Chapter 17. Partitioning

Table of Contents

17.1. Overview of Partitioning in MySQL
17.2. Partition Types
17.2.1. RANGE Partitioning
17.2.2. LIST Partitioning
17.2.3. HASH Partitioning
17.2.4. KEY Partitioning
17.2.5. Subpartitioning
17.2.6. How MySQL Partitioning Handles NULL
17.3. Partition Management
17.3.1. Management of RANGE and LIST Partitions
17.3.2. Management of HASH and KEY Partitions
17.3.3. Maintenance of Partitions
17.3.4. Obtaining Information About Partitions
17.4. Partition Pruning
17.5. Restrictions and Limitations on Partitioning
17.5.1. Partitioning Keys, Primary Keys, and Unique Keys
17.5.2. Partitioning Limitations Relating to Storage Engines
17.5.3. Partitioning Limitations Relating to Functions

This chapter discusses MySQL's implementation of user-defined partitioning. You can determine whether your MySQL Server supports partitioning by means of a SHOW VARIABLES command such as this one:

mysql> SHOW VARIABLES LIKE '%partition%';

+-------------------+-------+
| Variable_name     | Value |
+-------------------+-------+
| have_partitioning | YES   |
+-------------------+-------+
1 row in set (0.00 sec)

You can also check the output of the SHOW PLUGINS statement, as shown here:

mysql> SHOW PLUGINS;
+------------+----------+----------------+---------+---------+
| Name       | Status   | Type           | Library | License |
+------------+----------+----------------+---------+---------+
| binlog     | ACTIVE   | STORAGE ENGINE | NULL    | GPL     |
| partition  | ACTIVE   | STORAGE ENGINE | NULL    | GPL     |
| ARCHIVE    | ACTIVE   | STORAGE ENGINE | NULL    | GPL     |
| BLACKHOLE  | ACTIVE   | STORAGE ENGINE | NULL    | GPL     |
| CSV        | ACTIVE   | STORAGE ENGINE | NULL    | GPL     |
| FEDERATED  | DISABLED | STORAGE ENGINE | NULL    | GPL     |
| MEMORY     | ACTIVE   | STORAGE ENGINE | NULL    | GPL     |
| InnoDB     | ACTIVE   | STORAGE ENGINE | NULL    | GPL     |
| MRG_MYISAM | ACTIVE   | STORAGE ENGINE | NULL    | GPL     |
| MyISAM     | ACTIVE   | STORAGE ENGINE | NULL    | GPL     |
| ndbcluster | DISABLED | STORAGE ENGINE | NULL    | GPL     |
+------------+----------+----------------+---------+---------+
11 rows in set (0.00 sec)

If you do not see the have_partitioning variable with the value YES listed in the output of an appropriate SHOW VARIABLES statement, or if you do not see the partition plugin listed with the value ACTIVE for the Status column in the output of SHOW PLUGINS (show in bold text in the example just given), then your version of MySQL does not support partitioning.

Community binaries provided by Sun Microsystems include partitioning support. For information about partitioning support offered in commercial MySQL Server binaries, see MySQL Enterprise Server 5.1, on the MySQL website.

If you are compiling MySQL 6.0 from source, the build must be configured using --with-partition to enable partitioning.

If your MySQL binary is built with partitioning support, nothing further needs to be done in order to enable it (for example, no special entries are required in your my.cnf file).

An introduction to partitioning and partitioning concepts may be found in Section 17.1, “Overview of Partitioning in MySQL”.

MySQL supports several types of partitioning, which are discussed in Section 17.2, “Partition Types”, as well as subpartitioning, which is described in Section 17.2.5, “Subpartitioning”.

Methods of adding, removing, and altering partitions in existing partitioned tables are covered in Section 17.3, “Partition Management”.

Table maintenance commands for use with partitioned tables are discussed in Section 17.3.3, “Maintenance of Partitions”.

The PARTITIONS table in the INFORMATION_SCHEMA database provides information about partitions and partitioned tables. See Section 19.19, “The INFORMATION_SCHEMA PARTITIONS Table”, for more information; for some examples of queries against this table, see Section 17.2.6, “How MySQL Partitioning Handles NULL.

The partitioning implementation in MySQL 6.0 is still undergoing development. For known issues with MySQL partitioning, see Section 17.5, “Restrictions and Limitations on Partitioning”, where we have noted these.

You may also find the following resources to be useful when working with partitioned tables.

Additional Resources.  Other sources of information about user-defined partitioning in MySQL include the following:

MySQL 6.0 binaries are available from http://dev.mysql.com/downloads/mysql/6.0.html. However, for the latest partitioning bugfixes and feature additions, you can obtain the source from our Bazaar repository. To enable partitioning, you need to compile the server using the --with-partition option. For more information about building MySQL, see Section 2.9, “MySQL Installation Using a Source Distribution”. If you have problems compiling a partitioning-enabled MySQL 6.0 build, check the MySQL Partitioning Forum and ask for assistance there if you do not find a solution to your problem already posted.

17.1. Overview of Partitioning in MySQL

This section provides a conceptual overview of partitioning in MySQL 6.0.

For information on partitioning restrictions and feature limitations, see Section 17.5, “Restrictions and Limitations on Partitioning”.

The SQL standard does not provide much in the way of guidance regarding the physical aspects of data storage. The SQL language itself is intended to work independently of any data structures or media underlying the schemas, tables, rows, or columns with which it works. Nonetheless, most advanced database management systems have evolved some means of determining the physical location to be used for storing specific pieces of data in terms of the file system, hardware or even both. In MySQL, the InnoDB storage engine has long supported the notion of a tablespace, and the MySQL Server, even prior to the introduction of partitioning, could be configured to employ different physical directories for storing different databases (see Section 7.6.1, “Using Symbolic Links”, for an explanation of how this is done).

Partitioning takes this notion a step further, by allowing you to distribute portions of individual tables across a file system according to rules which you can set largely as needed. In effect, different portions of a table are stored as separate tables in different locations. The user-selected rule by which the division of data is accomplished is known as a partitioning function, which in MySQL can be the modulus, simple matching against a set of ranges or value lists, an internal hashing function, or a linear hashing function. The function is selected according to the partitioning type specified by the user, and takes as its parameter the value of a user-supplied expression. This expression can be either an integer column value, or a function acting on one or more column values and returning an integer. The value of this expression is passed to the partitioning function, which returns an integer value representing the number of the partition in which that particular record should be stored. This function must be nonconstant and nonrandom. It may not contain any queries, but may use an SQL expression that is valid in MySQL, as long as that expression returns either NULL or an integer intval such that

-MAXVALUE <= intval <= MAXVALUE

(MAXVALUE is used to represent the least upper bound for the type of integer in question. -MAXVALUE represents the greatest lower bound.) There are some additional restrictions on partitioning functions; see Section 17.5, “Restrictions and Limitations on Partitioning”, for more information about these.

Examples of partitioning functions can be found in the discussions of partitioning types later in this chapter (see Section 17.2, “Partition Types”), as well as in the partitioning syntax descriptions given in Section 12.1.14, “CREATE TABLE Syntax”.

This is known as horizontal partitioning — that is, different rows of a table may be assigned to different physical partitions. MySQL 6.0 does not support vertical partitioning, in which different columns of a table are assigned to different physical partitions. There are not at this time any plans to introduce vertical partitioning into MySQL 6.0.

For creating partitioned tables, you can use most storage engines that are supported by your MySQL server; the MySQL partitioning engine runs in a separate layer and can interact with any of these. In MySQL 6.0, all partitions of the same partitioned table must use the same storage engine; for example, you cannot use MyISAM for one partition and InnoDB for another. However, there is nothing preventing you from using different storage engines for different partitioned tables on the same MySQL server or even in the same database.

Note

MySQL partitioning cannot be used with the MERGE or CSV storage engines.

To employ a particular storage engine for a partitioned table, it is necessary only to use the [STORAGE] ENGINE option just as you would for a nonpartitioned table. However, you should keep in mind that [STORAGE] ENGINE (and other table options) need to be listed before any partitioning options are used in a CREATE TABLE statement. This example shows how to create a table that is partitioned by hash into 6 partitions and which uses the InnoDB storage engine:

CREATE TABLE ti (id INT, amount DECIMAL(7,2), tr_date DATE)
    ENGINE=INNODB
    PARTITION BY HASH( MONTH(tr_date) )
    PARTITIONS 6;

Note

Each PARTITION clause can include a [STORAGE] ENGINE option, but in MySQL 6.0 this has no effect.

Important

Partitioning applies to all data and indexes of a table; you cannot partition only the data and not the indexes, or vice versa, nor can you partition only a portion of the table.

Data and indexes for each partition can be assigned to a specific directory using the DATA DIRECTORY and INDEX DIRECTORY options for the PARTITION clause of the CREATE TABLE statement used to create the partitioned table.

Note

The DATA DIRECTORY and INDEX DIRECTORY options have no effect when defining partitions for tables using the InnoDB storage engine.

DATA DIRECTORY and INDEX DIRECTORY are not supported for individual partitions or subpartitions on Windows. Beginning with MySQL 6.0.5, these options are ignored on Windows, except that a warning is generated. (Bug#30459)

In addition, MAX_ROWS and MIN_ROWS can be used to determine the maximum and minimum numbers of rows, respectively, that can be stored in each partition. See Section 17.3, “Partition Management”, for more information on these options.

Some of the advantages of partitioning include:

  • Being able to store more data in one table than can be held on a single disk or file system partition.

  • Data that loses its usefulness can often be easily be removed from the table by dropping the partition containing only that data. Conversely, the process of adding new data can in some cases be greatly facilitated by adding a new partition specifically for that data.

  • Some queries can be greatly optimized in virtue of the fact that data satisfying a given WHERE clause can be stored only on one or more partitions, thereby excluding any remaining partitions from the search. Because partitions can be altered after a partitioned table has been created, you can reorganize your data to enhance frequent queries that may not have been so when the partitioning scheme was first set up. This capability is sometimes referred to as partition pruning. For more information, see Section 17.4, “Partition Pruning”.

