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23.2.5 KEY Partitioning

Contents

Partitioning by key is similar to partitioning by hash, except that where hash partitioning employs a user-defined expression, the hashing function for key partitioning is supplied by the MySQL server. NDB Cluster uses MD5() for this purpose; for tables using other storage engines, the server employs its own internal hashing function which is based on the same algorithm as PASSWORD().

The syntax rules for CREATE TABLE ... PARTITION BY KEY are similar to those for creating a table that is partitioned by hash. The major differences are listed here:

  • KEY is used rather than HASH.

  • KEY takes only a list of zero or more column names. Any columns used as the partitioning key must comprise part or all of the table's primary key, if the table has one. Where no column name is specified as the partitioning key, the table's primary key is used, if there is one. For example, the following CREATE TABLE statement is valid in MySQL 8.0:

    1. CREATE TABLE k1 (
    2.     id INT NOT NULL PRIMARY KEY,
    3.     name VARCHAR(20)
    4. )
    5. PARTITION BY KEY()
    6. PARTITIONS 2;

    If there is no primary key but there is a unique key, then the unique key is used for the partitioning key:

    1. CREATE TABLE k1 (
    2.     id INT NOT NULL,
    3.     name VARCHAR(20),
    4.     UNIQUE KEY (id)
    5. )
    6. PARTITION BY KEY()
    7. PARTITIONS 2;

    However, if the unique key column were not defined as NOT NULL, then the previous statement would fail.

    In both of these cases, the partitioning key is the id column, even though it is not shown in the output of SHOW CREATE TABLE or in the PARTITION_EXPRESSION column of the INFORMATION_SCHEMA.PARTITIONS table.

    Unlike the case with other partitioning types, columns used for partitioning by KEY are not restricted to integer or NULL values. For example, the following CREATE TABLE statement is valid:

    1. CREATE TABLE tm1 (
    2.     s1 CHAR(32) PRIMARY KEY
    3. )
    4. PARTITION BY KEY(s1)
    5. PARTITIONS 10;

    The preceding statement would not be valid, were a different partitioning type to be specified. (In this case, simply using PARTITION BY KEY() would also be valid and have the same effect as PARTITION BY KEY(s1), since s1 is the table's primary key.)

    For additional information about this issue, see Section 23.6, “Restrictions and Limitations on Partitioning”.

    Note

    Tables using the NDB storage engine are implicitly partitioned by KEY, again using the table's primary key as the partitioning key. In the event that the NDB Cluster table has no explicit primary key, the “hidden” primary key generated by the NDB storage engine for each NDB Cluster table is used as the partitioning key.

    If you define an explicit partitioning scheme for an NDB table, the table must have an explicit primary key, and any columns used in the partitioning expression must be part of this key. However, if the table uses an “empty” partitioning expression—that is, PARTITION BY KEY() with no column references—then no explicit primary key is required.

    You can observe this partitioning using the ndb_desc utility (with the -p option).

    Important

    For a key-partitioned table, you cannot execute an ALTER TABLE DROP PRIMARY KEY, as doing so generates the error ERROR 1466 (HY000): Field in list of fields for partition function not found in table. This is not an issue for NDB Cluster tables which are partitioned by KEY; in such cases, the table is reorganized using the “hidden” primary key as the table's new partitioning key. See Chapter 22, MySQL NDB Cluster 8.0.

It is also possible to partition a table by linear key. Here is a simple example:

  1. CREATE TABLE tk (
  2.     col1 INT NOT NULL,
  3.     col2 CHAR(5),
  4.     col3 DATE
  5. )
  6. PARTITION BY LINEAR KEY (col1)
  7. PARTITIONS 3;

The LINEAR keyword has the same effect on KEY partitioning as it does on HASH partitioning, with the partition number being derived using a powers-of-two algorithm rather than modulo arithmetic. See Section 23.2.4.1, “LINEAR HASH Partitioning”, for a description of this algorithm and its implications.


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