13.2.5.1 INSERT ... SELECT Statement

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

value:
    {expr | DEFAULT}

assignment:
    col_name = value

assignment_list:
    assignment [, assignment] ...

With INSERT ... SELECT, you can quickly insert many rows into a table from the result of a SELECT statement, which can select 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 INSERT ... SELECT statements:

• Specify IGNORE to ignore rows that would cause duplicate-key violations.

• The target table of the INSERT statement may appear in the FROM clause of the SELECT part of the query. However, you cannot insert into a table and select from the same table in a subquery.

  When selecting from and inserting into the same table, MySQL creates an internal temporary table to hold the rows from the SELECT and then inserts those rows into the target table. However, you cannot use INSERT INTO t ... SELECT ... FROM t when t is a TEMPORARY table, because TEMPORARY tables cannot be referred to twice in the same statement. See Section 8.4.4, “Internal Temporary Table Use in MySQL”, and Section B.3.6.2, “TEMPORARY Table Problems”.

• AUTO_INCREMENT columns work as usual.

• To ensure that the binary log can be used to re-create the original tables, MySQL does not permit concurrent inserts for INSERT ... SELECT statements (see Section 8.11.3, “Concurrent Inserts”).

• To avoid ambiguous column reference problems when the SELECT and the INSERT refer to the same table, provide a unique alias for each table used in the SELECT part, and qualify column names in that part with the appropriate alias.

You can explicitly select which partitions or subpartitions (or both) of the source or target table (or both) are to be used with a PARTITION clause following the name of the table. When PARTITION is used with the name of the source table in the SELECT portion of the statement, rows are selected only from the partitions or subpartitions named in its partition list. When PARTITION is used with the name of the target table for the INSERT portion of the statement, it must be possible to insert all rows selected into the partitions or subpartitions named in the partition list following the option. Otherwise, the INSERT ... SELECT statement fails. For more information and examples, see Section 22.5, “Partition Selection”.

For INSERT ... SELECT statements, see Section 13.2.5.2, “INSERT ... ON DUPLICATE KEY UPDATE Statement” for conditions under which the SELECT columns can be referred to in an ON DUPLICATE KEY UPDATE clause.

The order in which a SELECT statement with no ORDER BY clause returns rows is nondeterministic. This means that, when using replication, there is no guarantee that such a SELECT returns rows in the same order on the source and the replica, which can lead to inconsistencies between them. To prevent this from occurring, always write INSERT ... SELECT statements that are to be replicated using an ORDER BY clause that produces the same row order on the source and the replica. See also Section 16.4.1.17, “Replication and LIMIT”.

Due to this issue, INSERT ... SELECT ON DUPLICATE KEY UPDATE and INSERT IGNORE ... SELECT statements are flagged as unsafe for statement-based replication. Such statements produce a warning in the error log when using statement-based mode and are written to the binary log using the row-based format when using MIXED mode. (Bug #11758262, Bug #50439)

See also Section 16.2.1.1, “Advantages and Disadvantages of Statement-Based and Row-Based Replication”.

An INSERT ... SELECT statement affecting partitioned tables using a storage engine such as MyISAM that employs table-level locks locks all partitions of the target table; however, only those partitions that are actually read from the source table are locked. (This does not occur with tables using storage engines such as InnoDB that employ row-level locking.) For more information, see Section 22.6.4, “Partitioning and Locking”.