Other benefits usually associated with partitioning include those in the following list. These features are not currently implemented in MySQL Partitioning, but are high on our list of priorities.

  • Queries involving aggregate functions such as SUM() and COUNT() can easily be parallelized. A simple example of such a query might be SELECT salesperson_id, COUNT(orders) as order_total FROM sales GROUP BY salesperson_id;. By “parallelized,” we mean that the query can be run simultaneously on each partition, and the final result obtained merely by summing the results obtained for all partitions.

  • Achieving greater query throughput in virtue of spreading data seeks over multiple disks.

Be sure to check this section and chapter frequently for updates as Partitioning development continues.

17.2. Partition Types

This section discusses the types of partitioning which are available in MySQL 6.0. These include:

  • RANGE partitioning: Assigns rows to partitions based on column values falling within a given range. See Section 17.2.1, “RANGE Partitioning”.

  • LIST partitioning: Similar to partitioning by range, except that the partition is selected based on columns matching one of a set of discrete values. See Section 17.2.2, “LIST Partitioning”.

  • HASH partitioning: A partition is selected based on the value returned by a user-defined expression that operates on column values in rows to be inserted into the table. The function may consist of any expression valid in MySQL that yields a nonnegative integer value. See Section 17.2.3, “HASH Partitioning”.

  • KEY partitioning: Similar to partitioning by hash, except that only one or more columns to be evaluated are supplied, and the MySQL server provides its own hashing function. These columns can contain other than integer values, since the hashing function supplied by MySQL guarantees an integer result regardless of the column data type. See Section 17.2.4, “KEY Partitioning”.

A very common use of database partitioning is to segregate data by date. Some database systems support explicit date partitioning, which MySQL does not implement in 6.0. However, it is not difficult in MySQL to create partitioning schemes based on DATE, TIME, or DATETIME columns, or based on expressions making use of such columns.

When partitioning by KEY or LINEAR KEY, you can use a DATE, TIME, or DATETIME column as the partitioning column without performing any modification of the column value. For example, this table creation statement is perfectly valid in MySQL:

CREATE TABLE members (
    firstname VARCHAR(25) NOT NULL,
    lastname VARCHAR(25) NOT NULL,
    username VARCHAR(16) NOT NULL,
    email VARCHAR(35),
    joined DATE NOT NULL
)
PARTITION BY KEY(joined)
PARTITIONS 6;

MySQL's other partitioning types, however, require a partitioning expression that yields an integer value or NULL. If you wish to use date-based partitioning by RANGE, LIST, HASH, or LINEAR HASH, you can simply employ a function that operates on a DATE, TIME, or DATETIME column and returns such a value, as shown here:

CREATE TABLE members (
    firstname VARCHAR(25) NOT NULL,
    lastname VARCHAR(25) NOT NULL,
    username VARCHAR(16) NOT NULL,
    email VARCHAR(35),
    joined DATE NOT NULL
)
PARTITION BY RANGE( YEAR(joined) ) (
    PARTITION p0 VALUES LESS THAN (1960),
    PARTITION p1 VALUES LESS THAN (1970),
    PARTITION p2 VALUES LESS THAN (1980),
    PARTITION p3 VALUES LESS THAN (1990),
    PARTITION p4 VALUES LESS THAN MAXVALUE
);

Additional examples of partitioning using dates may be found here:

For more complex examples of date-based partitioning, see:

MySQL partitioning is optimized for use with the TO_DAYS() and YEAR() functions. However, you can use other date and time functions that return an integer or NULL, such as WEEKDAY(), DAYOFYEAR(), or MONTH(). See Section 11.6, “Date and Time Functions”, for more information about such functions.

It is important to remember — regardless of the type of partitioning that you use — that partitions are always numbered automatically and in sequence when created, starting with 0. When a new row is inserted into a partitioned table, it is these partition numbers that are used in identifying the correct partition. For example, if your table uses 4 partitions, these partitions are numbered 0, 1, 2, and 3. For the RANGE and LIST partitioning types, it is necessary to ensure that there is a partition defined for each partition number. For HASH partitioning, the user function employed must return an integer value greater than 0. For KEY partitioning, this issue is taken care of automatically by the hashing function which the MySQL server employs internally.

Names of partitions generally follow the rules governing other MySQL identifiers, such as those for tables and databases. However, you should note that partition names are not case-sensitive. For example, the following CREATE TABLE statement fails as shown:

mysql> CREATE TABLE t2 (val INT)
    -> PARTITION BY LIST(val)(
    ->     PARTITION mypart VALUES IN (1,3,5),
    ->     PARTITION MyPart VALUES IN (2,4,6)
    -> );
ERROR 1488 (HY000): Duplicate partition name mypart

Failure occurs because MySQL sees no difference between the partition names mypart and MyPart.

When you specify the number of partitions for the table, this must be expressed as a positive, nonzero integer literal with no leading zeroes, and may not be an expression such as 0.8E+01 or 6-2, even if it evaluates to an integer value. Decimal fractions are not allowed.

In the sections that follow, we do not necessarily provide all possible forms for the syntax that can be used for creating each partition type; this information may be found in Section 12.1.14, “CREATE TABLE Syntax”.

17.2.1. RANGE Partitioning

A table that is partitioned by range is partitioned in such a way that each partition contains rows for which the partitioning expression value lies within a given range. Ranges should be contiguous but not overlapping, and are defined using the VALUES LESS THAN operator. For the next few examples, suppose that you are creating a table such as the following to hold personnel records for a chain of 20 video stores, numbered 1 through 20:

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 NOT NULL,
    store_id INT NOT NULL
);

This table can be partitioned by range in a number of ways, depending on your needs. One way would be to use the store_id column. For instance, you might decide to partition the table 4 ways by adding a PARTITION BY RANGE clause as 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 NOT NULL,
    store_id INT NOT NULL
)
PARTITION BY RANGE (store_id) (
    PARTITION p0 VALUES LESS THAN (6),
    PARTITION p1 VALUES LESS THAN (11),
    PARTITION p2 VALUES LESS THAN (16),
    PARTITION p3 VALUES LESS THAN (21)
);

In this partitioning scheme, all rows corresponding to employees working at stores 1 through 5 are stored in partition p0, to those employed at stores 6 through 10 are stored in partition p1, and so on. Note that each partition is defined in order, from lowest to highest. This is a requirement of the PARTITION BY RANGE syntax; you can think of it as being analogous to a series of if ... elseif ... statements in C or Java in this regard.

It is easy to determine that a new row containing the data (72, 'Michael', 'Widenius', '1998-06-25', NULL, 13) is inserted into partition p2, but what happens when your chain adds a 21st store? Under this scheme, there is no rule that covers a row whose store_id is greater than 20, so an error results because the server does not know where to place it. You can keep this from occurring by using a “catchallVALUES LESS THAN clause in the CREATE TABLE statement that provides for all values greater than highest value explicitly named:

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 NOT NULL,
    store_id INT NOT NULL
)
PARTITION BY RANGE (store_id) (
    PARTITION p0 VALUES LESS THAN (6),
    PARTITION p1 VALUES LESS THAN (11),
    PARTITION p2 VALUES LESS THAN (16),
    PARTITION p3 VALUES LESS THAN MAXVALUE
);

Note

Another way to avoid an error when no matching value is found is to use the IGNORE keyword as part of the INSERT statement. For an example, see Section 17.2.2, “LIST Partitioning”. Also see Section 12.2.5, “INSERT Syntax”, for general information about IGNORE.

MAXVALUE represents an integer value that is always greater than the largest possible integer value (in mathematical language, it serves as a least upper bound). Now, any rows whose store_id column value is greater than or equal to 16 (the highest value defined) are stored in partition p3. At some point in the future — when the number of stores has increased to 25, 30, or more — you can use an ALTER TABLE statement to add new partitions for stores 21-25, 26-30, and so on (see Section 17.3, “Partition Management”, for details of how to do this).

In much the same fashion, you could partition the table based on employee job codes — that is, based on ranges of job_code column values. For example — assuming that two-digit job codes are used for regular (in-store) workers, three-digit codes are used for office and support personnel, and four-digit codes are used for management positions — you could create the partitioned table using the following:

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 NOT NULL,
    store_id INT NOT NULL
)
PARTITION BY RANGE (job_code) (
    PARTITION p0 VALUES LESS THAN (100),
    PARTITION p1 VALUES LESS THAN (1000),
    PARTITION p2 VALUES LESS THAN (10000)
);

In this instance, all rows relating to in-store workers would be stored in partition p0, those relating to office and support staff in p1, and those relating to managers in partition p2.

It is also possible to use an expression in VALUES LESS THAN clauses. However, MySQL must be able to evaluate the expression's return value as part of a LESS THAN (<) comparison.

Rather than splitting up the table data according to store number, you can use an expression based on one of the two DATE columns instead. For example, let us suppose that you wish to partition based on the year that each employee left the company; that is, the value of YEAR(separated). An example of a CREATE TABLE statement that implements such a partitioning scheme is 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 BY RANGE ( YEAR(separated) ) (
    PARTITION p0 VALUES LESS THAN (1991),
    PARTITION p1 VALUES LESS THAN (1996),
    PARTITION p2 VALUES LESS THAN (2001),
    PARTITION p3 VALUES LESS THAN MAXVALUE
);

In this scheme, for all employees who left before 1991, the rows are stored in partition p0; for those who left in the years 1991 through 1995, in p1; for those who left in the years 1996 through 2000, in p2; and for any workers who left after the year 2000, in p3.

Range partitioning is particularly useful when:

  • You want or need to delete “old” data. If you are using the partitioning scheme shown immediately above, you can simply use ALTER TABLE employees DROP PARTITION p0; to delete all rows relating to employees who stopped working for the firm prior to 1991. (See Section 12.1.6, “ALTER TABLE Syntax”, and Section 17.3, “Partition Management”, for more information.) For a table with a great many rows, this can be much more efficient than running a DELETE query such as DELETE FROM employees WHERE YEAR(separated) <= 1990;.

