQL —
that either inserts or updates — see
Section 13.2.4.3, “INSERT ... ON DUPLICATE KEY UPDATE
Syntax”.
Note that unless the table has a PRIMARY KEY
or UNIQUE
index, using a
REPLACE
statement makes no sense. It becomes
equivalent to INSERT
, because there is no
index to be used to determine whether a new row duplicates
another.
Values for all columns are taken from the values specified in
the REPLACE
statement. Any missing columns
are set to their default values, just as happens for
INSERT
. You cannot refer to values from the
current row and use them in the new row. If you use an
assignment such as SET
, the reference
to the column name on the right hand side is treated as
col_name
=
col_name
+ 1DEFAULT(
,
so the assignment is equivalent to col_name
)SET
.
col_name
=
DEFAULT(col_name
) + 1
To use REPLACE
, you must have both the
INSERT
and DELETE
privileges for the table.
The REPLACE
statement returns a count to
indicate the number of rows affected. This is the sum of the
rows deleted and inserted. If the count is 1 for a single-row
REPLACE
, a row was inserted and no rows were
deleted. If the count is greater than 1, one or more old rows
were deleted before the new row was inserted. It is possible for
a single row to replace more than one old row if the table
contains multiple unique indexes and the new row duplicates
values for different old rows in different unique indexes.
The affected-rows count makes it easy to determine whether
REPLACE
only added a row or whether it also
replaced any rows: Check whether the count is 1 (added) or
greater (replaced).
If you are using the C API, the affected-rows count can be
obtained using the mysql_affected_rows()
function.
Currently, you cannot replace into a table and select from the same table in a subquery.
MySQL uses the following algorithm for
REPLACE
(and LOAD DATA ...
REPLACE
):
Try to insert the new row into the table
While the insertion fails because a duplicate-key error occurs for a primary key or unique index:
Delete from the table the conflicting row that has the duplicate key value
Try again to insert the new row into the table
SELECT [ALL | DISTINCT | DISTINCTROW ] [HIGH_PRIORITY] [STRAIGHT_JOIN] [SQL_SMALL_RESULT] [SQL_BIG_RESULT] [SQL_BUFFER_RESULT] [SQL_CACHE | SQL_NO_CACHE] [SQL_CALC_FOUND_ROWS]select_expr
, ... [FROMtable_references
[WHEREwhere_condition
] [GROUP BY {col_name
|expr
|position
} [ASC | DESC], ... [WITH ROLLUP]] [HAVINGwhere_condition
] [ORDER BY {col_name
|expr
|position
} [ASC | DESC], ...] [LIMIT {[offset
,]row_count
|row_count
OFFSEToffset
}] [PROCEDUREprocedure_name
(argument_list
)] [INTO OUTFILE 'file_name
'export_options
| INTO DUMPFILE 'file_name
' | INTO @var_name
[, @var_name
]] [FOR UPDATE | LOCK IN SHARE MODE]]
SELECT
is used to retrieve rows selected from
one or more tables, and can include UNION
statements and subqueries. See Section 13.2.7.2, “UNION
Syntax”, and
Section 13.2.8, “Subquery Syntax”.
The most commonly used clauses of SELECT
statements are these:
Each select_expr
indicates a
column that you want to retrieve. There must be at least one
select_expr
.
table_references
indicates the
table or tables from which to retrieve rows. Its syntax is
described in Section 13.2.7.1, “JOIN
Syntax”.
The WHERE
clause, if given, indicates the
condition or conditions that rows must satisfy to be
selected. where_condition
is an
expression that evaluates to true for each row to be
selected. The statement selects all rows if there is no
WHERE
clause.
In the WHERE
clause, you can use any of
the functions and operators that MySQL supports, except for
aggregate (summary) functions. See
Chapter 12, Functions and Operators.
SELECT
can also be used to retrieve rows
computed without reference to any table.
For example:
mysql> SELECT 1 + 1;
-> 2
You are allowed to specify DUAL
as a dummy
table name in situations where no tables are referenced:
mysql> SELECT 1 + 1 FROM DUAL;
-> 2
DUAL
is purely for compatibility with some
other database servers that require a FROM
clause. MySQL does not require the clause if no tables are
referenced.
In general, clauses used must be given in exactly the order
shown in the syntax description. For example, a
HAVING
clause must come after any
GROUP BY
clause and before any ORDER
BY
clause. The exception is that the
INTO
clause can appear either as shown in the
syntax description or immediately preceding the
FROM
clause.
A select_expr
can be given an
alias using AS
. The alias
is used as the expression's column name and can be used in
alias_name
GROUP BY
, ORDER BY
, or
HAVING
clauses. For example:
SELECT CONCAT(last_name,', ',first_name) AS full_name FROM mytable ORDER BY full_name;
The AS
keyword is optional when aliasing
a select_expr
. The preceding
example could have been written like this:
SELECT CONCAT(last_name,', ',first_name) full_name FROM mytable ORDER BY full_name;
However, because the AS
is optional, a
subtle problem can occur if you forget the comma between two
select_expr
expressions: MySQL
interprets the second as an alias name. For example, in the
following statement, columnb
is treated
as an alias name:
SELECT columna columnb FROM mytable;
For this reason, it is good practice to be in the habit of
using AS
explicitly when specifying
column aliases.
It is not allowable to use a column alias in a
WHERE
clause, because the column value
might not yet be determined when the
WHERE
clause is executed. See
Section A.5.4, “Problems with Column Aliases”.
The FROM
clause
indicates the table or tables from which to retrieve rows.
If you name more than one table, you are performing a join.
For information on join syntax, see Section 13.2.7.1, “table_references
JOIN
Syntax”.
For each table specified, you can optionally specify an
alias.
tbl_name
[[AS]alias
] [{USE|IGNORE|FORCE} INDEX (key_list
)]
The use of USE INDEX
, IGNORE
INDEX
, FORCE INDEX
to give the
optimizer hints about how to choose indexes is described in
Section 13.2.7.1, “JOIN
Syntax”.
You can use SET
max_seeks_for_key=
as an alternative way to force MySQL to prefer key scans
instead of table scans. See
Section 5.2.2, “Server System Variables”.
value
You can refer to a table within the default database as
tbl_name
, or as
db_name
.tbl_name
to specify a database explicitly. You can refer to a column
as col_name
,
tbl_name
.col_name
,
or
db_name
.tbl_name
.col_name
.
You need not specify a tbl_name
or
db_name
.tbl_name
prefix for a column reference unless the reference would be
ambiguous. See Section 9.2.1, “Identifier Qualifiers”, for
examples of ambiguity that require the more explicit column
reference forms.
A table reference can be aliased using
or
tbl_name
AS
alias_name
tbl_name alias_name
:
SELECT t1.name, t2.salary FROM employee AS t1, info AS t2 WHERE t1.name = t2.name; SELECT t1.name, t2.salary FROM employee t1, info t2 WHERE t1.name = t2.name;
Columns selected for output can be referred to in
ORDER BY
and GROUP BY
clauses using column names, column aliases, or column
positions. Column positions are integers and begin with 1:
SELECT college, region, seed FROM tournament ORDER BY region, seed; SELECT college, region AS r, seed AS s FROM tournament ORDER BY r, s; SELECT college, region, seed FROM tournament ORDER BY 2, 3;
To sort in reverse order, add the DESC
(descending) keyword to the name of the column in the
ORDER BY
clause that you are sorting by.
The default is ascending order; this can be specified
explicitly using the ASC
keyword.
Use of column positions is deprecated because the syntax has been removed from the SQL standard.
If you use GROUP BY
, output rows are
sorted according to the GROUP BY
columns
as if you had an ORDER BY
for the same
columns. To avoid the overhead of sorting that
GROUP BY
produces, add ORDER BY
NULL
:
SELECT a, COUNT(b) FROM test_table GROUP BY a ORDER BY NULL;
MySQL extends the GROUP BY
clause so that
you can also specify ASC
and
DESC
after columns named in the clause:
SELECT a, COUNT(b) FROM test_table GROUP BY a DESC;
MySQL extends the use of GROUP BY
to
allow selecting fields that are not mentioned in the
GROUP BY
clause. If you are not getting
the results that you expect from your query, please read the
description of GROUP BY
found in
Section 12.10, “Functions and Modifiers for Use with GROUP BY
Clauses”.
GROUP BY
allows a WITH
ROLLUP
modifier. See
Section 12.10.2, “GROUP BY
Modifiers”.
The HAVING
clause is applied nearly last,
just before items are sent to the client, with no
optimization. (LIMIT
is applied after
HAVING
.)
