13.2. Data Manipulation Statements

MySQL 5.0

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13.2. Data Manipulation Statements

13.2.1. `DELETE` Syntax

Single-table syntax:

DELETE [LOW_PRIORITY] [QUICK] [IGNORE] FROM tbl_name
    [WHERE where_condition]
    [ORDER BY ...]
    [LIMIT row_count]

Multiple-table syntax:

DELETE [LOW_PRIORITY] [QUICK] [IGNORE]
    tbl_name[.*] [, tbl_name[.*]] ...
    FROM table_references
    [WHERE where_condition]

Or:

DELETE [LOW_PRIORITY] [QUICK] [IGNORE]
    FROM tbl_name[.*] [, tbl_name[.*]] ...
    USING table_references
    [WHERE where_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 FROMtbl_name (without a 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 LIMITrow_count option to 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.

13.2.2. DO Syntax

DO expr [, expr] ...

DO executes the expressions but does not return any results. In most respects, DO is shorthand for SELECT expr, ..., but has the advantage that it is slightly faster when you do not care about the result.

DO is useful primarily with functions that have side effects, such as RELEASE_LOCK().

13.2.3. HANDLER Syntax

HANDLER tbl_name OPEN [ AS alias ] HANDLER tbl_name READ index_name { = | >= | <= | < } (value1,value2,...) [ WHERE where_condition ] [LIMIT ... ] HANDLER tbl_name READ index_name { FIRST | NEXT | PREV | LAST } [ WHERE where_condition ] [LIMIT ... ] HANDLER tbl_name READ { FIRST | NEXT } [ WHERE where_condition ] [LIMIT ... ] HANDLER tbl_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 tbl_name READ index_name when a full table scan is desired. Natural row order is the order in which rows are stored in a 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.

13.2.4. INSERT Syntax

INSERT [LOW_PRIORITY | DELAYED | HIGH_PRIORITY] [IGNORE] [INTO] tbl_name [(col_name,...)] VALUES ({expr | DEFAULT},...),(...),... [ ON DUPLICATE KEY UPDATE col_name=expr, ... ]

Or:

INSERT [LOW_PRIORITY | DELAYED | HIGH_PRIORITY] [IGNORE] [INTO] tbl_name SET col_name={expr | DEFAULT}, ... [ ON DUPLICATE KEY UPDATE col_name=expr, ... ]

Or:

INSERT [LOW_PRIORITY | HIGH_PRIORITY] [IGNORE] [INTO] tbl_name [(col_name,...)] SELECT ... [ ON DUPLICATE KEY UPDATE col_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 DESCRIBEtbl_name to find out.

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(col_name) as a more general form that can be used in expressions to produce a given column's default value.

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”.

13.2.4.1. INSERT ... SELECT Syntax

INSERT [LOW_PRIORITY | HIGH_PRIORITY] [IGNORE] [INTO] tbl_name [(col_name,...)] SELECT ... [ ON DUPLICATE KEY UPDATE col_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.

13.2.4.2. INSERT DELAYED Syntax

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.

Pending INSERT DELAYED statements are lost if a table is write locked and ALTER TABLE is used to modify the table structure.

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 KILLthread_id. However, before exiting, it first stores all queued rows into the table. During this time it does not accept any new 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 KILLthread_id), or someone executes a 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.

13.2.4.3. INSERT ... ON DUPLICATE KEY UPDATE Syntax

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(col_name) function in the UPDATE clause to refer to column values from the INSERT portion of the INSERT ... UPDATE statement. In other words, VALUES(col_name) in the 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.

13.2.5. LOAD DATA INFILE Syntax

LOAD DATA [LOW_PRIORITY | CONCURRENT] [LOCAL] INFILE 'file_name' [REPLACE | IGNORE] INTO TABLE tbl_name [FIELDS [TERMINATED BY 'string'] [[OPTIONALLY] ENCLOSED BY 'char'] [ESCAPED BY 'char'] ] [LINES [STARTING BY 'string'] [TERMINATED BY 'string'] ] [IGNORE number LINES] [(col_name_or_user_var,...)] [SET col_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 'prefix_string' 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:

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 number LINES option can be used to ignore lines at the start of the file. For example, you can use IGNORE 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.

An attempt to load NULL into a NOT NULL column causes assignment of the implicit default value for the column's data type and a warning, or an error in strict SQL mode. Implicit default values are discussed in Section 11.1.4, “Data Type Default Values”.

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”.