  • You want to use a column containing date or time values, or containing values arising from some other series.

  • You frequently run queries that depend directly on the column used for partitioning the table. For example, when executing a query such as EXPLAIN PARTITIONS SELECT COUNT(*) FROM employees WHERE separated BETWEEN '2000-01-01' AND '2000-12-31' GROUP BY store_id;, MySQL can quickly determine that only partition p2 needs to be scanned because the remaining partitions cannot contain any records satisfying the WHERE clause. See Section 17.4, “Partition Pruning”, for more information about how this is accomplished.

17.2.2. 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 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.

Note

In MySQL 6.0, it is possible to match against only a list of integers (and possibly NULL — see Section 17.2.6, “How MySQL Partitioning Handles NULL) when partitioning by LIST.

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 12.1.14, “CREATE TABLE Syntax”.

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 17.2.1, “RANGE Partitioning”.)

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

RegionStore ID Numbers
North3, 5, 6, 9, 17
East1, 2, 10, 11, 19, 20
West4, 12, 13, 14, 18
Central7, 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 BY LIST(store_id) (
    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. All rows relating to employees working at stores in that region can be deleted with the query ALTER TABLE employees DROP 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);.

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 17.2.5, “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, any rows coming before the row containing the unmatched value are inserted, but any coming after it are not:

mysql> SELECT * FROM h2;
Empty set (0.00 sec)

mysql> INSERT INTO h2 VALUES (4, 7), (3, 5), (6, 0);
ERROR 1525 (HY000): Table has no partition for value 3
mysql> SELECT * FROM h2;
+------+------+
| c1   | c2   |
+------+------+
|    4 |    7 |
+------+------+
1 row in set (0.00 sec)

You can cause this type of error to be ignored by using the IGNORE key word. If you do so, rows containing unmatched partitioning column values are not inserted, but any rows with matching values are inserted, and no errors are reported:

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

mysql> SELECT * FROM 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 (0.00 sec)
Records: 5  Duplicates: 2  Warnings: 0

mysql> SELECT * FROM h2;
+------+------+
| c1   | c2   |
+------+------+
|    7 |    5 |
|    1 |    9 |
|    2 |    5 |
+------+------+
3 rows in set (0.00 sec)

17.2.3. HASH Partitioning

Partitioning by HASH is used primarily to ensure an even distribution of data among a predetermined number of partitions. With range or list partitioning, you must specify explicitly into which partition a given column value or set of column values is to be stored; with hash partitioning, MySQL takes care of this for you, and you need only specify a column value or expression based on a column value to be hashed and the number of partitions into which the partitioned table is to be divided.

To partition a table using HASH partitioning, it is necessary to append to the CREATE TABLE statement a PARTITION BY HASH (expr) clause, where expr is an expression that returns an integer. This can simply be the name of a column whose type is one of MySQL's integer types. In addition, you will most likely want to follow this with a PARTITIONS num clause, where num is a positive integer representing the number of partitions into which the table is to be divided.

For example, the following statement creates a table that uses hashing on the store_id column and is divided into 4 partitions:

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 BY HASH(store_id)
PARTITIONS 4;

If you do not include a PARTITIONS clause, the number of partitions defaults to 1.

Using the PARTITIONS keyword without a number following it results in a syntax error.

You can also use an SQL expression that returns an integer for expr. For instance, you might want to partition based on the year in which an employee was hired. This can be done as 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 BY HASH( YEAR(hired) )
PARTITIONS 4;

expr must return a nonconstant, nonrandom integer value (in other words, it should be varying but deterministic), and must not contain any prohibited constructs as described in Section 17.5, “Restrictions and Limitations on Partitioning”. You should also keep in mind that this expression is evaluated each time a row is inserted or updated (or possibly deleted); this means that very complex expressions may give rise to performance issues, particularly when performing operations (such as batch inserts) that affect a great many rows at one time.

The most efficient hashing function is one which operates upon a single table column and whose value increases or decreases consistently with the column value, as this allows for “pruning” on ranges of partitions. That is, the more closely that the expression varies with the value of the column on which it is based, the more efficiently MySQL can use the expression for hash partitioning.

For example, where date_col is a column of type DATE, then the expression TO_DAYS(date_col) is said to vary directly with the value of date_col, because for every change in the value of date_col, the value of the expression changes in a consistent manner. The variance of the expression YEAR(date_col) with respect to date_col is not quite as direct as that of TO_DAYS(date_col), because not every possible change in date_col produces an equivalent change in YEAR(date_col). Even so, YEAR(date_col) is a good candidate for a hashing function, because it varies directly with a portion of date_col and there is no possible change in date_col that produces a disproportionate change in YEAR(date_col).

By way of contrast, suppose that you have a column named int_col whose type is INT. Now consider the expression POW(5-int_col,3) + 6. This would be a poor choice for a hashing function because a change in the value of int_col is not guaranteed to produce a proportional change in the value of the expression. Changing the value of int_col by a given amount can produce by widely different changes in the value of the expression. For example, changing int_col from 5 to 6 produces a change of -1 in the value of the expression, but changing the value of int_col from 6 to 7 produces a change of -7 in the expression value.

In other words, the more closely the graph of the column value versus the value of the expression follows a straight line as traced by the equation y=nx where n is some nonzero constant, the better the expression is suited to hashing. This has to do with the fact that the more nonlinear an expression is, the more uneven the distribution of data among the partitions it tends to produce.

In theory, pruning is also possible for expressions involving more than one column value, but determining which of such expressions are suitable can be quite difficult and time-consuming. For this reason, the use of hashing expressions involving multiple columns is not particularly recommended.

When PARTITION BY HASH is used, MySQL determines which partition of num partitions to use based on the modulus of the result of the user function. In other words, for an expression expr, the partition in which the record is stored is partition number N, where N = MOD(expr, num). For example, suppose table t1 is defined as follows, so that it has 4 partitions:

CREATE TABLE t1 (col1 INT, col2 CHAR(5), col3 DATE)
    PARTITION BY HASH( YEAR(col3) )
    PARTITIONS 4;

If you insert a record into t1 whose col3 value is '2005-09-15', then the partition in which it is stored is determined as follows:

MOD(YEAR('2005-09-01'),4)
=  MOD(2005,4)
=  1

MySQL 6.0 also supports a variant of HASH partitioning known as linear hashing which employs a more complex algorithm for determining the placement of new rows inserted into the partitioned table. See Section 17.2.3.1, “LINEAR HASH Partitioning”, for a description of this algorithm.

The user function is evaluated each time a record is inserted or updated. It may also — depending on the circumstances — be evaluated when records are deleted.

Note

If a table to be partitioned has a UNIQUE key, then any columns supplied as arguments to the HASH user function or to the KEY's column_list must be part of that key.

17.2.3.1. LINEAR HASH Partitioning

MySQL also supports linear hashing, which differs from regular hashing in that linear hashing utilizes a linear powers-of-two algorithm whereas regular hashing employs the modulus of the hashing function's value.

Syntactically, the only difference between linear-hash partitioning and regular hashing is the addition of the LINEAR keyword in the PARTITION BY clause, as 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 BY LINEAR HASH( YEAR(hired) )
PARTITIONS 4;

Given an expression expr, the partition in which the record is stored when linear hashing is used is partition number N from among num partitions, where N is derived according to the following algorithm:

  1. Find the next power of 2 greater than num. We call this value V; it can be calculated as:

    V = POWER(2, CEILING(LOG(2, num)))
    

    (For example, suppose that num is 13. Then LOG(2,13) is 3.7004397181411. CEILING(3.7004397181411) is 4, and V = POWER(2,4), which is 16.)

  2. Set N = F(column_list) & (V - 1).

  3. While N >= num:

    • Set V = CEIL(V / 2)

    • Set N = N & (V - 1)

For example, suppose that the table t1, using linear hash partitioning and having 6 partitions, is created using this statement:

CREATE TABLE t1 (col1 INT, col2 CHAR(5), col3 DATE)
    PARTITION BY LINEAR HASH( YEAR(col3) )
    PARTITIONS 6;

Now assume that you want to insert two records into t1 having the col3 column values '2003-04-14' and '1998-10-19'. The partition number for the first of these is determined as follows:

V = POWER(2, CEILING( LOG(2,6) )) = 8
N = YEAR('2003-04-14') & (8 - 1)
   = 2003 & 7
   = 3

(3 >= 6 is FALSE: record stored in partition #3)

The number of the partition where the second record is stored is calculated as shown here:

V = 8
N = YEAR('1998-10-19') & (8-1)
  = 1998 & 7
  = 6

(6 >= 6 is TRUE: additional step required)

N = 6 & CEILING(8 / 2)
  = 6 & 3
  = 2

(2 >= 6 is FALSE: record stored in partition #2)

The advantage in partitioning by linear hash is that the adding, dropping, merging, and splitting of partitions is made much faster, which can be beneficial when dealing with tables containing extremely large amounts (terabytes) of data. The disadvantage is that data is less likely to be evenly distributed between partitions as compared with the distribution obtained using regular hash partitioning.

17.2.4. KEY Partitioning

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. This function 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 that:

  • KEY is used rather than HASH.

  • KEY takes only a list of one or more column names. The column or columns used as the partitioning key must comprise part or all of the table's primary key, if the table has one.

    KEY takes a list of zero or more column names. 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 6.0:

    CREATE TABLE k1 (
        id INT NOT NULL PRIMARY KEY,
        name VARCHAR(20)
    )
    PARTITION BY KEY()
    PARTITIONS 2;
    

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

    CREATE TABLE k1 (
        id INT NOT NULL,
        name VARCHAR(20),
        UNIQUE KEY (id)
    )
    PARTITION BY KEY()
    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:

    CREATE TABLE tm1 (
        s1 CHAR(32) PRIMARY KEY
    )
    PARTITION BY KEY(s1)
    PARTITIONS 10;
    

    The preceding statement would not be valid, were a different partitioning type to be specified.

    Note

    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 17.5, “Restrictions and Limitations on Partitioning”.

