The REPLACE Statement

The MySQL-specific statement 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. REPLACE is a MySQL extension to the SQL standard. It either inserts, or deletes and inserts. Uses the following general syntax;

REPLACE INTO table_name (column_list) VALUES(value_list);

In this example, we are replacing a current row of data (containing three columns) in the people database;

REPLACE INTO people (id,name,age) VALUES(12,'Bruce',25);

Note that unless the table has a PRIMARY KEY or a 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. It is not possible to refer to values from the current row and use them in the new row.

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).

Currently, it is not possible to perform a replace into a table and select from the same table in a subquery.

MySQL uses the following algorithm for REPLACE:

1. Try to insert the new row into the table

2. While the insertion fails because a duplicate-key error occurs for a primary key or unique index:

              a. Delete from the table the conflicting row that has the duplicate key value

              b. Try again to insert the new row into the table