A HAVING
clause can refer to any column
or alias named in a select_expr
in the SELECT
list or in outer
subqueries, and to aggregate functions. However, the SQL
standard requires that HAVING
must
reference only columns in the GROUP BY
clause or columns used in aggregate functions. To
accommodate both standard SQL and the MySQL-specific
behavior of being able to refer columns in the
SELECT
list, MySQL 5.0.2 and up allows
HAVING
to refer to columns in the
SELECT
list, columns in the
GROUP BY
clause, columns in outer
subqueries, and to aggregate functions.
For example, the following statement works in MySQL 5.0.2 but produces an error for earlier versions:
mysql> SELECT COUNT(*) FROM t GROUP BY col1 HAVING col1 = 2;
If the HAVING
clause refers to a column
that is ambiguous, a warning occurs. In the following
statement, col2
is ambiguous because it
is used as both an alias and a column name:
SELECT COUNT(col1) AS col2 FROM t GROUP BY col2 HAVING col2 = 2;
Preference is given to standard SQL behavior, so if a
HAVING
column name is used both in
GROUP BY
and as an aliased column in the
output column list, preference is given to the column in the
GROUP BY
column.
Do not use HAVING
for items that should
be in the WHERE
clause. For example, do
not write the following:
SELECTcol_name
FROMtbl_name
HAVINGcol_name
> 0;
Write this instead:
SELECTcol_name
FROMtbl_name
WHEREcol_name
> 0;
The HAVING
clause can refer to aggregate
functions, which the WHERE
clause cannot:
SELECT user, MAX(salary) FROM users GROUP BY user HAVING MAX(salary) > 10;
(This did not work in some older versions of MySQL.)
MySQL allows duplicate column names. That is, there can be
more than one select_expr
with
the same name. This is an extension to standard SQL. Because
MySQL also allows GROUP BY
and
HAVING
to refer to
select_expr
values, this can
result in an ambiguity:
SELECT 12 AS a, a FROM t GROUP BY a;
In that statement, both columns have the name
a
. To ensure that the correct column is
used for grouping, use different names for each
select_expr
.
When MySQL resolves an unqualified column or alias reference
in an ORDER BY
, GROUP
BY
, or HAVING
clause, it first
searches for the name in the
select_expr
values. If the name
is not found, it looks in the columns of the tables named in
the FROM
clause.
The LIMIT
clause can be used to constrain
the number of rows returned by the SELECT
statement. LIMIT
takes one or two numeric
arguments, which must both be non-negative integer constants
(except when using prepared statements).
With two arguments, the first argument specifies the offset of the first row to return, and the second specifies the maximum number of rows to return. The offset of the initial row is 0 (not 1):
SELECT * FROM tbl LIMIT 5,10; # Retrieve rows 6-15
To retrieve all rows from a certain offset up to the end of the result set, you can use some large number for the second parameter. This statement retrieves all rows from the 96th row to the last:
SELECT * FROM tbl LIMIT 95,18446744073709551615;
With one argument, the value specifies the number of rows to return from the beginning of the result set:
SELECT * FROM tbl LIMIT 5; # Retrieve first 5 rows
In other words, LIMIT
is equivalent
to row_count
LIMIT 0,
.
row_count
For prepared statements, you can use placeholders (supported
as of MySQL version 5.0.7). The following statements will
return one row from the tbl
table:
SET @a=1; PREPARE STMT FROM 'SELECT * FROM tbl LIMIT ?'; EXECUTE STMT USING @a;
The following statements will return the second to sixth row
from the tbl
table:
SET @skip=1; SET @numrows=5; PREPARE STMT FROM 'SELECT * FROM tbl LIMIT ?, ?'; EXECUTE STMT USING @skip, @numrows;
For compatibility with PostgreSQL, MySQL also supports the
LIMIT
syntax.
row_count
OFFSET
offset
The SELECT ... INTO OUTFILE
'
form of
file_name
'SELECT
writes the selected rows to a
file. The file is created on the server host, so you must
have the FILE
privilege to use this
syntax. file_name
cannot be an
existing file, which among other things prevents files such
as /etc/passwd
and database tables from
being destroyed. As of MySQL 5.0.19, the
character_set_filesystem
system variable
controls the interpretation of the filename.
The SELECT ... INTO OUTFILE
statement is
intended primarily to let you very quickly dump a table to a
text file on the server machine. If you want to create the
resulting file on some client host other than the server
host, you cannot use SELECT ... INTO
OUTFILE
. In that case, you should instead use a
command such as mysql -e "SELECT ..." >
to generate
the file on the client host.
file_name
SELECT ... INTO OUTFILE
is the complement
of LOAD DATA INFILE
; the syntax for the
export_options
part of the
statement consists of the same FIELDS
and
LINES
clauses that are used with the
LOAD DATA INFILE
statement. See
Section 13.2.5, “LOAD DATA INFILE
Syntax”.
FIELDS ESCAPED BY
controls how to write
special characters. If the FIELDS ESCAPED
BY
character is not empty, it is used as a prefix
that precedes following characters on output:
The FIELDS ESCAPED BY
character
The FIELDS [OPTIONALLY] ENCLOSED BY
character
The first character of the FIELDS TERMINATED
BY
and LINES TERMINATED BY
values
ASCII NUL
(the zero-valued byte; what
is actually written following the escape character is
ASCII ‘0
’, not a
zero-valued byte)
The FIELDS TERMINATED BY
,
ENCLOSED BY
, ESCAPED
BY
, or LINES TERMINATED BY
characters must be escaped so that you
can read the file back in reliably. ASCII
NUL
is escaped to make it easier to view
with some pagers.
The resulting file does not have to conform to SQL syntax, so nothing else need be escaped.
If the FIELDS ESCAPED BY
character is
empty, no characters are escaped and NULL
is output as NULL
, not
\N
. It is probably not a good idea to
specify an empty escape character, particularly if field
values in your data contain any of the characters in the
list just given.
Here is an example that produces a file in the comma-separated values (CSV) format used by many programs:
SELECT a,b,a+b INTO OUTFILE '/tmp/result.txt' FIELDS TERMINATED BY ',' OPTIONALLY ENCLOSED BY '"' LINES TERMINATED BY '\n' FROM test_table;
If you use INTO DUMPFILE
instead of
INTO OUTFILE
, MySQL writes only one row
into the file, without any column or line termination and
without performing any escape processing. This is useful if
you want to store a BLOB
value in a file.
The INTO
clause can name a list of one or
more user-defined variables. The selected values are
assigned to the variables. The number of variables must
match the number of columns.
Within a stored routine, the variables can be routine
parameters or local variables. See
Section 17.2.7.3, “SELECT ... INTO
Statement”.
Note: Any file created by
INTO OUTFILE
or INTO
DUMPFILE
is writable by all users on the server
host. The reason for this is that the MySQL server cannot
create a file that is owned by anyone other than the user
under whose account it is running. (You should
never run mysqld as
root
for this and other reasons.) The
file thus must be world-writable so that you can manipulate
its contents.
The SELECT
syntax description at the
beginning this section shows the INTO
clause near the end of the statement. It is also possible to
use INTO OUTFILE
or INTO
DUMPFILE
immediately preceding the
FROM
clause.
A PROCEDURE
clause names a procedure that
should process the data in the result set. For an example,
see Section 24.3.1, “Procedure Analyse”.
If you use FOR UPDATE
with a storage
engine that uses page or row locks, rows examined by the
query are write-locked until the end of the current
transaction. Using LOCK IN SHARE MODE
sets a shared lock that allows other transactions to read
the examined rows but not to update or delete them. See
Section 14.2.10.5, “SELECT ... FOR UPDATE
and SELECT ... LOCK IN SHARE MODE
Locking Reads”.
Following the SELECT
keyword, you can use a
number of options that affect the operation of the statement.
The ALL
, DISTINCT
, and
DISTINCTROW
options specify whether duplicate
rows should be returned. If none of these options are given, the
default is ALL
(all matching rows are
returned). DISTINCT
and
DISTINCTROW
are synonyms and specify removal
of duplicate rows from the result set.
HIGH_PRIORITY
,
STRAIGHT_JOIN
, and options beginning with
SQL_
are MySQL extensions to standard SQL.
HIGH_PRIORITY
gives the
SELECT
higher priority than a statement
that updates a table. You should use this only for queries
that are very fast and must be done at once. A
SELECT HIGH_PRIORITY
query that is issued
while the table is locked for reading runs even if there is
an update statement waiting for the table to be free.
HIGH_PRIORITY
cannot be used with
SELECT
statements that are part of a
UNION
.
STRAIGHT_JOIN
forces the optimizer to
join the tables in the order in which they are listed in the
FROM
clause. You can use this to speed up
a query if the optimizer joins the tables in non-optimal
order. See Section 7.2.1, “Optimizing Queries with EXPLAIN
”.