13.2.6. REPLACE Syntax

REPLACE [LOW_PRIORITY | DELAYED] [INTO] tbl_name [(col_name,...)] VALUES ({expr | DEFAULT},...),(...),...

Or:

REPLACE [LOW_PRIORITY | DELAYED] [INTO] tbl_name SET col_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 SETcol_name = col_name + 1, the reference to the column name on the right hand side is treated as DEFAULT(col_name), so the assignment is equivalent to SETcol_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

13.2.7. SELECT Syntax

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, ... [FROM table_references [WHERE where_condition] [GROUP BY {col_name | expr | position} [ASC | DESC], ... [WITH ROLLUP]] [HAVING where_condition] [ORDER BY {col_name | expr | position} [ASC | DESC], ...] [LIMIT {[offset,] row_count | row_count OFFSET offset}] [PROCEDURE procedure_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 ASalias_name. The alias is used as the expression's column name and can be used in 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 FROMtable_references 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, “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=value as an alternative way to force MySQL to prefer key scans instead of table scans. See Section 5.2.2, “Server System Variables”.

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 tbl_name AS alias_name or 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:

SELECT col_name FROM tbl_name HAVING col_name > 0;

Write this instead:

SELECT col_name FROM tbl_name WHERE col_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, LIMITrow_count is equivalent to 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 row_count OFFSET offset syntax.

The SELECT ... INTO OUTFILE 'file_name' form of 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 ..." >file_name to generate the file on the client host.

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.

13.2.7.1. JOIN Syntax

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 ) | { OJ table_reference LEFT OUTER JOIN table_reference ON conditional_expr } join_table: table_reference [INNER | CROSS] JOIN table_factor [join_condition] | table_reference STRAIGHT_JOIN table_factor | table_reference STRAIGHT_JOIN table_factor ON condition | table_reference LEFT [OUTER] JOIN table_reference join_condition | table_reference NATURAL [LEFT [OUTER]] JOIN table_factor | table_reference RIGHT [OUTER] JOIN table_reference join_condition | table_reference NATURAL [RIGHT [OUTER]] JOIN table_factor join_condition: ON conditional_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 tbl_name AS alias_name or 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 'col_name' in 'on clause' may occur. Information about dealing with this problem is given later in this section.

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(column_list) clause names a list of columns that must exist in both tables. If tables 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 (key_list), you can tell MySQL to use only one of the possible indexes to find rows in the table. The alternative syntax IGNORE INDEX (key_list) can be used to tell MySQL to not use some particular index. These hints are useful if 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 (key_list) 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.

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 SELECTtbl_name.* into a list of selected columns.

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 j 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.

13.2.7.2. UNION Syntax

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;

13.2.8. Subquery Syntax

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”.

13.2.8.1. The Subquery as Scalar Operand

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;

13.2.8.2. Comparisons Using Subqueries

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”.

13.2.8.3. Subqueries with ANY, IN, and SOME

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.

13.2.8.4. Subqueries with ALL

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);

13.2.8.5. Row Subqueries

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);

13.2.8.6. EXISTS and NOT EXISTS

If a subquery returns any rows at all, EXISTSsubquery is TRUE, and NOT EXISTSsubquery is 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?”

13.2.8.7. Correlated Subqueries

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 (SELECT key_val FROM tbl_name WHERE correlated_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.

13.2.8.8. Subqueries in the FROM clause

Subqueries are legal in a SELECT statement's FROM clause. The actual syntax is:

SELECT ... FROM (subquery) [AS] name ...

The [AS] name clause is mandatory, because every table in a 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.

13.2.8.9. Subquery Errors

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.

13.2.8.10. Optimizing Subqueries

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 (table containing (1,2)) rather than 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 (SELECT indexed_column FROM single_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/.

13.2.8.11. Rewriting Subqueries as Joins for Earlier MySQL Versions

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.

13.2.9. TRUNCATE Syntax

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 tbl_name.frm is valid, the table can be re-created as an empty table with TRUNCATE 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.

13.2.10. UPDATE Syntax

Single-table syntax:

UPDATE [LOW_PRIORITY] [IGNORE] tbl_name SET col_name1=expr1 [, col_name2=expr2 ...] [WHERE where_condition] [ORDER BY ...] [LIMIT row_count]

Multiple-table syntax:

UPDATE [LOW_PRIORITY] [IGNORE] table_references SET col_name1=expr1 [, col_name2=expr2 ...] [WHERE where_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 LIMITrow_count to restrict the scope of the 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.

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13.2. Data Manipulation Statements

MySQL 5.0