    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.

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

CREATE TABLE tk (
    col1 INT NOT NULL,
    col2 CHAR(5),
    col3 DATE
)
PARTITION BY LINEAR KEY (col1)
PARTITIONS 3;

Using LINEAR 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 17.2.3.1, “LINEAR HASH Partitioning”, for a description of this algorithm and its implications.

17.2.5. Subpartitioning

Subpartitioning — also known as composite partitioning — is the further division of each partition in a partitioned table. For example, consider the following CREATE TABLE statement:

CREATE TABLE ts (id INT, purchased DATE)
    PARTITION BY RANGE( YEAR(purchased) )
    SUBPARTITION BY HASH( TO_DAYS(purchased) )
    SUBPARTITIONS 2 (
        PARTITION p0 VALUES LESS THAN (1990),
        PARTITION p1 VALUES LESS THAN (2000),
        PARTITION p2 VALUES LESS THAN MAXVALUE
    );

Table ts has 3 RANGE partitions. Each of these partitions — p0, p1, and p2 — is further divided into 2 subpartitions. In effect, the entire table is divided into 3 * 2 = 6 partitions. However, due to the action of the PARTITION BY RANGE clause, the first 2 of these store only those records with a value less than 1990 in the purchased column.

In MySQL 6.0, it is possible to subpartition tables that are partitioned by RANGE or LIST. Subpartitions may use either HASH or KEY partitioning. This is also known as composite partitioning.

It is also possible to define subpartitions explicitly using SUBPARTITION clauses to specify options for individual subpartitions. For example, a more verbose fashion of creating the same table ts as shown in the previous example would be:

CREATE TABLE ts (id INT, purchased DATE)
    PARTITION BY RANGE( YEAR(purchased) )
    SUBPARTITION BY HASH( TO_DAYS(purchased) ) (
        PARTITION p0 VALUES LESS THAN (1990) (
            SUBPARTITION s0,
            SUBPARTITION s1
        ),
        PARTITION p1 VALUES LESS THAN (2000) (
            SUBPARTITION s2,
            SUBPARTITION s3
        ),
        PARTITION p2 VALUES LESS THAN MAXVALUE (
            SUBPARTITION s4,
            SUBPARTITION s5
        )
    );

Some syntactical items of note:

  • Each partition must have the same number of subpartitions.

  • If you explicitly define any subpartitions using SUBPARTITION on any partition of a partitioned table, you must define them all. In other words, the following statement will fail:

    CREATE TABLE ts (id INT, purchased DATE)
        PARTITION BY RANGE( YEAR(purchased) )
        SUBPARTITION BY HASH( TO_DAYS(purchased) ) (
            PARTITION p0 VALUES LESS THAN (1990) (
                SUBPARTITION s0,
                SUBPARTITION s1
            ),
            PARTITION p1 VALUES LESS THAN (2000),
            PARTITION p2 VALUES LESS THAN MAXVALUE (
                SUBPARTITION s2,
                SUBPARTITION s3
            )
        );
    

    This statement would still fail even if it included a SUBPARTITIONS 2 clause.

  • Each SUBPARTITION clause must include (at a minimum) a name for the subpartition. Otherwise, you may set any desired option for the subpartition or allow it to assume its default setting for that option.

  • Subpartition names must be unique across the entire table. For example, the following CREATE TABLE statement is valid in MySQL 6.0:

    CREATE TABLE ts (id INT, purchased DATE)
        PARTITION BY RANGE( YEAR(purchased) )
        SUBPARTITION BY HASH( TO_DAYS(purchased) ) (
            PARTITION p0 VALUES LESS THAN (1990) (
                SUBPARTITION s0,
                SUBPARTITION s1
            ),
            PARTITION p1 VALUES LESS THAN (2000) (
                SUBPARTITION s2,
                SUBPARTITION s3
            ),
            PARTITION p2 VALUES LESS THAN MAXVALUE (
                SUBPARTITION s4,
                SUBPARTITION s5
            )
        );
    

Subpartitions can be used with especially large tables to distribute data and indexes across many disks. Suppose that you have 6 disks mounted as /disk0, /disk1, /disk2, and so on. Now consider the following example:

CREATE TABLE ts (id INT, purchased DATE)
    PARTITION BY RANGE( YEAR(purchased) )
    SUBPARTITION BY HASH( TO_DAYS(purchased) ) (
        PARTITION p0 VALUES LESS THAN (1990) (
            SUBPARTITION s0
                DATA DIRECTORY = '/disk0/data'
                INDEX DIRECTORY = '/disk0/idx',
            SUBPARTITION s1
                DATA DIRECTORY = '/disk1/data'
                INDEX DIRECTORY = '/disk1/idx'
        ),
        PARTITION p1 VALUES LESS THAN (2000) (
            SUBPARTITION s2
                DATA DIRECTORY = '/disk2/data'
                INDEX DIRECTORY = '/disk2/idx',
            SUBPARTITION s3
                DATA DIRECTORY = '/disk3/data'
                INDEX DIRECTORY = '/disk3/idx'
        ),
        PARTITION p2 VALUES LESS THAN MAXVALUE (
            SUBPARTITION s4
                DATA DIRECTORY = '/disk4/data'
                INDEX DIRECTORY = '/disk4/idx',
            SUBPARTITION s5
                DATA DIRECTORY = '/disk5/data'
                INDEX DIRECTORY = '/disk5/idx'
        )
    );

In this case, a separate disk is used for the data and for the indexes of each RANGE. Many other variations are possible; another example might be:

CREATE TABLE ts (id INT, purchased DATE)
    PARTITION BY RANGE(YEAR(purchased))
    SUBPARTITION BY HASH( TO_DAYS(purchased) ) (
        PARTITION p0 VALUES LESS THAN (1990) (
            SUBPARTITION s0a
                DATA DIRECTORY = '/disk0'
                INDEX DIRECTORY = '/disk1',
            SUBPARTITION s0b
                DATA DIRECTORY = '/disk2'
                INDEX DIRECTORY = '/disk3'
        ),
        PARTITION p1 VALUES LESS THAN (2000) (
            SUBPARTITION s1a
                DATA DIRECTORY = '/disk4/data'
                INDEX DIRECTORY = '/disk4/idx',
            SUBPARTITION s1b
                DATA DIRECTORY = '/disk5/data'
                INDEX DIRECTORY = '/disk5/idx'
        ),
        PARTITION p2 VALUES LESS THAN MAXVALUE (
            SUBPARTITION s2a,
            SUBPARTITION s2b
        )
    );

Here, the storage is as follows:

  • Rows with purchased dates from before 1990 take up a vast amount of space, so are split up 4 ways, with a separate disk dedicated to the data and to the indexes for each of the two subpartitions (s0a and s0b) making up partition p0. In other words:

    • The data for subpartition s0a is stored on /disk0.

    • The indexes for subpartition s0a are stored on /disk1.

    • The data for subpartition s0b is stored on /disk2.

    • The indexes for subpartition s0b are stored on /disk3.

  • Rows containing dates ranging from 1990 to 1999 (partition p1) do not require as much room as those from before 1990. These are split between 2 disks (/disk4 and /disk5) rather than 4 disks as with the legacy records stored in p0:

    • Data and indexes belonging to p1's first subpartition (s1a) are stored on /disk4 — the data in /disk4/data, and the indexes in /disk4/idx.

    • Data and indexes belonging to p1's second subpartition (s1b) are stored on /disk5 — the data in /disk5/data, and the indexes in /disk5/idx.

  • Rows reflecting dates from the year 2000 to the present (partition p2) do not take up as much space as required by either of the two previous ranges. Currently, it is sufficient to store all of these in the default location.

    In future, when the number of purchases for the decade beginning with the year 2000 grows to a point where the default location no longer provides sufficient space, the corresponding rows can be moved using an ALTER TABLE ... REORGANIZE PARTITION statement. See Section 17.3, “Partition Management”, for an explanation of how this can be done.

The DATA DIRECTORY and INDEX DIRECTORY options are disallowed when the NO_DIR_IN_CREATE server SQL mode is in effect. This is true for partitions and subpartitions.

17.2.6. How MySQL Partitioning Handles NULL

Partitioning in MySQL does nothing to disallow NULL as the value of a partitioning expression, whether it is a column value or the value of a user-supplied expression. Even though it is permitted to use NULL as the value of an expression that must otherwise yield an integer, it is important to keep in mind that NULL is not a number. MySQL's partitioning implementation treats NULL as being less than any non-NULL value, just as ORDER BY does.

This means that treatment of NULL varies between partitioning of different types, and may produce behavior which you do not expect if you are not prepared for it. This being the case, we discuss in this section how each MySQL partitioning type handles NULL values when determining the partition in which a row should be stored, and provide examples for each.