STRAIGHT_JOIN
also can be used in the
table_references
list. See
Section 13.2.7.1, “JOIN
Syntax”.
SQL_BIG_RESULT
can be used with
GROUP BY
or DISTINCT
to tell the optimizer that the result set has many rows. In
this case, MySQL directly uses disk-based temporary tables
if needed, and prefers sorting to using a temporary table
with a key on the GROUP BY
elements.
SQL_BUFFER_RESULT
forces the result to be
put into a temporary table. This helps MySQL free the table
locks early and helps in cases where it takes a long time to
send the result set to the client.
SQL_SMALL_RESULT
can be used with
GROUP BY
or DISTINCT
to tell the optimizer that the result set is small. In this
case, MySQL uses fast temporary tables to store the
resulting table instead of using sorting. This should not
normally be needed.
SQL_CALC_FOUND_ROWS
tells MySQL to
calculate how many rows there would be in the result set,
disregarding any LIMIT
clause. The number
of rows can then be retrieved with SELECT
FOUND_ROWS()
. See
Section 12.9.3, “Information Functions”.
SQL_CACHE
tells MySQL to store the query
result in the query cache if you are using a
query_cache_type
value of
2
or DEMAND
. For a
query that uses UNION
or subqueries, this
option effects any SELECT
in the query.
See Section 5.14, “The MySQL Query Cache”.
SQL_NO_CACHE
tells MySQL not to store the
query result in the query cache. See
Section 5.14, “The MySQL Query Cache”. For a query that uses
UNION
or subqueries, this option effects
any SELECT
in the query.
MySQL supports the following JOIN
syntaxes
for the table_references
part of
SELECT
statements and multiple-table
DELETE
and UPDATE
statements:
table_references:
table_reference
[,table_reference
] ...table_reference
:table_factor
|join_table
table_factor
:tbl_name
[[AS]alias
] [{USE|IGNORE|FORCE} INDEX (key_list
)] | (table_references
) | { OJtable_reference
LEFT OUTER JOINtable_reference
ONconditional_expr
}join_table
:table_reference
[INNER | CROSS] JOINtable_factor
[join_condition
] |table_reference
STRAIGHT_JOINtable_factor
|table_reference
STRAIGHT_JOINtable_factor
ONcondition
|table_reference
LEFT [OUTER] JOINtable_reference
join_condition
|table_reference
NATURAL [LEFT [OUTER]] JOINtable_factor
|table_reference
RIGHT [OUTER] JOINtable_reference
join_condition
|table_reference
NATURAL [RIGHT [OUTER]] JOINtable_factor
join_condition
: ONconditional_expr
| USING (column_list
)
A table reference is also known as a join expression.
The syntax of table_factor
is
extended in comparison with the SQL Standard. The latter
accepts only table_reference
, not a
list of them inside a pair of parentheses.
This is a conservative extension if we consider each comma in
a list of table_reference
items as
equivalent to an inner join. For example:
SELECT * FROM t1 LEFT JOIN (t2, t3, t4) ON (t2.a=t1.a AND t3.b=t1.b AND t4.c=t1.c)
is equivalent to:
SELECT * FROM t1 LEFT JOIN (t2 CROSS JOIN t3 CROSS JOIN t4) ON (t2.a=t1.a AND t3.b=t1.b AND t4.c=t1.c)
In MySQL, CROSS JOIN
is a syntactic
equivalent to INNER JOIN
(they can replace
each other). In standard SQL, they are not equivalent.
INNER JOIN
is used with an
ON
clause, CROSS JOIN
is
used otherwise.
In versions of MySQL prior to 5.0.1, parentheses in
table_references
were just omitted
and all join operations were grouped to the left. In general,
parentheses can be ignored in join expressions containing only
inner join operations. As of 5.0.1, nested joins are allowed
(see Section 7.2.10, “Nested Join Optimization”).
Further changes in join processing were made in 5.0.12 to make MySQL more compliant with standard SQL. These charges are described later in this section.
The following list describes general factors to take into account when writing joins.
A table reference can be aliased using
or
tbl_name
AS
alias_name
tbl_name alias_name
:
SELECT t1.name, t2.salary FROM employee AS t1 INNER JOIN info AS t2 ON t1.name = t2.name; SELECT t1.name, t2.salary FROM employee t1 INNER JOIN info t2 ON t1.name = t2.name;
INNER JOIN
and ,
(comma) are semantically equivalent in the absence of a
join condition: both produce a Cartesian product between
the specified tables (that is, each and every row in the
first table is joined to each and every row in the second
table).
However, the precedence of the comma operator is less than
than of INNER JOIN
, CROSS
JOIN
, LEFT JOIN
, and so on.
If you mix comma joins with the other join types when
there is a join condition, an error of the form
Unknown column
'
may occur. Information about dealing
with this problem is given later in this section.
col_name
' in 'on
clause'
The ON
conditional is any conditional
expression of the form that can be used in a
WHERE
clause. Generally, you should use
the ON
clause for conditions that
specify how to join tables, and the
WHERE
clause to restrict which rows you
want in the result set.
If there is no matching row for the right table in the
ON
or USING
part in
a LEFT JOIN
, a row with all columns set
to NULL
is used for the right table.
You can use this fact to find rows in a table that have no
counterpart in another table:
SELECT table1.* FROM table1 LEFT JOIN table2 ON table1.id=table2.id WHERE table2.id IS NULL;
This example finds all rows in table1
with an id
value that is not present in
table2
(that is, all rows in
table1
with no corresponding row in
table2
). This assumes that
table2.id
is declared NOT
NULL
. See
Section 7.2.9, “LEFT JOIN
and RIGHT JOIN
Optimization”.
The
USING(
clause names a list of columns that must exist in both
tables. If tables column_list
)a
and
b
both contain columns
c1
, c2
, and
c3
, the following join compares
corresponding columns from the two tables:
a LEFT JOIN b USING (c1,c2,c3)
The NATURAL [LEFT] JOIN
of two tables
is defined to be semantically equivalent to an
INNER JOIN
or a LEFT
JOIN
with a USING
clause that
names all columns that exist in both tables.
RIGHT JOIN
works analogously to
LEFT JOIN
. To keep code portable across
databases, it is recommended that you use LEFT
JOIN
instead of RIGHT JOIN
.
The { OJ ... LEFT OUTER JOIN ...}
syntax shown in the join syntax description exists only
for compatibility with ODBC. The curly braces in the
syntax should be written literally; they are not
metasyntax as used elsewhere in syntax descriptions.
STRAIGHT_JOIN
is identical to
JOIN
, except that the left table is
always read before the right table. This can be used for
those (few) cases for which the join optimizer puts the
tables in the wrong order.
Some join examples:
SELECT * FROM table1, table2; SELECT * FROM table1 INNER JOIN table2 ON table1.id=table2.id; SELECT * FROM table1 LEFT JOIN table2 ON table1.id=table2.id; SELECT * FROM table1 LEFT JOIN table2 USING (id); SELECT * FROM table1 LEFT JOIN table2 ON table1.id=table2.id LEFT JOIN table3 ON table2.id=table3.id;
You can provide hints as to which index MySQL should use when
retrieving information from a table. By specifying
USE INDEX
(
, you can tell
MySQL to use only one of the possible indexes to find rows in
the table. The alternative syntax key_list
)IGNORE INDEX
(
can be used to
tell MySQL to not use some particular index. These hints are
useful if key_list
)EXPLAIN
shows that MySQL is using
the wrong index from the list of possible indexes.
You can also use FORCE INDEX
, which acts
like USE INDEX
(
but with the
addition that a table scan is assumed to be
very expensive. In other words, a table
scan is used only if there is no way to use one of the given
indexes to find rows in the table.
key_list
)
USE INDEX
, IGNORE INDEX
,
and FORCE INDEX
affect only which indexes
are used when MySQL decides how to find rows in the table and
how to do the join. They do not affect whether an index is
used when resolving an ORDER BY
or
GROUP BY
.
USE KEY
, IGNORE KEY
, and
FORCE KEY
are synonyms for USE
INDEX
, IGNORE INDEX
, and
FORCE INDEX
.
Examples:
SELECT * FROM table1 USE INDEX (key1,key2) WHERE key1=1 AND key2=2 AND key3=3; SELECT * FROM table1 IGNORE INDEX (key3) WHERE key1=1 AND key2=2 AND key3=3;
Join Processing Changes in MySQL 5.0.12
Beginning with MySQL 5.0.12, natural joins and joins with
USING
, including outer join variants, are
processed according to the SQL:2003 standard. The goal was to
align the syntax and semantics of MySQL with respect to
NATURAL JOIN
and JOIN ...
