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MySQL 8.4 Reference Manual  /  ...  /  LIST Partitioning

26.2.2 LIST Partitioning

List partitioning in MySQL is similar to range partitioning in many ways. As in partitioning by RANGE, each partition must be explicitly defined. The chief difference between the two types of partitioning is that, in list partitioning, each partition is defined and selected based on the membership of a column value in one of a set of value lists, rather than in one of a set of contiguous ranges of values. This is done by using PARTITION BY LIST(expr) where expr is a column value or an expression based on a column value and returning an integer value, and then defining each partition by means of a VALUES IN (value_list), where value_list is a comma-separated list of integers.


In MySQL 8.4, it is possible to match against only a list of integers (and possibly NULL—see Section 26.2.7, “How MySQL Partitioning Handles NULL”) when partitioning by LIST.

However, other column types may be used in value lists when employing LIST COLUMN partitioning, which is described later in this section.

Unlike the case with partitions defined by range, list partitions do not need to be declared in any particular order. For more detailed syntactical information, see Section 15.1.20, “CREATE TABLE Statement”.

For the examples that follow, we assume that the basic definition of the table to be partitioned is provided by the CREATE TABLE statement shown here:

CREATE TABLE employees (
    id INT NOT NULL,
    fname VARCHAR(30),
    lname VARCHAR(30),
    hired DATE NOT NULL DEFAULT '1970-01-01',
    separated DATE NOT NULL DEFAULT '9999-12-31',
    job_code INT,
    store_id INT

(This is the same table used as a basis for the examples in Section 26.2.1, “RANGE Partitioning”. As with the other partitioning examples, we assume that the default_storage_engine is InnoDB.)

Suppose that there are 20 video stores distributed among 4 franchises as shown in the following table.

Region Store ID Numbers
North 3, 5, 6, 9, 17
East 1, 2, 10, 11, 19, 20
West 4, 12, 13, 14, 18
Central 7, 8, 15, 16

To partition this table in such a way that rows for stores belonging to the same region are stored in the same partition, you could use the CREATE TABLE statement shown here:

CREATE TABLE employees (
    id INT NOT NULL,
    fname VARCHAR(30),
    lname VARCHAR(30),
    hired DATE NOT NULL DEFAULT '1970-01-01',
    separated DATE NOT NULL DEFAULT '9999-12-31',
    job_code INT,
    store_id INT
    PARTITION pNorth VALUES IN (3,5,6,9,17),
    PARTITION pEast VALUES IN (1,2,10,11,19,20),
    PARTITION pWest VALUES IN (4,12,13,14,18),
    PARTITION pCentral VALUES IN (7,8,15,16)

This makes it easy to add or drop employee records relating to specific regions to or from the table. For instance, suppose that all stores in the West region are sold to another company. In MySQL 8.4, all rows relating to employees working at stores in that region can be deleted with the query ALTER TABLE employees TRUNCATE PARTITION pWest, which can be executed much more efficiently than the equivalent DELETE statement DELETE FROM employees WHERE store_id IN (4,12,13,14,18);. (Using ALTER TABLE employees DROP PARTITION pWest would also delete all of these rows, but would also remove the partition pWest from the definition of the table; you would need to use an ALTER TABLE ... ADD PARTITION statement to restore the table's original partitioning scheme.)

As with RANGE partitioning, it is possible to combine LIST partitioning with partitioning by hash or key to produce a composite partitioning (subpartitioning). See Section 26.2.6, “Subpartitioning”.

Unlike the case with RANGE partitioning, there is no catch-all such as MAXVALUE; all expected values for the partitioning expression should be covered in PARTITION ... VALUES IN (...) clauses. An INSERT statement containing an unmatched partitioning column value fails with an error, as shown in this example:

mysql> CREATE TABLE h2 (
    ->   c1 INT,
    ->   c2 INT
    -> )
    -> PARTITION BY LIST(c1) (
    ->   PARTITION p0 VALUES IN (1, 4, 7),
    ->   PARTITION p1 VALUES IN (2, 5, 8)
    -> );
Query OK, 0 rows affected (0.11 sec)

mysql> INSERT INTO h2 VALUES (3, 5);
ERROR 1525 (HY000): Table has no partition for value 3

When inserting multiple rows using a single INSERT statement into a single InnoDB table, InnoDB considers the statement a single transaction, so that the presence of any unmatched values causes the statement to fail completely, and so no rows are inserted.

You can cause this type of error to be ignored by using the IGNORE keyword, although a warning is issued for each row containing unmatched partitioning column values, as shown here.

mysql> TRUNCATE h2;
Query OK, 1 row affected (0.00 sec)

mysql> TABLE h2;
Empty set (0.00 sec)

mysql> INSERT IGNORE INTO h2 VALUES (2, 5), (6, 10), (7, 5), (3, 1), (1, 9);
Query OK, 3 rows affected, 2 warnings (0.01 sec)
Records: 5  Duplicates: 2  Warnings: 2

| Level   | Code | Message                            |
| Warning | 1526 | Table has no partition for value 6 |
| Warning | 1526 | Table has no partition for value 3 |
2 rows in set (0.00 sec)

You can see in the output of the following TABLE statement that rows containing unmatched partitioning column values were silently rejected, while rows containing no unmatched values were inserted into the table:

mysql> TABLE h2;
| c1   | c2   |
|    7 |    5 |
|    1 |    9 |
|    2 |    5 |
3 rows in set (0.00 sec)

MySQL also provides support for LIST COLUMNS partitioning, a variant of LIST partitioning that enables you to use columns of types other than integer for partitioning columns, and to use multiple columns as partitioning keys. For more information, see Section, “LIST COLUMNS partitioning”.