Handling of NULL with RANGE partitioning.  If you insert a row into a table partitioned by RANGE such that the column value used to determine the partition is NULL, the row is inserted into the lowest partition. For example, consider these two tables in a database named p, created as follows:

mysql> CREATE TABLE t1 (
    ->     c1 INT,
    ->     c2 VARCHAR(20)
    -> )
    -> PARTITION BY RANGE(c1) (
    ->     PARTITION p0 VALUES LESS THAN (0),
    ->     PARTITION p1 VALUES LESS THAN (10),
    ->     PARTITION p2 VALUES LESS THAN MAXVALUE
    -> );
Query OK, 0 rows affected (0.09 sec)

mysql> CREATE TABLE t2 (
    ->     c1 INT,
    ->     c2 VARCHAR(20)
    -> )
    -> PARTITION BY RANGE(c1) (
    ->     PARTITION p0 VALUES LESS THAN (-5),
    ->     PARTITION p1 VALUES LESS THAN (0),
    ->     PARTITION p2 VALUES LESS THAN (10),
    ->     PARTITION p3 VALUES LESS THAN MAXVALUE
    -> );
Query OK, 0 rows affected (0.09 sec)

You can see the partitions created by these two CREATE TABLE statements using the following query against the PARTITIONS table in the INFORMATION_SCHEMA database:

mysql> SELECT TABLE_NAME, PARTITION_NAME, TABLE_ROWS, AVG_ROW_LENGTH, DATA_LENGTH
     >   FROM INFORMATION_SCHEMA.PARTITIONS
     >   WHERE TABLE_SCHEMA = 'p' AND TABLE_NAME LIKE 't_';
+------------+----------------+------------+----------------+-------------+
| TABLE_NAME | PARTITION_NAME | TABLE_ROWS | AVG_ROW_LENGTH | DATA_LENGTH |
+------------+----------------+------------+----------------+-------------+
| t1         | p0             |          0 |              0 |           0 |
| t1         | p1             |          0 |              0 |           0 |
| t1         | p2             |          0 |              0 |           0 |
| t2         | p0             |          0 |              0 |           0 |
| t2         | p1             |          0 |              0 |           0 |
| t2         | p2             |          0 |              0 |           0 |
| t2         | p3             |          0 |              0 |           0 |
+------------+----------------+------------+----------------+-------------+
7 rows in set (0.00 sec)

(For more information about this table, see Section 19.19, “The INFORMATION_SCHEMA PARTITIONS Table”.) Now let us populate each of these tables with a single row containing a NULL in the column used as the partitioning key, and verify that the rows were inserted using a pair of SELECT statements:

mysql> INSERT INTO t1 VALUES (NULL, 'mothra');
Query OK, 1 row affected (0.00 sec)

mysql> INSERT INTO t2 VALUES (NULL, 'mothra');
Query OK, 1 row affected (0.00 sec)

mysql> SELECT * FROM t1;
+------+--------+
| id   | name   |
+------+--------+
| NULL | mothra |
+------+--------+
1 row in set (0.00 sec)

mysql> SELECT * FROM t2;
+------+--------+
| id   | name   |
+------+--------+
| NULL | mothra |
+------+--------+
1 row in set (0.00 sec)

You can see which partitions are used to store the inserted rows by rerunning the previous query against INFORMATION_SCHEMA.PARTITIONS and inspecting the output:

mysql> SELECT TABLE_NAME, PARTITION_NAME, TABLE_ROWS, AVG_ROW_LENGTH, DATA_LENGTH
     >   FROM INFORMATION_SCHEMA.PARTITIONS
     >   WHERE TABLE_SCHEMA = 'p' AND TABLE_NAME LIKE 't_';
+------------+----------------+------------+----------------+-------------+
| TABLE_NAME | PARTITION_NAME | TABLE_ROWS | AVG_ROW_LENGTH | DATA_LENGTH |
+------------+----------------+------------+----------------+-------------+
| t1         | p0             |          1 |             20 |          20 |
| t1         | p1             |          0 |              0 |           0 |
| t1         | p2             |          0 |              0 |           0 |
| t2         | p0             |          1 |             20 |          20 |
| t2         | p1             |          0 |              0 |           0 |
| t2         | p2             |          0 |              0 |           0 |
| t2         | p3             |          0 |              0 |           0 |
+------------+----------------+------------+----------------+-------------+
7 rows in set (0.01 sec)

You can also demonstrate that these rows were stored in the lowest partition of each table by dropping these partitions, and then re-running the SELECT statements:

mysql> ALTER TABLE t1 DROP PARTITION p0;
Query OK, 0 rows affected (0.16 sec)

mysql> ALTER TABLE t2 DROP PARTITION p0;
Query OK, 0 rows affected (0.16 sec)

mysql> SELECT * FROM t1;
Empty set (0.00 sec)

mysql> SELECT * FROM t2;
Empty set (0.00 sec)

(For more information on ALTER TABLE ... DROP PARTITION, see Section 12.1.6, “ALTER TABLE Syntax”.)

NULL is also treated in this way for partitioning expressions that use SQL functions. Suppose that we define a table using a CREATE TABLE statement such as this one:

CREATE TABLE tndate (
    id INT,
    dt DATE
)
PARTITION BY RANGE( YEAR(dt) ) (
    PARTITION p0 VALUES LESS THAN (1990),
    PARTITION p1 VALUES LESS THAN (2000),
    PARTITION p2 VALUES LESS THAN MAXVALUE
);

As with other MySQL functions, YEAR(NULL) returns NULL. A row with a dt column value of NULL is treated as though the partitioning expression evaluated to a value less than any other value, and so is inserted into partition p0.

Handling of NULL with LIST partitioning.  A table that is partitioned by LIST admits NULL values if and only if one of its partitions is defined using that value-list that contains NULL. The converse of this is that a table partitioned by LIST which does not explicitly use NULL in a value list rejects rows resulting in a NULL value for the partitioning expression, as shown in this example:

mysql> CREATE TABLE ts1 (
    ->     c1 INT,
    ->     c2 VARCHAR(20)
    -> )
    -> PARTITION BY LIST(c1) (
    ->     PARTITION p0 VALUES IN (0, 3, 6),
    ->     PARTITION p1 VALUES IN (1, 4, 7),
    ->     PARTITION p2 VALUES IN (2, 5, 8)
    -> );
Query OK, 0 rows affected (0.01 sec)

mysql> INSERT INTO ts1 VALUES (9, 'mothra');
ERROR 1504 (HY000): Table has no partition for value 9

mysql> INSERT INTO ts1 VALUES (NULL, 'mothra');
ERROR 1504 (HY000): Table has no partition for value NULL

Only rows having a c1 value between 0 and 8 inclusive can be inserted into ts1. NULL falls outside this range, just like the number 9. We can create tables ts2 and ts3 having value lists containing NULL, as shown here:

mysql> CREATE TABLE ts2 (
    ->     c1 INT,
    ->     c2 VARCHAR(20)
    -> )
    -> PARTITION BY LIST(c1) (
    ->     PARTITION p0 VALUES IN (0, 3, 6),
    ->     PARTITION p1 VALUES IN (1, 4, 7),
    ->     PARTITION p2 VALUES IN (2, 5, 8),
    ->     PARTITION p3 VALUES IN (NULL)
    -> );
Query OK, 0 rows affected (0.01 sec)

mysql> CREATE TABLE ts3 (
    ->     c1 INT,
    ->     c2 VARCHAR(20)
    -> )
    -> PARTITION BY LIST(c1) (
    ->     PARTITION p0 VALUES IN (0, 3, 6),
    ->     PARTITION p1 VALUES IN (1, 4, 7, NULL),
    ->     PARTITION p2 VALUES IN (2, 5, 8)
    -> );
Query OK, 0 rows affected (0.01 sec)

When defining value lists for partitioning, you can (and should) treat NULL just as you would any other value. For example, both VALUES IN (NULL) and VALUES IN (1, 4, 7, NULL) are valid, as are VALUES IN (1, NULL, 4, 7), VALUES IN (NULL, 1, 4, 7), and so on. You can insert a row having NULL for column c1 into each of the tables ts2 and ts3:

mysql> INSERT INTO ts2 VALUES (NULL, 'mothra');
Query OK, 1 row affected (0.00 sec)

mysql> INSERT INTO ts3 VALUES (NULL, 'mothra');
Query OK, 1 row affected (0.00 sec)

By issuing the appropriate query against INFORMATION_SCHEMA.PARTITIONS, you can determine which partitions were used to store the rows just inserted (we assume, as in the previous examples, that the partitioned tables were created in the p database):

mysql> SELECT TABLE_NAME, PARTITION_NAME, TABLE_ROWS, AVG_ROW_LENGTH, DATA_LENGTH
     >   FROM INFORMATION_SCHEMA.PARTITIONS
     >   WHERE TABLE_SCHEMA = 'p' AND TABLE_NAME LIKE 'ts_';
+------------+----------------+------------+----------------+-------------+
| TABLE_NAME | PARTITION_NAME | TABLE_ROWS | AVG_ROW_LENGTH | DATA_LENGTH |
+------------+----------------+------------+----------------+-------------+
| ts2        | p0             |          0 |              0 |           0 |
| ts2        | p1             |          0 |              0 |           0 |
| ts2        | p2             |          0 |              0 |           0 |
| ts2        | p3             |          1 |             20 |          20 |
| ts3        | p0             |          0 |              0 |           0 |
| ts3        | p1             |          1 |             20 |          20 |
| ts3        | p2             |          0 |              0 |           0 |
+------------+----------------+------------+----------------+-------------+
7 rows in set (0.01 sec)

As shown earlier in this section, you can also verify which partitions were used for storing the rows by deleting these partitions and then performing a SELECT.

Handling of NULL with HASH and KEY partitioning.  NULL is handled somewhat differently for tables partitioned by HASH or KEY. In these cases, any partition expression that yields a NULL value is treated as though its return value were zero. We can verify this behavior by examining the effects on the file system of creating a table partitioned by HASH and populating it with a record containing appropriate values. Suppose that you have a table th (also in the p database) created using the following statement:

mysql> CREATE TABLE th (
    ->     c1 INT,
    ->     c2 VARCHAR(20)
    -> )
    -> PARTITION BY HASH(c1)
    -> PARTITIONS 2;
Query OK, 0 rows affected (0.00 sec)

The partitions belonging to this table can be viewed like this:

mysql> SELECT TABLE_NAME,PARTITION_NAME,TABLE_ROWS,AVG_ROW_LENGTH,DATA_LENGTH
     >   FROM INFORMATION_SCHEMA.PARTITIONS
     >   WHERE TABLE_SCHEMA = 'p' AND TABLE_NAME ='th';
+------------+----------------+------------+----------------+-------------+
| TABLE_NAME | PARTITION_NAME | TABLE_ROWS | AVG_ROW_LENGTH | DATA_LENGTH |
+------------+----------------+------------+----------------+-------------+
| th         | p0             |          0 |              0 |           0 |
| th         | p1             |          0 |              0 |           0 |
+------------+----------------+------------+----------------+-------------+
2 rows in set (0.00 sec)

Note that TABLE_ROWS for each partition is 0. Now insert two rows into th whose c1 column values are NULL and 0, and verify that these rows were inserted:

mysql> INSERT INTO th VALUES (NULL, 'mothra'), (0, 'gigan');
Query OK, 1 row affected (0.00 sec)

mysql> SELECT * FROM th;
+------+---------+
| c1   | c2      |
+------+---------+
| NULL | mothra  |
+------+---------+
|    0 | gigan   |
+------+---------+
2 rows in set (0.01 sec)

Recall that for any integer N, the value of NULL MOD N is always NULL. For tables that are partitioned by HASH or KEY, this result is treated for determining the correct partition as 0. Checking the INFORMATION_SCHEMA.PARTITIONS table once again, we can see that both rows were inserted into partition p0:

mysql> SELECT TABLE_NAME, PARTITION_NAME, TABLE_ROWS, AVG_ROW_LENGTH, DATA_LENGTH
     >   FROM INFORMATION_SCHEMA.PARTITIONS
     >   WHERE TABLE_SCHEMA = 'p' AND TABLE_NAME ='th';
+------------+----------------+------------+----------------+-------------+
| TABLE_NAME | PARTITION_NAME | TABLE_ROWS | AVG_ROW_LENGTH | DATA_LENGTH |
+------------+----------------+------------+----------------+-------------+
| th         | p0             |          2 |             20 |          20 |
| th         | p1             |          0 |              0 |           0 |
+------------+----------------+------------+----------------+-------------+
2 rows in set (0.00 sec)

If you repeat this example using PARTITION BY KEY in place of PARTITION BY HASH in the definition of the table, you can verify easily that NULL is also treated like 0 for this type of partitioning as well.