USING
according to SQL:2003. However, these changes
in join processing can result in different output columns for
some joins. Also, some queries that appeared to work correctly
in older versions must be rewritten to comply with the
standard.
These changes have five main aspects:
The way that MySQL determines the result columns of
NATURAL
or USING
join operations (and thus the result of the entire
FROM
clause).
Expansion of SELECT *
and
SELECT
into a
list of selected columns.
tbl_name
.*
Resolution of column names in NATURAL
or USING
joins.
Transformation of NATURAL
or
USING
joins into JOIN ...
ON
.
Resolution of column names in the ON
condition of a JOIN ... ON
.
The following list provides more detail about several effects of the 5.0.12 change in join processing. The term “previously” means “prior to MySQL 5.0.12.”
The columns of a NATURAL
join or a
USING
join may be different from
previously. Specifically, redundant output columns no
longer appear, and the order of columns for
SELECT *
expansion may be different
from before.
Consider this set of statements:
CREATE TABLE t1 (i INT, j INT); CREATE TABLE t2 (k INT, j INT); INSERT INTO t1 VALUES(1,1); INSERT INTO t2 VALUES(1,1); SELECT * FROM t1 NATURAL JOIN t2; SELECT * FROM t1 JOIN t2 USING (j);
Previously, the statements produced this output:
+------+------+------+------+ | i | j | k | j | +------+------+------+------+ | 1 | 1 | 1 | 1 | +------+------+------+------+ +------+------+------+------+ | i | j | k | j | +------+------+------+------+ | 1 | 1 | 1 | 1 | +------+------+------+------+
In the first SELECT
statement, column
i
appears in both tables and thus
becomes a join column, so, according to standard SQL, it
should appear only once in the output, not twice.
Similarly, in the second SELECT statement, column
j
is named in the
USING
clause and should appear only
once in the output, not twice. But in both cases, the
redundant column is not eliminated. Also, the order of the
columns is not correct according to standard SQL.
Now the statements produce this output:
+------+------+------+ | j | i | k | +------+------+------+ | 1 | 1 | 1 | +------+------+------+ +------+------+------+ | j | i | k | +------+------+------+ | 1 | 1 | 1 | +------+------+------+
The redundant column is eliminated and the column order is correct according to standard SQL:
First, coalesced common columns of the two joined tables, in the order in which they occur in the first table
Second, columns unique to the first table, in order in which they occur in that table
Third, columns unique to the second table, in order in which they occur in that table
The single result column that replaces two common columns
is defined via the coalesce operation. That is, fro two
t1.a
and t2.a
the
resulting single join column a
is
defined as a = COALESCE(t1.a, t2.a)
,
where:
COALESCE(x, y) = (CASE WHEN V1 IS NOT NULL THEN V1 ELSE V2 END)
If the join operation is any other join, the result columns of the join consists of the concatenation of all columns of the joined tables. This is the same as previously.
A consequence of the definition of coalesced columns is
that, for outer joins, the coalesced column contains the
value of the non-NULL
column if one of
the two columns is always NULL
. If
neither or both columns are NULL
, both
common columns have the same value, so it doesn't matter
which one is chosen as the value of the coalesced column.
A simple way to interpret this is to consider that a
coalesced column of an outer join is represented by the
common column of the inner table of a
JOIN
. Suppose that the tables
t1(a,b)
and t2(a,c)
have the following contents:
t1 t2 ---- ---- 1 x 2 z 2 y 3 w
Then:
mysql> SELECT * FROM t1 NATURAL LEFT JOIN t2;
+------+------+------+
| a | b | c |
+------+------+------+
| 1 | x | NULL |
| 2 | y | y |
+------+------+------+
Here column a
contains the values of
t1.a
.
mysql> SELECT * FROM t1 NATURAL RIGHT JOIN t2;
+------+------+------+
| a | c | b |
+------+------+------+
| 2 | y | y |
| 3 | z | NULL |
+------+------+------+
Here column a
contains the values of
t2.a
.
Compare these results to the otherwise equivalent queries
with JOIN ... ON
:
mysql> SELECT * FROM t1 LEFT JOIN t2 ON (t1.a = t2.a);
+------+------+------+------+
| a | b | a | c |
+------+------+------+------+
| 1 | x | NULL | NULL |
| 2 | y | 2 | y |
+------+------+------+------+
mysql> SELECT * FROM t1 RIGHT JOIN t2 ON (t1.a = t2.a);
+------+------+------+------+
| a | b | a | c |
+------+------+------+------+
| 2 | y | 2 | y |
| NULL | NULL | 3 | z |
+------+------+------+------+
Previously, a USING
clause could be
rewritten as an ON
clause that compares
corresponding columns. For example, the following two
clauses were semantically identical:
a LEFT JOIN b USING (c1,c2,c3) a LEFT JOIN b ON a.c1=b.c1 AND a.c2=b.c2 AND a.c3=b.c3
Now the two clauses no longer are quite the same:
With respect to determining which rows satisfy the join condition, both joins remain semantically identical.
With respect to determining which columns to display
for SELECT *
expansion, the two
joins are not semantically identical. The
USING
join selects the coalesced
value of corresponding columns, whereas the
ON
join selects all columns from
all tables. For the preceding USING
join, SELECT *
selects these
values:
COALESCE(a.c1,b.c1), COALESCE(a.c2,b.c2), COALESCE(a.c3,b.c3)
For the ON
join, SELECT
*
selects these values:
a.c1, a.c2, a.c3, b.c1, b.c2, b.c3
With an inner join,
COALESCE(a.c1,b.c1)
is the same as
either a.c1
or
b.c1
because both columns will have
the same value. With an outer join (such as
LEFT JOIN
), one of the two columns
can be NULL
. That column will be
omitted from the result.
The evaluation of multi-way natural joins differs in a
very important way that affects the result of
NATURAL
or USING
joins and that can require query rewriting. Suppose that
you have three tables t1(a,b)
,
t2(c,b)
, and t3(a,c)
that each have one row: t1(1,2)
,
t2(10,2)
, and
t3(7,10)
. Suppose also that you have
this NATURAL JOIN
on the three tables:
SELECT ... FROM t1 NATURAL JOIN t2 NATURAL JOIN t3;
Previously, the left operand of the second join was
considered to be t2
, whereas it should
be the nested join (t1 NATURAL JOIN
t2)
. As a result, the columns of
t3
are checked for common columns only
in t2
, and, if t3
has common columns with t1
, these
columns are not used as equi-join columns. Thus,
previously, the preceding query was transformed to the
following equi-join:
SELECT ... FROM t1, t2, t3 WHERE t1.b = t2.b AND t2.c = t3.c;
That join is missing one more equi-join predicate
(t1.a = t3.a)
. As a result, it produces
one row, not the empty result that it should. The correct
equivalent query is this:
SELECT ... FROM t1, t2, t3 WHERE t1.b = t2.b AND t2.c = t3.c AND t1.a = t3.a;
If you require the same query result in current versions of MySQL as in older versions, rewrite the natural join as the first equi-join.
Previously, the comma operator (,
) and
JOIN
both had the same precedence, so
the join expression t1, t2 JOIN t3
was
interpreted as ((t1, t2) JOIN t3)
. Now
JOIN
has higher precedence, so the
expression is interpreted as (t1, (t2 JOIN
t3))
. This change affects statements that use an
ON
clause, because that clause can
refer only to columns in the operands of the join, and the
change in precedence changes interpretation of what those
operands are.
Example:
CREATE TABLE t1 (i1 INT, j1 INT); CREATE TABLE t2 (i2 INT, j2 INT); CREATE TABLE t3 (i3 INT, j3 INT); INSERT INTO t1 VALUES(1,1); INSERT INTO t2 VALUES(1,1); INSERT INTO t3 VALUES(1,1); SELECT * FROM t1, t2 JOIN t3 ON (t1.i1 = t3.i3);
Previously, the SELECT
was legal due to
the implicit grouping of t1,t2
as
(t1,t2)
. Now the
JOIN
takes precedence, so the operands
for the ON
clause are
t2
and t3
. Because
t1.i1
is not a column in either of the
operands, the result is an Unknown column 't1.i1'
in 'on clause'
error. To allow the join to be
processed, group the first two tables explicitly with
parentheses so that the operands for the
ON
clause are
(t1,t2)
and t3
:
SELECT * FROM (t1, t2) JOIN t3 ON (t1.i1 = t3.i3);
Alternatively, avoid the use of the comma operator and use
JOIN
instead:
SELECT * FROM t1 JOIN t2 JOIN t3 ON (t1.i1 = t3.i3);
This change also applies to statements that mix the comma
operator with INNER JOIN
,
CROSS JOIN
, LEFT
JOIN
, and RIGHT JOIN
, all of
which now have higher precedence than the comma operator.
Previously, the ON
clause could refer
to columns in tables named to its right. Now an
ON
clause can refer only to its
operands.
Example:
CREATE TABLE t1 (i1 INT); CREATE TABLE t2 (i2 INT); CREATE TABLE t3 (i3 INT); SELECT * FROM t1 JOIN t2 ON (i1 = i3) JOIN t3;
Previously, the SELECT
statement was
legal. Now the statement fails with an Unknown
column 'i3' in 'on clause'
error because
i3
is a column in
t3
, which is not an operand of the
ON
clause. The statement should be
rewritten as follows:
SELECT * FROM t1 JOIN t2 JOIN t3 ON (i1 = i3);
Resolution of column names in NATURAL
or USING
joins is different than
previously. For column names that are outside the
FROM
clause, MySQL now handles a
superset of the queries compared to previously. That is,
in cases when MySQL formerly issued an error that some
column is ambiguous, the query now is handled correctly.
This is due to the fact that MySQL now treats the common
columns of NATURAL
or
USING
joins as a single column, so when
a query refers to such columns, the query compiler does
not consider them as ambiguous.
Example:
SELECT * FROM t1 NATURAL JOIN t2 WHERE b > 1;
Previously, this query would produce an error
ERROR 1052 (23000): Column 'b' in where clause is
ambiguous
. Now the query produces the correct
result:
+------+------+------+ | b | c | y | +------+------+------+ | 4 | 2 | 3 | +------+------+------+
One extension of MySQL compared to the SQL:2003 standard
is that MySQL allows you to qualify the common (coalesced)
columns of NATURAL
or
USING
joins (just as previously), while
the standard disallows that.
SELECT ... UNION [ALL | DISTINCT] SELECT ... [UNION [ALL | DISTINCT] SELECT ...]
UNION
is used to combine the result from
multiple SELECT
statements into a single
result set.
The column names from the first SELECT
statement are used as the column names for the results
returned. Selected columns listed in corresponding positions
of each SELECT
statement should have the
same data type. (For example, the first column selected by the
first statement should have the same type as the first column
selected by the other statements.)
If the data types of corresponding SELECT
columns do not match, the types and lengths of the columns in
the UNION
result take into account the
values retrieved by all of the SELECT
statements. For example, consider the following:
mysql> SELECT REPEAT('a',1) UNION SELECT REPEAT('b',10);
+---------------+
| REPEAT('a',1) |
+---------------+
| a |
| bbbbbbbbbb |
+---------------+
(In some earlier versions of MySQL, only the type and length
from the first SELECT
would have been used
and the second row would have been truncated to a length of
1.)
The SELECT
statements are normal select
statements, but with the following restrictions:
Only the last SELECT
statement can use
INTO OUTFILE
.
HIGH_PRIORITY
cannot be used with
SELECT
statements that are part of a
UNION
. If you specify it for the first
SELECT
, it has no effect. If you
specify it for any subsequent SELECT
statements, a syntax error results.
The default behavior for UNION
is that
duplicate rows are removed from the result. The optional
DISTINCT
keyword has no effect other than
the default because it also specifies duplicate-row removal.
With the optional ALL
keyword,
duplicate-row removal does not occur and the result includes
all matching rows from all the SELECT
statements.
You can mix UNION ALL
and UNION
DISTINCT
in the same query. Mixed
UNION
types are treated such that a
DISTINCT
union overrides any
ALL
union to its left. A
DISTINCT
union can be produced explicitly
by using UNION DISTINCT
or implicitly by
using UNION
with no following
DISTINCT
or ALL
keyword.
To use an ORDER BY
or
LIMIT
clause to sort or limit the entire
UNION
result, parenthesize the individual
SELECT
statements and place the
ORDER BY
or LIMIT
after
the last one. The following example uses both clauses:
(SELECT a FROM t1 WHERE a=10 AND B=1) UNION (SELECT a FROM t2 WHERE a=11 AND B=2) ORDER BY a LIMIT 10;
This kind of ORDER BY
cannot use column
references that include a table name (that is, names in
tbl_name
.col_name
format). Instead, provide a column alias in the first
SELECT
statement and refer to the alias in
the ORDER BY
. (Alternatively, refer to the
column in the ORDER BY
using its column
position. However, use of column positions is deprecated.)
Also, if a column to be sorted is aliased, the ORDER
BY
clause must refer to the
alias, not the column name. The first of the following
statements will work, but the second will fail with an
Unknown column 'a' in 'order clause'
error:
(SELECT a AS b FROM t) UNION (SELECT ...) ORDER BY b; (SELECT a AS b FROM t) UNION (SELECT ...) ORDER BY a;
To apply ORDER BY
or
LIMIT
to an individual
SELECT
, place the clause inside the
parentheses that enclose the SELECT
:
(SELECT a FROM t1 WHERE a=10 AND B=1 ORDER BY a LIMIT 10) UNION (SELECT a FROM t2 WHERE a=11 AND B=2 ORDER BY a LIMIT 10);
Use of ORDER BY
for individual
SELECT
statements implies nothing about the
order in which the rows appear in the final result because
UNION
by default produces an unordered set
of rows. If ORDER BY
appears with
LIMIT
, it is used to determine the subset
of the selected rows to retrieve for the
SELECT
, but does not necessarily affect the
order of those rows in the final UNION
result. If ORDER BY
appears without
LIMIT
in a SELECT
, it is
optimized away because it will have no effect anyway.
To cause rows in a UNION
result to consist
of the sets of rows retrieved by each
SELECT
one after the other, select an
additional column in each SELECT
to use as
a sort column and add an ORDER BY
following
the last SELECT
:
(SELECT 1 AS sort_col, col1a, col1b, ... FROM t1) UNION (SELECT 2, col2a, col2b, ... FROM t2) ORDER BY sort_col;
To additionally maintain sort order within individual
SELECT
results, add a secondary column to
the ORDER BY
clause:
(SELECT 1 AS sort_col, col1a, col1b, ... FROM t1) UNION (SELECT 2, col2a, col2b, ... FROM t2) ORDER BY sort_col, col1a;
A subquery is a SELECT
statement within
another statement.
Starting with MySQL 4.1, all subquery forms and operations that the SQL standard requires are supported, as well as a few features that are MySQL-specific.
Here is an example of a subquery:
SELECT * FROM t1 WHERE column1 = (SELECT column1 FROM t2);
In this example, SELECT * FROM t1 ...
is the
outer query (or outer
statement), and (SELECT column1 FROM
t2)
is the subquery. We say that
the subquery is nested within the outer
query, and in fact it is possible to nest subqueries within
other subqueries, to a considerable depth. A subquery must
always appear within parentheses.
The main advantages of subqueries are:
They allow queries that are structured so that it is possible to isolate each part of a statement.
They provide alternative ways to perform operations that would otherwise require complex joins and unions.
They are, in many people's opinion, readable. Indeed, it was the innovation of subqueries that gave people the original idea of calling the early SQL “Structured Query Language.”
Here is an example statement that shows the major points about subquery syntax as specified by the SQL standard and supported in MySQL:
DELETE FROM t1 WHERE s11 > ANY (SELECT COUNT(*) /* no hint */ FROM t2 WHERE NOT EXISTS (SELECT * FROM t3 WHERE ROW(5*t2.s1,77)= (SELECT 50,11*s1 FROM t4 UNION SELECT 50,77 FROM (SELECT * FROM t5) AS t5)));
A subquery can return a scalar (a single value), a single row, a single column, or a table (one or more rows of one or more columns). These are called scalar, column, row, and table subqueries. Subqueries that return a particular kind of result often can be used only in certain contexts, as described in the following sections.
There are few restrictions on the type of statements in which
subqueries can be used. A subquery can contain any of the
keywords or clauses that an ordinary SELECT
can contain: DISTINCT
, GROUP
BY
, ORDER BY
,
LIMIT
, joins, index hints,
UNION
constructs, comments, functions, and so
on.
One restriction is that a subquery's outer statement must be one
of: SELECT
, INSERT
,
UPDATE
, DELETE
,
SET
, or DO
. Another
restriction is that currently you cannot modify a table and
select from the same table in a subquery. This applies to
statements such as DELETE
,
INSERT
, REPLACE
,
UPDATE
, and (because subqueries can be used
in the SET
clause) LOAD DATA
INFILE
.
A more comprehensive discussion of restrictions on subquery use, including performance issues for certain forms of subquery syntax, is given in Section I.3, “Restrictions on Subqueries”.