17.3. Partition Management

MySQL 6.0 provides a number of ways to modify partitioned tables. It is possible to add, drop, redefine, merge, or split existing partitions. All of these actions can be carried out using the partitioning extensions to the ALTER TABLE command (see Section 12.1.6, “ALTER TABLE Syntax”, for syntax definitions). There are also ways to obtain information about partitioned tables and partitions. We discuss these topics in the sections that follow.

Note

In MySQL 6.0, all partitions of a partitioned table must have the same number of subpartitions, and it is not possible to change the subpartitioning once the table has been created.

To change a table's partitioning scheme, it is necessary only to use the ALTER TABLE command with a partition_options clause. This clause has the same syntax as that as used with CREATE TABLE for creating a partitioned table, and always begins with the keywords PARTITION BY. For example, suppose that you have a table partitioned by range using the following CREATE TABLE statement:

CREATE TABLE trb3 (id INT, name VARCHAR(50), purchased DATE)
    PARTITION BY RANGE( YEAR(purchased) ) (
        PARTITION p0 VALUES LESS THAN (1990),
        PARTITION p1 VALUES LESS THAN (1995),
        PARTITION p2 VALUES LESS THAN (2000),
        PARTITION p3 VALUES LESS THAN (2005)
    );

To repartition this table so that it is partitioned by key into two partitions using the id column value as the basis for the key, you can use this statement:

ALTER TABLE trb3 PARTITION BY KEY(id) PARTITIONS 2;

This has the same effect on the structure of the table as dropping the table and re-creating it using CREATE TABLE trb3 PARTITION BY KEY(id) PARTITIONS 2;.

ALTER TABLE ... ENGINE = ... changes only the storage engine used by the table, and leaves the table's partitioning scheme intact. Use ALTER TABLE ... REMOVE PARTITIONING to remove a table's partitioning. See Section 12.1.6, “ALTER TABLE Syntax”.

Important

Only a single PARTITION BY, ADD PARTITION, DROP PARTITION, REORGANIZE PARTITION, or COALESCE PARTITION clause can be used in a given ALTER TABLE statement. If you (for example) wish to drop a partition and reorganize a table's remaining partitions, you must do so in two separate ALTER TABLE statements (one using DROP PARTITION and then a second one using REORGANIZE PARITITIONS).

17.3.1. Management of RANGE and LIST Partitions

Range and list partitions are very similar with regard to how the adding and dropping of partitions are handled. For this reason we discuss the management of both sorts of partitioning in this section. For information about working with tables that are partitioned by hash or key, see Section 17.3.2, “Management of HASH and KEY Partitions”. Dropping a RANGE or LIST partition is more straightforward than adding one, so we discuss this first.

Dropping a partition from a table that is partitioned by either RANGE or by LIST can be accomplished using the ALTER TABLE statement with a DROP PARTITION clause. Here is a very basic example, which supposes that you have already created a table which is partitioned by range and then populated with 10 records using the following CREATE TABLE and INSERT statements:

mysql> CREATE TABLE tr (id INT, name VARCHAR(50), purchased DATE)
    ->     PARTITION BY RANGE( YEAR(purchased) ) (
    ->         PARTITION p0 VALUES LESS THAN (1990),
    ->         PARTITION p1 VALUES LESS THAN (1995),
    ->         PARTITION p2 VALUES LESS THAN (2000),
    ->         PARTITION p3 VALUES LESS THAN (2005)
    ->     );
Query OK, 0 rows affected (0.01 sec)

mysql> INSERT INTO tr VALUES
    ->     (1, 'desk organiser', '2003-10-15'),
    ->     (2, 'CD player', '1993-11-05'),
    ->     (3, 'TV set', '1996-03-10'),
    ->     (4, 'bookcase', '1982-01-10'),
    ->     (5, 'exercise bike', '2004-05-09'),
    ->     (6, 'sofa', '1987-06-05'),
    ->     (7, 'popcorn maker', '2001-11-22'),
    ->     (8, 'aquarium', '1992-08-04'),
    ->     (9, 'study desk', '1984-09-16'),
    ->     (10, 'lava lamp', '1998-12-25');
Query OK, 10 rows affected (0.01 sec)

You can see which items should have been inserted into partition p2 as shown here:

mysql> SELECT * FROM tr
    -> WHERE purchased BETWEEN '1995-01-01' AND '1999-12-31';
+------+-----------+------------+
| id   | name      | purchased  |
+------+-----------+------------+
|    3 | TV set    | 1996-03-10 |
|   10 | lava lamp | 1998-12-25 |
+------+-----------+------------+
2 rows in set (0.00 sec)

To drop the partition named p2, execute the following command:

mysql> ALTER TABLE tr DROP PARTITION p2;
Query OK, 0 rows affected (0.03 sec)

It is very important to remember that, when you drop a partition, you also delete all the data that was stored in that partition. You can see that this is the case by re-running the previous SELECT query:

mysql> SELECT * FROM tr WHERE purchased
    -> BETWEEN '1995-01-01' AND '1999-12-31';
Empty set (0.00 sec)

Because of this, you must have the DROP privilege for a table before you can execute ALTER TABLE ... DROP PARTITION on that table.

If you wish to drop all data from all partitions while preserving the table definition and its partitioning scheme, use the TRUNCATE TABLE command. (See Section 12.2.11, “TRUNCATE Syntax”.)

If you intend to change the partitioning of a table without losing data, use ALTER TABLE ... REORGANIZE PARTITION instead. See below or in Section 12.1.6, “ALTER TABLE Syntax”, for information about REORGANIZE PARTITION.

If you now execute a SHOW CREATE TABLE command, you can see how the partitioning makeup of the table has been changed:

mysql> SHOW CREATE TABLE tr\G
*************************** 1. row ***************************
       Table: tr
Create Table: CREATE TABLE `tr` (
  `id` int(11) default NULL,
  `name` varchar(50) default NULL,
  `purchased` date default NULL
) ENGINE=MyISAM DEFAULT CHARSET=latin1
PARTITION BY RANGE ( YEAR(purchased) ) (
  PARTITION p0 VALUES LESS THAN (1990) ENGINE = MyISAM,
  PARTITION p1 VALUES LESS THAN (1995) ENGINE = MyISAM,
  PARTITION p3 VALUES LESS THAN (2005) ENGINE = MyISAM
)
1 row in set (0.01 sec)

When you insert new rows into the changed table with purchased column values between '1995-01-01' and '2004-12-31' inclusive, those rows will be stored in partition p3. You can verify this as follows:

mysql> INSERT INTO tr VALUES (11, 'pencil holder', '1995-07-12');
Query OK, 1 row affected (0.00 sec)

mysql> SELECT * FROM tr WHERE purchased
    -> BETWEEN '1995-01-01' AND '2004-12-31';
+------+----------------+------------+
| id   | name           | purchased  |
+------+----------------+------------+
|   11 | pencil holder  | 1995-07-12 |
|    1 | desk organiser | 2003-10-15 |
|    5 | exercise bike  | 2004-05-09 |
|    7 | popcorn maker  | 2001-11-22 |
+------+----------------+------------+
4 rows in set (0.00 sec)

mysql> ALTER TABLE tr DROP PARTITION p3;
Query OK, 0 rows affected (0.03 sec)

mysql> SELECT * FROM tr WHERE purchased
    -> BETWEEN '1995-01-01' AND '2004-12-31';
Empty set (0.00 sec)

Note that the number of rows dropped from the table as a result of ALTER TABLE ... DROP PARTITION is not reported by the server as it would be by the equivalent DELETE query.

Dropping LIST partitions uses exactly the same ALTER TABLE ... DROP PARTITION syntax as used for dropping RANGE partitions. However, there is one important difference in the effect this has on your use of the table afterward: You can no longer insert into the table any rows having any of the values that were included in the value list defining the deleted partition. (See Section 17.2.2, “LIST Partitioning”, for an example.)