In its simplest form, a subquery is a scalar subquery that
returns a single value. A scalar subquery is a simple operand,
and you can use it almost anywhere a single column value or
literal is legal, and you can expect it to have those
characteristics that all operands have: a data type, a length,
an indication whether it can be NULL
, and
so on. For example:
CREATE TABLE t1 (s1 INT, s2 CHAR(5) NOT NULL); INSERT INTO t1 VALUES(100, 'abcde'); SELECT (SELECT s2 FROM t1);
The subquery in this SELECT
returns a
single value ('abcde'
) that has a data type
of CHAR
, a length of 5, a character set and
collation equal to the defaults in effect at CREATE
TABLE
time, and an indication that the value in the
column can be NULL
. In fact, almost all
subqueries can be NULL
. If the table used
in the example were empty, the value of the subquery would be
NULL
.
There are a few contexts in which a scalar subquery cannot be
used. If a statement allows only a literal value, you cannot
use a subquery. For example, LIMIT
requires
literal integer arguments, and LOAD DATA
INFILE
requires a literal string filename. You
cannot use subqueries to supply these values.
When you see examples in the following sections that contain
the rather spartan construct (SELECT column1 FROM
t1)
, imagine that your own code contains much more
diverse and complex constructions.
Suppose that we make two tables:
CREATE TABLE t1 (s1 INT); INSERT INTO t1 VALUES (1); CREATE TABLE t2 (s1 INT); INSERT INTO t2 VALUES (2);
Then perform a SELECT
:
SELECT (SELECT s1 FROM t2) FROM t1;
The result is 2
because there is a row in
t2
containing a column
s1
that has a value of
2
.
A scalar subquery can be part of an expression, but remember the parentheses, even if the subquery is an operand that provides an argument for a function. For example:
SELECT UPPER((SELECT s1 FROM t1)) FROM t2;
The most common use of a subquery is in the form:
non_subquery_operand
comparison_operator
(subquery
)
Where comparison_operator
is one of
these operators:
= > < >= <= <>
For example:
... 'a' = (SELECT column1 FROM t1)
At one time the only legal place for a subquery was on the right side of a comparison, and you might still find some old DBMSs that insist on this.
Here is an example of a common-form subquery comparison that
you cannot do with a join. It finds all the values in table
t1
that are equal to a maximum value in
table t2
:
SELECT column1 FROM t1 WHERE column1 = (SELECT MAX(column2) FROM t2);
Here is another example, which again is impossible with a join
because it involves aggregating for one of the tables. It
finds all rows in table t1
containing a
value that occurs twice in a given column:
SELECT * FROM t1 AS t WHERE 2 = (SELECT COUNT(*) FROM t1 WHERE t1.id = t.id);
For a comparison performed with one of these operators, the
subquery must return a scalar, with the exception that
=
can be used with row subqueries. See
Section 13.2.8.5, “Row Subqueries”.
Syntax:
operand
comparison_operator
ANY (subquery
)operand
IN (subquery
)operand
comparison_operator
SOME (subquery
)
The ANY
keyword, which must follow a
comparison operator, means “return
TRUE
if the comparison is
TRUE
for ANY
of the
values in the column that the subquery returns.” For
example:
SELECT s1 FROM t1 WHERE s1 > ANY (SELECT s1 FROM t2);
Suppose that there is a row in table t1
containing (10)
. The expression is
TRUE
if table t2
contains (21,14,7)
because there is a value
7
in t2
that is less
than 10
. The expression is
FALSE
if table t2
contains (20,10)
, or if table
t2
is empty. The expression is
UNKNOWN
if table t2
contains (NULL,NULL,NULL)
.
The word IN
is an alias for =
ANY
. Thus, these two statements are the same:
SELECT s1 FROM t1 WHERE s1 = ANY (SELECT s1 FROM t2); SELECT s1 FROM t1 WHERE s1 IN (SELECT s1 FROM t2);
However, NOT IN
is not an alias for
<> ANY
, but for <>
ALL
. See Section 13.2.8.4, “Subqueries with ALL
”.
The word SOME
is an alias for
ANY
. Thus, these two statements are the
same:
SELECT s1 FROM t1 WHERE s1 <> ANY (SELECT s1 FROM t2); SELECT s1 FROM t1 WHERE s1 <> SOME (SELECT s1 FROM t2);
Use of the word SOME
is rare, but this
example shows why it might be useful. To most people's ears,
the English phrase “a is not equal to any b”
means “there is no b which is equal to a,” but
that is not what is meant by the SQL syntax. The syntax means
“there is some b to which a is not equal.” Using
<> SOME
instead helps ensure that
everyone understands the true meaning of the query.
Syntax:
operand
comparison_operator
ALL (subquery
)
The word ALL
, which must follow a
comparison operator, means “return
TRUE
if the comparison is
TRUE
for ALL
of the
values in the column that the subquery returns.” For
example:
SELECT s1 FROM t1 WHERE s1 > ALL (SELECT s1 FROM t2);
Suppose that there is a row in table t1
containing (10)
. The expression is
TRUE
if table t2
contains (-5,0,+5)
because
10
is greater than all three values in
t2
. The expression is
FALSE
if table t2
contains (12,6,NULL,-100)
because there is
a single value 12
in table
t2
that is greater than
10
. The expression is
unknown (that is,
NULL
) if table t2
contains (0,NULL,1)
.
Finally, if table t2
is empty, the result
is TRUE
. So, the following statement is
TRUE
when table t2
is
empty:
SELECT * FROM t1 WHERE 1 > ALL (SELECT s1 FROM t2);
But this statement is NULL
when table
t2
is empty:
SELECT * FROM t1 WHERE 1 > (SELECT s1 FROM t2);
In addition, the following statement is
NULL
when table t2
is
empty:
SELECT * FROM t1 WHERE 1 > ALL (SELECT MAX(s1) FROM t2);
In general, tables containing
NULL
values and empty
tables are “edge cases.” When writing
subquery code, always consider whether you have taken those
two possibilities into account.
NOT IN
is an alias for <>
ALL
. Thus, these two statements are the same:
SELECT s1 FROM t1 WHERE s1 <> ALL (SELECT s1 FROM t2); SELECT s1 FROM t1 WHERE s1 NOT IN (SELECT s1 FROM t2);
The discussion to this point has been of scalar or column subqueries; that is, subqueries that return a single value or a column of values. A row subquery is a subquery variant that returns a single row and can thus return more than one column value. Here are two examples:
SELECT * FROM t1 WHERE (1,2) = (SELECT column1, column2 FROM t2); SELECT * FROM t1 WHERE ROW(1,2) = (SELECT column1, column2 FROM t2);
The queries here are both TRUE
if table
t2
has a row where column1 =
1
and column2 = 2
.
The expressions (1,2)
and
ROW(1,2)
are sometimes called
row constructors. The two are
equivalent. They are legal in other contexts as well. For
example, the following two statements are semantically
equivalent (although currently only the second one can be
optimized):
SELECT * FROM t1 WHERE (column1,column2) = (1,1); SELECT * FROM t1 WHERE column1 = 1 AND column2 = 1;
The normal use of row constructors is for comparisons with
subqueries that return two or more columns. For example, the
following query answers the request, “find all rows in
table t1
that also exist in table
t2
”:
SELECT column1,column2,column3 FROM t1 WHERE (column1,column2,column3) IN (SELECT column1,column2,column3 FROM t2);
If a subquery returns any rows at all, EXISTS
is
subquery
TRUE
, and NOT EXISTS
is
subquery
FALSE
. For example:
SELECT column1 FROM t1 WHERE EXISTS (SELECT * FROM t2);
Traditionally, an EXISTS
subquery starts
with SELECT *
, but it could begin with
SELECT 5
or SELECT
column1
or anything at all. MySQL ignores the
SELECT
list in such a subquery, so it makes
no difference.
For the preceding example, if t2
contains
any rows, even rows with nothing but NULL
values, the EXISTS
condition is
TRUE
. This is actually an unlikely example
because a [NOT] EXISTS
subquery almost
always contains correlations. Here are some more realistic
examples:
What kind of store is present in one or more cities?
SELECT DISTINCT store_type FROM stores WHERE EXISTS (SELECT * FROM cities_stores WHERE cities_stores.store_type = stores.store_type);
What kind of store is present in no cities?
SELECT DISTINCT store_type FROM stores WHERE NOT EXISTS (SELECT * FROM cities_stores WHERE cities_stores.store_type = stores.store_type);
What kind of store is present in all cities?
SELECT DISTINCT store_type FROM stores s1 WHERE NOT EXISTS ( SELECT * FROM cities WHERE NOT EXISTS ( SELECT * FROM cities_stores WHERE cities_stores.city = cities.city AND cities_stores.store_type = stores.store_type));
The last example is a double-nested NOT
EXISTS
query. That is, it has a NOT
EXISTS
clause within a NOT EXISTS
clause. Formally, it answers the question “does a city
exist with a store that is not in
Stores
”? But it is easier to say
that a nested NOT EXISTS
answers the
question “is x
TRUE
for all
y
?”
A correlated subquery is a subquery that contains a reference to a table that also appears in the outer query. For example:
SELECT * FROM t1 WHERE column1 = ANY (SELECT column1 FROM t2 WHERE t2.column2 = t1.column2);
Notice that the subquery contains a reference to a column of
t1
, even though the subquery's
FROM
clause does not mention a table
t1
. So, MySQL looks outside the subquery,
and finds t1
in the outer query.
Suppose that table t1
contains a row where
column1 = 5
and column2 =
6
; meanwhile, table t2
contains a
row where column1 = 5
and column2
= 7
. The simple expression ... WHERE
column1 = ANY (SELECT column1 FROM t2)
would be
TRUE
, but in this example, the
WHERE
clause within the subquery is
FALSE
(because (5,6)
is
not equal to (5,7)
), so the subquery as a
whole is FALSE
.
Scoping rule: MySQL evaluates from inside to outside. For example:
SELECT column1 FROM t1 AS x WHERE x.column1 = (SELECT column1 FROM t2 AS x WHERE x.column1 = (SELECT column1 FROM t3 WHERE x.column2 = t3.column1));
In this statement, x.column2
must be a
column in table t2
because SELECT
column1 FROM t2 AS x ...
renames
t2
. It is not a column in table
t1
because SELECT column1 FROM t1
...
is an outer query that is farther
out.
For subqueries in HAVING
or ORDER
BY
clauses, MySQL also looks for column names in the
outer select list.
For certain cases, a correlated subquery is optimized. For example:
val
IN (SELECTkey_val
FROMtbl_name
WHEREcorrelated_condition
)
Otherwise, they are inefficient and likely to be slow. Rewriting the query as a join might improve performance.
Correlated subqueries cannot refer to the results of aggregate functions from the outer query.
Subqueries are legal in a SELECT
statement's FROM
clause. The actual syntax
is:
SELECT ... FROM (subquery
) [AS]name
...
The [AS]
clause is mandatory, because every table in a
name
FROM
clause must have a name. Any columns
in the subquery
select list must
have unique names. You can find this syntax described
elsewhere in this manual, where the term used is
“derived tables.”
For the sake of illustration, assume that you have this table:
CREATE TABLE t1 (s1 INT, s2 CHAR(5), s3 FLOAT);
Here is how to use a subquery in the FROM
clause, using the example table:
INSERT INTO t1 VALUES (1,'1',1.0); INSERT INTO t1 VALUES (2,'2',2.0); SELECT sb1,sb2,sb3 FROM (SELECT s1 AS sb1, s2 AS sb2, s3*2 AS sb3 FROM t1) AS sb WHERE sb1 > 1;
Result: 2, '2', 4.0
.
Here is another example: Suppose that you want to know the average of a set of sums for a grouped table. This does not work:
SELECT AVG(SUM(column1)) FROM t1 GROUP BY column1;
However, this query provides the desired information:
SELECT AVG(sum_column1) FROM (SELECT SUM(column1) AS sum_column1 FROM t1 GROUP BY column1) AS t1;
Notice that the column name used within the subquery
(sum_column1
) is recognized in the outer
query.
Subqueries in the FROM
clause can return a
scalar, column, row, or table. Subqueries in the
FROM
clause cannot be correlated
subqueries.
Subqueries in the FROM
clause are executed
even for the EXPLAIN
statement (that is,
derived temporary tables are built). This occurs because upper
level queries need information about all tables during
optimization phase.
There are some errors that apply only to subqueries. This section describes them.
Unsupported subquery syntax:
ERROR 1235 (ER_NOT_SUPPORTED_YET) SQLSTATE = 42000 Message = "This version of MySQL does not yet support 'LIMIT & IN/ALL/ANY/SOME subquery'"
This means that statements of the following form do not work yet:
SELECT * FROM t1 WHERE s1 IN (SELECT s2 FROM t2 ORDER BY s1 LIMIT 1)
Incorrect number of columns from subquery:
ERROR 1241 (ER_OPERAND_COL) SQLSTATE = 21000 Message = "Operand should contain 1 column(s)"
This error occurs in cases like this:
SELECT (SELECT column1, column2 FROM t2) FROM t1;
You may use a subquery that returns multiple columns, if the purpose is comparison. See Section 13.2.8.5, “Row Subqueries”. However, in other contexts, the subquery must be a scalar operand.
Incorrect number of rows from subquery:
ERROR 1242 (ER_SUBSELECT_NO_1_ROW) SQLSTATE = 21000 Message = "Subquery returns more than 1 row"
This error occurs for statements where the subquery returns more than one row. Consider the following example:
SELECT * FROM t1 WHERE column1 = (SELECT column1 FROM t2);
If SELECT column1 FROM t2
returns just
one row, the previous query will work. If the subquery
returns more than one row, error 1242 will occur. In that
case, the query should be rewritten as:
SELECT * FROM t1 WHERE column1 = ANY (SELECT column1 FROM t2);
Incorrectly used table in subquery:
Error 1093 (ER_UPDATE_TABLE_USED) SQLSTATE = HY000 Message = "You can't specify target table 'x' for update in FROM clause"
This error occurs in cases such as the following:
UPDATE t1 SET column2 = (SELECT MAX(column1) FROM t1);
You can use a subquery for assignment within an
UPDATE
statement because subqueries are
legal in UPDATE
and
DELETE
statements as well as in
SELECT
statements. However, you cannot
use the same table (in this case, table
t1
) for both the subquery's
FROM
clause and the update target.
For transactional storage engines, the failure of a subquery causes the entire statement to fail. For non-transactional storage engines, data modifications made before the error was encountered are preserved.
Development is ongoing, so no optimization tip is reliable for the long term. The following list provides some interesting tricks that you might want to play with:
Use subquery clauses that affect the number or order of the rows in the subquery. For example:
SELECT * FROM t1 WHERE t1.column1 IN (SELECT column1 FROM t2 ORDER BY column1); SELECT * FROM t1 WHERE t1.column1 IN (SELECT DISTINCT column1 FROM t2); SELECT * FROM t1 WHERE EXISTS (SELECT * FROM t2 LIMIT 1);
Replace a join with a subquery. For example, try this:
SELECT DISTINCT column1 FROM t1 WHERE t1.column1 IN ( SELECT column1 FROM t2);
Instead of this:
SELECT DISTINCT t1.column1 FROM t1, t2 WHERE t1.column1 = t2.column1;
Some subqueries can be transformed to joins for compatibility with older versions of MySQL that do not support subqueries. However, in some cases, converting a subquery to a join may improve performance. See Section 13.2.8.11, “Rewriting Subqueries as Joins for Earlier MySQL Versions”.
Move clauses from outside to inside the subquery. For example, use this query:
SELECT * FROM t1 WHERE s1 IN (SELECT s1 FROM t1 UNION ALL SELECT s1 FROM t2);
Instead of this query:
SELECT * FROM t1 WHERE s1 IN (SELECT s1 FROM t1) OR s1 IN (SELECT s1 FROM t2);
For another example, use this query:
SELECT (SELECT column1 + 5 FROM t1) FROM t2;
Instead of this query:
SELECT (SELECT column1 FROM t1) + 5 FROM t2;
Use a row subquery instead of a correlated subquery. For example, use this query:
SELECT * FROM t1 WHERE (column1,column2) IN (SELECT column1,column2 FROM t2);
Instead of this query:
SELECT * FROM t1 WHERE EXISTS (SELECT * FROM t2 WHERE t2.column1=t1.column1 AND t2.column2=t1.column2);
Use NOT (a = ANY (...))
rather than
a <> ALL (...)
.
Use x = ANY (
rather than table containing
(1,2)
)x=1 OR
x=2
.
Use = ANY
rather than
EXISTS
.
For uncorrelated subqueries that always return one row,
IN
is always slower than
=
. For example, use this query:
SELECT * FROM t1 WHERE t1.col_name
= (SELECT a FROM t2 WHERE b =some_const
);
Instead of this query:
SELECT * FROM t1 WHERE t1.col_name
IN (SELECT a FROM t2 WHERE b =some_const
);
These tricks might cause programs to go faster or slower.
Using MySQL facilities like the BENCHMARK()
function, you can get an idea about what helps in your own
situation. See Section 12.9.3, “Information Functions”.