To add a new range or list partition to a previously partitioned table, use the ALTER TABLE ... ADD PARTITION statement. For tables which are partitioned by RANGE, this can be used to add a new range to the end of the list of existing partitions. For example, suppose that you have a partitioned table containing membership data for your organisation, which is defined as follows:

CREATE TABLE members (
    id INT,
    fname VARCHAR(25),
    lname VARCHAR(25),
    dob DATE
)
PARTITION BY RANGE( YEAR(dob) ) (
    PARTITION p0 VALUES LESS THAN (1970),
    PARTITION p1 VALUES LESS THAN (1980),
    PARTITION p2 VALUES LESS THAN (1990)
);

Suppose further that the minimum age for members is 16. As the calendar approaches the end of 2005, you realize that you will soon be admitting members who were born in 1990 (and later in years to come). You can modify the members table to accommodate new members born in the years 1990–1999 as shown here:

ALTER TABLE ADD PARTITION (PARTITION p3 VALUES LESS THAN (2000));

Important

With tables that are partitioned by range, you can use ADD PARTITION to add new partitions to the high end of the partitions list only. Trying to add a new partition in this manner between or before existing partitions will result in an error as shown here:

mysql> ALTER TABLE members
     >     ADD PARTITION (
     >     PARTITION p3 VALUES LESS THAN (1960));
ERROR 1463 (HY000): VALUES LESS THAN value must be strictly »
   increasing for each partition

In a similar fashion, you can add new partitions to a table that is partitioned by LIST. For example, given a table defined like so:

CREATE TABLE tt (
    id INT,
    data INT
)
PARTITION BY LIST(data) (
    PARTITION p0 VALUES IN (5, 10, 15),
    PARTITION p1 VALUES IN (6, 12, 18)
);

You can add a new partition in which to store rows having the data column values 7, 14, and 21 as shown:

ALTER TABLE tt ADD PARTITION (PARTITION p2 VALUES IN (7, 14, 21));

Note that you cannot add a new LIST partition encompassing any values that are already included in the value list of an existing partition. If you attempt to do so, an error will result:

mysql> ALTER TABLE tt ADD PARTITION 
     >     (PARTITION np VALUES IN (4, 8, 12));
ERROR 1465 (HY000): Multiple definition of same constant »
                    in list partitioning

Because any rows with the data column value 12 have already been assigned to partition p1, you cannot create a new partition on table tt that includes 12 in its value list. To accomplish this, you could drop p1, and add np and then a new p1 with a modified definition. However, as discussed earlier, this would result in the loss of all data stored in p1 — and it is often the case that this is not what you really want to do. Another solution might appear to be to make a copy of the table with the new partitioning and to copy the data into it using CREATE TABLE ... SELECT ..., then drop the old table and rename the new one, but this could be very time-consuming when dealing with a large amounts of data. This also might not be feasible in situations where high availability is a requirement.

You can add multiple partitions in a single ALTER TABLE ... ADD PARTITION statement as shown here:

CREATE TABLE employees (
  id INT NOT NULL,
  fname VARCHAR(50) NOT NULL,
  lname VARCHAR(50) NOT NULL,
  hired DATE NOT NULL
)
PARTITION BY RANGE( YEAR(hired) ) (
  PARTITION p1 VALUES LESS THAN (1991),
  PARTITION p2 VALUES LESS THAN (1996),
  PARTITION p3 VALUES LESS THAN (2001),
  PARTITION p4 VALUES LESS THAN (2005)
);

ALTER TABLE employees ADD PARTITION (
    PARTITION p5 VALUES LESS THAN (2010),
    PARTITION p6 VALUES LESS THAN MAXVALUE
);

Fortunately, MySQL's partitioning implementation provides ways to redefine partitions without losing data. Let us look first at a couple of simple examples involving RANGE partitioning. Recall the members table which is now defined as shown here:

mysql> SHOW CREATE TABLE members\G
*************************** 1. row ***************************
       Table: members
Create Table: CREATE TABLE `members` (
  `id` int(11) default NULL,
  `fname` varchar(25) default NULL,
  `lname` varchar(25) default NULL,
  `dob` date default NULL
) ENGINE=MyISAM DEFAULT CHARSET=latin1
PARTITION BY RANGE ( YEAR(dob) ) (
  PARTITION p0 VALUES LESS THAN (1970) ENGINE = MyISAM,
  PARTITION p1 VALUES LESS THAN (1980) ENGINE = MyISAM,
  PARTITION p2 VALUES LESS THAN (1990) ENGINE = MyISAM.
  PARTITION p3 VALUES LESS THAN (2000) ENGINE = MyISAM
)

Suppose that you would like to move all rows representing members born before 1960 into a separate partition. As we have already seen, this cannot be done using ALTER TABLE ... ADD PARTITION. However, you can use another partition-related extension to ALTER TABLE in order to accomplish this:

ALTER TABLE members REORGANIZE PARTITION p0 INTO (
    PARTITION s0 VALUES LESS THAN (1960),
    PARTITION s1 VALUES LESS THAN (1970)
);

In effect, this command splits partition p0 into two new partitions s0 and s1. It also moves the data that was stored in p0 into the new partitions according to the rules embodied in the two PARTITION ... VALUES ... clauses, so that s0 contains only those records for which YEAR(dob) is less than 1960 and s1 contains those rows in which YEAR(dob) is greater than or equal to 1960 but less than 1970.

A REORGANIZE PARTITION clause may also be used for merging adjacent partitions. You can return the members table to its previous partitioning as shown here:

ALTER TABLE members REORGANIZE PARTITION s0,s1 INTO (
    PARTITION p0 VALUES LESS THAN (1970)
);

No data is lost in splitting or merging partitions using REORGANIZE PARTITION. In executing the above statement, MySQL moves all of the records that were stored in partitions s0 and s1 into partition p0.

The general syntax for REORGANIZE PARTITION is:

ALTER TABLE tbl_name
    REORGANIZE PARTITION partition_list
    INTO (partition_definitions);

Here, tbl_name is the name of the partitioned table, and partition_list is a comma-separated list of names of one or more existing partitions to be changed. partition_definitions is a comma-separated list of new partition definitions, which follow the same rules as for the partition_definitions list used in CREATE TABLE (see Section 12.1.14, “CREATE TABLE Syntax”). It should be noted that you are not limited to merging several partitions into one, or to splitting one partition into many, when using REORGANIZE PARTITION. For example, you can reorganize all four partitions of the members table into two, as follows:

ALTER TABLE members REORGANIZE PARTITION p0,p1,p2,p3 INTO (
    PARTITION m0 VALUES LESS THAN (1980),
    PARTITION m1 VALUES LESS THAN (2000)
);

You can also use REORGANIZE PARTITION with tables that are partitioned by LIST. Let us return to the problem of adding a new partition to the list-partitioned tt table and failing because the new partition had a value that was already present in the value-list of one of the existing partitions. We can handle this by adding a partition that contains only nonconflicting values, and then reorganizing the new partition and the existing one so that the value which was stored in the existing one is now moved to the new one:

ALTER TABLE tt ADD PARTITION (PARTITION np VALUES IN (4, 8));
ALTER TABLE tt REORGANIZE PARTITION p1,np INTO (
    PARTITION p1 VALUES IN (6, 18),
    PARTITION np VALUES in (4, 8, 12)
);

Here are some key points to keep in mind when using ALTER TABLE ... REORGANIZE PARTITION to repartition tables that are partitioned by RANGE or LIST:

  • The PARTITION clauses used to determine the new partitioning scheme are subject to the same rules as those used with a CREATE TABLE statement.

    Most importantly, you should remember that the new partitioning scheme cannot have any overlapping ranges (applies to tables partitioned by RANGE) or sets of values (when reorganizing tables partitioned by LIST).

  • The combination of partitions in the partition_definitions list should account for the same range or set of values overall as the combined partitions named in the partition_list.

    For instance, in the members table used as an example in this section, partitions p1 and p2 together cover the years 1980 through 1999. Therefore, any reorganization of these two partitions should cover the same range of years overall.

  • For tables partitioned by RANGE, you can reorganize only adjacent partitions; you cannot skip over range partitions.

    For instance, you could not reorganize the members table used as an example in this section using a statement beginning with ALTER TABLE members REORGANIZE PARTITION p0,p2 INTO ... because p0 covers the years prior to 1970 and p2 the years from 1990 through 1999 inclusive, and thus the two are not adjacent partitions.

  • You cannot use REORGANIZE PARTITION to change the table's partitioning type; that is, you cannot (for example) change RANGE partitions to HASH partitions or vice versa. You also cannot use this command to change the partitioning expression or column. To accomplish either of these tasks without dropping and re-creating the table, you can use ALTER TABLE ... PARTITION BY .... For example:

    ALTER TABLE members
        PARTITION BY HASH( YEAR(dob) )
        PARTITIONS 8;
    

17.3.2. Management of HASH and KEY Partitions

Tables which are partitioned by hash or by key are very similar to one another with regard to making changes in a partitioning setup, and both differ in a number of ways from tables which have been partitioned by range or list. For that reason, this section addresses the modification of tables partitioned by hash or by key only. For a discussion of adding and dropping of partitions of tables that are partitioned by range or list, see Section 17.3.1, “Management of RANGE and LIST Partitions”.

You cannot drop partitions from tables that are partitioned by HASH or KEY in the same way that you can from tables that are partitioned by RANGE or LIST. However, you can merge HASH or KEY partitions using the ALTER TABLE ... COALESCE PARTITION command. For example, suppose that you have a table containing data about clients, which is divided into twelve partitions. The clients table is defined as shown here:

CREATE TABLE clients (
    id INT,
    fname VARCHAR(30),
    lname VARCHAR(30),
    signed DATE
)
PARTITION BY HASH( MONTH(signed) )
PARTITIONS 12;

To reduce the number of partitions from twelve to eight, execute the following ALTER TABLE command:

mysql> ALTER TABLE clients COALESCE PARTITION 4;
Query OK, 0 rows affected (0.02 sec)

COALESCE works equally well with tables that are partitioned by HASH, KEY, LINEAR HASH, or LINEAR KEY. Here is an example similar to the previous one, differing only in that the table is partitioned by LINEAR KEY:

mysql> CREATE TABLE clients_lk (
    ->     id INT,
    ->     fname VARCHAR(30),
    ->     lname VARCHAR(30),
    ->     signed DATE
    -> )
    -> PARTITION BY LINEAR KEY(signed)
    -> PARTITIONS 12;
Query OK, 0 rows affected (0.03 sec)

mysql> ALTER TABLE clients_lk COALESCE PARTITION 4;
Query OK, 0 rows affected (0.06 sec)
Records: 0  Duplicates: 0  Warnings: 0

Note that the number following COALESCE PARTITION is the number of partitions to merge into the remainder — in other words, it is the number of partitions to remove from the table.