Some optimizations that MySQL itself makes are:
MySQL executes non-correlated subqueries only once. Use
EXPLAIN
to make sure that a given
subquery really is non-correlated.
MySQL rewrites IN
,
ALL
, ANY
, and
SOME
subqueries in an attempt to take
advantage of the possibility that the select-list columns
in the subquery are indexed.
MySQL replaces subqueries of the following form with an
index-lookup function, which EXPLAIN
describes as a special join type
(unique_subquery
or
index_subquery
):
... IN (SELECTindexed_column
FROMsingle_table
...)
MySQL enhances expressions of the following form with an
expression involving MIN()
or
MAX()
, unless NULL
values or empty sets are involved:
value
{ALL|ANY|SOME} {> | < | >= | <=} (non-correlated subquery
)
For example, this WHERE
clause:
WHERE 5 > ALL (SELECT x FROM t)
might be treated by the optimizer like this:
WHERE 5 > (SELECT MAX(x) FROM t)
There is a chapter titled “How MySQL Transforms Subqueries” in the MySQL Internals Manual, available at http://dev.mysql.com/doc/.
In previous versions of MySQL (prior to MySQL 4.1), only
nested queries of the form INSERT ... SELECT
...
and REPLACE ... SELECT ...
were supported. Although this is not the case in MySQL
5.0, it is still true that there are sometimes
other ways to test membership in a set of values. It is also
true that on some occasions, it is not only possible to
rewrite a query without a subquery, but it can be more
efficient to make use of some of these techniques rather than
to use subqueries. One of these is the IN()
construct:
For example, this query:
SELECT * FROM t1 WHERE id IN (SELECT id FROM t2);
Can be rewritten as:
SELECT DISTINCT t1.* FROM t1, t2 WHERE t1.id=t2.id;
The queries:
SELECT * FROM t1 WHERE id NOT IN (SELECT id FROM t2); SELECT * FROM t1 WHERE NOT EXISTS (SELECT id FROM t2 WHERE t1.id=t2.id);
Can be be rewritten using IN()
:
SELECT table1.* FROM table1 LEFT JOIN table2 ON table1.id=table2.id WHERE table2.id IS NULL;
A LEFT [OUTER] JOIN
can be faster than an
equivalent subquery because the server might be able to
optimize it better — a fact that is not specific to
MySQL Server alone. Prior to SQL-92, outer joins did not
exist, so subqueries were the only way to do certain things.
Today, MySQL Server and many other modern database systems
offer a wide range of outer join types.
MySQL Server supports multiple-table DELETE
statements that can be used to efficiently delete rows based
on information from one table or even from many tables at the
same time. Multiple-table UPDATE
statements
are also supported.
TRUNCATE [TABLE] tbl_name
TRUNCATE TABLE
empties a table completely.
Logically, this is equivalent to a DELETE
statement that deletes all rows, but there are practical
differences under some circumstances.
For InnoDB
before version 5.0.3,
TRUNCATE TABLE
is mapped to
DELETE
, so there is no difference. Starting
with MySQL 5.0.3, fast TRUNCATE TABLE
is
available. However, the operation is still mapped to
DELETE
if there are foreign key constraints
that reference the table. (When fast truncate is used, it resets
any AUTO_INCREMENT
counter. From MySQL 5.0.13
on, the AUTO_INCREMENT
counter is reset by
TRUNCATE TABLE
, regardless of whether there
is a foreign key constraint.)
For other storage engines, TRUNCATE TABLE
differs from DELETE
in the following ways in
MySQL 5.0:
Truncate operations drop and re-create the table, which is much faster than deleting rows one by one.
Truncate operations are not transaction-safe; an error occurs when attempting one in the course of an active transaction or active table lock.
The number of deleted rows is not returned.
As long as the table format file
is valid, the table can be re-created as an empty table with
tbl_name
.frmTRUNCATE TABLE
, even if the data or index
files have become corrupted.
The table handler does not remember the last used
AUTO_INCREMENT
value, but starts counting
from the beginning. This is true even for
MyISAM
and InnoDB
,
which normally do not reuse sequence values.
Since truncation of a table does not make any use of
DELETE
, the TRUNCATE
statement does not invoke ON DELETE
triggers.
TRUNCATE TABLE
is an Oracle SQL extension
adopted in MySQL.
Single-table syntax:
UPDATE [LOW_PRIORITY] [IGNORE]tbl_name
SETcol_name1
=expr1
[,col_name2
=expr2
...] [WHEREwhere_condition
] [ORDER BY ...] [LIMITrow_count
]
Multiple-table syntax:
UPDATE [LOW_PRIORITY] [IGNORE]table_references
SETcol_name1
=expr1
[,col_name2
=expr2
...] [WHEREwhere_condition
]
For the single-table syntax, the UPDATE
statement updates columns of existing rows in
tbl_name
with new values. The
SET
clause indicates which columns to modify
and the values they should be given. The
WHERE
clause, if given, specifies the
conditions that identify which rows to update. With no
WHERE
clause, all rows are updated. If the
ORDER BY
clause is specified, the rows are
updated in the order that is specified. The
LIMIT
clause places a limit on the number of
rows that can be updated.
For the multiple-table syntax, UPDATE
updates
rows in each table named in
table_references
that satisfy the
conditions. In this case, ORDER BY
and
LIMIT
cannot be used.
where_condition
is an expression that
evaluates to true for each row to be updated. It is specified as
described in Section 13.2.7, “SELECT
Syntax”.
The UPDATE
statement supports the following
modifiers:
If you use the LOW_PRIORITY
keyword,
execution of the UPDATE
is delayed until
no other clients are reading from the table.
If you use the IGNORE
keyword, the update
statement does not abort even if errors occur during the
update. Rows for which duplicate-key conflicts occur are not
updated. Rows for which columns are updated to values that
would cause data conversion errors are updated to the closet
valid values instead.
If you access a column from tbl_name
in an expression, UPDATE
uses the current
value of the column. For example, the following statement sets
the age
column to one more than its current
value:
UPDATE persondata SET age=age+1;
Single-table UPDATE
assignments are generally
evaluated from left to right. For multiple-table updates, there
is no guarantee that assignments are carried out in any
particular order.
If you set a column to the value it currently has, MySQL notices this and does not update it.
If you update a column that has been declared NOT
NULL
by setting to NULL
, the column
is set to the default value appropriate for the data type and
the warning count is incremented. The default value is
0
for numeric types, the empty string
(''
) for string types, and the
“zero” value for date and time types.
UPDATE
returns the number of rows that were
actually changed. The mysql_info()
C API
function returns the number of rows that were matched and
updated and the number of warnings that occurred during the
UPDATE
.
You can use LIMIT
to restrict the
scope of the row_count
UPDATE
. A
LIMIT
clause is a rows-matched restriction.
The statement stops as soon as it has found
row_count
rows that satisfy the
WHERE
clause, whether or not they actually
were changed.
If an UPDATE
statement includes an
ORDER BY
clause, the rows are updated in the
order specified by the clause. This can be useful in certain
situations that might otherwise result in an error. Suppose that
a table t
contains a column
id
that has a unique index. The following
statement could fail with a duplicate-key error, depending on
the order in which rows are updated:
UPDATE t SET id = id + 1;
For example, if the table contains 1 and 2 in the
id
column and 1 is updated to 2 before 2 is
updated to 3, an error occurs. To avoid this problem, add an
ORDER BY
clause to cause the rows with larger
id
values to be updated before those with
smaller values:
UPDATE t SET id = id + 1 ORDER BY id DESC;
You can also perform UPDATE
operations
covering multiple tables. However, you cannot use ORDER
BY
or LIMIT
with a multiple-table
UPDATE
. The
table_references
clause lists the
tables involved in the join. Its syntax is described in
Section 13.2.7.1, “JOIN
Syntax”. Here is an example:
UPDATE items,month SET items.price=month.price WHERE items.id=month.id;
The preceding example shows an inner join that uses the comma
operator, but multiple-table UPDATE
statements can use any type of join allowed in
SELECT
statements, such as LEFT
JOIN
.
You need the UPDATE
privilege only for
columns referenced in a multiple-table UPDATE
that are actually updated. You need only the
SELECT
privilege for any columns that are
read but not modified.
If you use a multiple-table UPDATE
statement
involving InnoDB
tables for which there are
foreign key constraints, the MySQL optimizer might process
tables in an order that differs from that of their parent/child
relationship. In this case, the statement fails and rolls back.
Instead, update a single table and rely on the ON
UPDATE
capabilities that InnoDB
provides to cause the other tables to be modified accordingly.
See Section 14.2.6.4, “FOREIGN KEY
Constraints”.
Currently, you cannot update a table and select from the same table in a subquery.