If you attempt to remove more partitions than the table has, the result is an error like the one shown:

mysql> ALTER TABLE clients COALESCE PARTITION 18;
ERROR 1478 (HY000): Cannot remove all partitions, use DROP TABLE instead

To increase the number of partitions for the clients table from 12 to 18. use ALTER TABLE ... ADD PARTITION as shown here:

ALTER TABLE clients ADD PARTITION PARTITIONS 6;

17.3.3. Maintenance of Partitions

A number of table and partition maintenance tasks can be carried out using SQL statements intended for such purposes on partitioned tables in MySQL 6.0.

Table maintenance of partitioned tables can be accomplished using the statements CHECK TABLE, OPTIMIZE TABLE, ANALYZE TABLE, and REPAIR TABLE, which are supported for partitioned tables as of MySQL 6.0.6.

Also beginning with MySQL 6.0.6, you can use a number of extensions to ALTER TABLE for performing operations of this type on one or more partitions directly, as described in the following list:

  • Rebuilding partitions.  Rebuilds the partition; this has the same effect as dropping all records stored in the partition, then reinserting them. This can be useful for purposes of defragmentation.

    Example:

    ALTER TABLE t1 REBUILD PARTITION p0, p1;
    
  • Optimizing partitions.  If you have deleted a large number of rows from a partition or if you have made many changes to a partitioned table with variable-length rows (that is, having VARCHAR, BLOB, or TEXT columns), you can use ALTER TABLE ... OPTIMIZE PARTITION to reclaim any unused space and to defragment the partition data file.

    Example:

    ALTER TABLE t1 OPTIMIZE PARTITION p0, p1;
    

    Using OPTIMIZE PARTITION on a given partition is equivalent to running CHECK PARTITION, ANALYZE PARTITION, and REPAIR PARTITION on that partition.

  • Analyzing partitions.  This reads and stores the key distributions for partitions.

    Example:

    ALTER TABLE t1 ANALYZE PARTITION p3;
  • Repairing partitions.  This repairs corrupted partitions.

    Example:

    ALTER TABLE t1 REPAIR PARTITION p0,p1;
    
  • Checking partitions.  You can check partitions for errors in much the same way that you can use CHECK TABLE with nonpartitioned tables.

    Example:

    ALTER TABLE trb3 CHECK PARTITION p1;
    

    This command will tell you if the data or indexes in partition p1 of table t1 are corrupted. If this is the case, use ALTER TABLE ... REPAIR PARTITION to repair the partition.

Note

The statements ALTER TABLE ... ANALYZE PARTITION, ALTER TABLE ... CHECK PARTITION, ALTER TABLE ... OPTIMIZE PARTITION, and ALTER TABLE ... REPAIR PARTITION did not work properly as originally implemented, and were disabled in MySQL 6.0.5. They were re-introduced in MySQL 6.0.6. (Bug#20129) The use of these partitioning-specific ALTER TABLE statements with tables which are not partitioned is not supported; beginning with MySQL 6.0.8, it is expressly disallowed. (Bug#39434)

17.3.4. Obtaining Information About Partitions

This section discusses obtaining information about existing partitions, which can be done in a number of ways. These include:

As discussed elsewhere in this chapter, SHOW CREATE TABLE includes in its output the PARTITION BY clause used to create a partitioned table. For example:

mysql> SHOW CREATE TABLE trb3\G
*************************** 1. row ***************************
       Table: trb3
Create Table: CREATE TABLE `trb3` (
  `id` int(11) default NULL,
  `name` varchar(50) default NULL,
  `purchased` date default NULL
) ENGINE=MyISAM DEFAULT CHARSET=latin1
PARTITION BY RANGE (YEAR(purchased)) (
  PARTITION p0 VALUES LESS THAN (1990) ENGINE = MyISAM,
  PARTITION p1 VALUES LESS THAN (1995) ENGINE = MyISAM,
  PARTITION p2 VALUES LESS THAN (2000) ENGINE = MyISAM,
  PARTITION p3 VALUES LESS THAN (2005) ENGINE = MyISAM
)
1 row in set (0.00 sec)

The output from SHOW TABLE STATUS for partitioned tables is the same as that for nonpartitioned tables, except that the Create_options column contains the string partitioned. The Engine column contains the name of the storage engine used by all partitions of the table. (See Section 12.5.6.36, “SHOW TABLE STATUS Syntax”, for more information about this statement.)

You can also obtain information about partitions from INFORMATION_SCHEMA, which contains a PARTITIONS table. See Section 19.19, “The INFORMATION_SCHEMA PARTITIONS Table”.

It is possible to determine which partitions of a partitioned table are involved in a given SELECT query using EXPLAIN PARTITIONS. The PARTITIONS keyword adds a partitions column to the output of EXPLAIN listing the partitions from which records would be matched by the query.

Suppose that you have a table trb1 defined and populated as follows:

CREATE TABLE trb1 (id INT, name VARCHAR(50), purchased DATE)
    PARTITION BY RANGE(id)
    (
        PARTITION p0 VALUES LESS THAN (3),
        PARTITION p1 VALUES LESS THAN (7),
        PARTITION p2 VALUES LESS THAN (9),
        PARTITION p3 VALUES LESS THAN (11)
    );

INSERT INTO trb1 VALUES
    (1, 'desk organiser', '2003-10-15'),
    (2, 'CD player', '1993-11-05'),
    (3, 'TV set', '1996-03-10'),
    (4, 'bookcase', '1982-01-10'),
    (5, 'exercise bike', '2004-05-09'),
    (6, 'sofa', '1987-06-05'),
    (7, 'popcorn maker', '2001-11-22'),
    (8, 'aquarium', '1992-08-04'),
    (9, 'study desk', '1984-09-16'),
    (10, 'lava lamp', '1998-12-25');

You can see which partitions are used in a query such as SELECT * FROM trb1;, as shown here:

mysql> EXPLAIN PARTITIONS SELECT * FROM trb1\G
*************************** 1. row ***************************
           id: 1
  select_type: SIMPLE
        table: trb1
   partitions: p0,p1,p2,p3
         type: ALL
possible_keys: NULL
          key: NULL
      key_len: NULL
          ref: NULL
         rows: 10
        Extra: Using filesort

In this case, all four partitions are searched. However, when a limiting condition making use of the partitioning key is added to the query, you can see that only those partitions containing matching values are scanned, as shown here:

mysql> EXPLAIN PARTITIONS SELECT * FROM trb1 WHERE id < 5\G
*************************** 1. row ***************************
           id: 1
  select_type: SIMPLE
        table: trb1
   partitions: p0,p1
         type: ALL
possible_keys: NULL
          key: NULL
      key_len: NULL
          ref: NULL
         rows: 10
        Extra: Using where

EXPLAIN PARTITIONS provides information about keys used and possible keys, just as with the standard EXPLAIN SELECT statement:

mysql> ALTER TABLE trb1 ADD PRIMARY KEY (id);
Query OK, 10 rows affected (0.03 sec)
Records: 10  Duplicates: 0  Warnings: 0

mysql> EXPLAIN PARTITIONS SELECT * FROM trb1 WHERE id < 5\G
*************************** 1. row ***************************
           id: 1
  select_type: SIMPLE
        table: trb1
   partitions: p0,p1
         type: range
possible_keys: PRIMARY
          key: PRIMARY
      key_len: 4
          ref: NULL
         rows: 7
        Extra: Using where

You should take note of the following restrictions and limitations on EXPLAIN PARTITIONS:

  • You cannot use the PARTITIONS and EXTENDED keywords together in the same EXPLAIN ... SELECT statement. Attempting to do so produces a syntax error.

  • If EXPLAIN PARTITIONS is used to examine a query against a nonpartitioned table, no error is produced, but the value of the partitions column is always NULL.

As of MySQL 6.0.7, the rows column of EXPLAIN PARTITIONS output always displays the total number of records in the table. Previously, this was the number of matching rows. (Bug#35745)

See also Section 12.3.2, “EXPLAIN Syntax”.

17.4. Partition Pruning

This section discusses an optimization known as partition pruning. The core concept behind partition pruning is relatively simple, and can be described as “Do not scan partitions where there can be no matching values”. For example, suppose you have a partitioned table t1 defined by this statement:

CREATE TABLE t1 (
    fname VARCHAR(50) NOT NULL,
    lname VARCHAR(50) NOT NULL,
    region_code TINYINT UNSIGNED NOT NULL,
    dob DATE NOT NULL
)
PARTITION BY RANGE( region_code ) (
    PARTITION p0 VALUES LESS THAN (64),
    PARTITION p1 VALUES LESS THAN (128),
    PARTITION p2 VALUES LESS THAN (192),
    PARTITION p3 VALUES LESS THAN MAXVALUE
);

Consider the case where you wish to obtain results from a query such as this one:

SELECT fname, lname, region_code, dob
    FROM t1
    WHERE region_code > 125 AND region_code < 130;

It is easy to see that none of the rows which ought to be returned will be in either of the partitions p0 or p3; that is, we need to search only in partitions p1 and p2 to find matching rows. By doing so, it is possible to expend much more time and effort in finding matching rows than it is to scan all partitions in the table. This “cutting away” of unneeded partitions is known as pruning. When the optimizer can make use of partition pruning in performing a query, execution of the query can be an order of magnitude faster than the same query against a nonpartitioned table containing the same column definitions and data.

The query optimizer can perform pruning whenever a WHERE condition can be reduced to either one of the following:

  • partition_column = constant

  • partition_column IN (constant1, constant2, ..., constantN)

In the first case, the optimizer simply evaluates the partitioning expression for the value given, determines which partition contains that value, and scans only this partition. In many cases, the equals sign can be replaced with another arithmetic comparison, including <, >, <=, >=, and <>. Some queries using BETWEEN in the WHERE clause can also take advantage of partition pruning. See the examples later in this section.

In the second case, the optimizer evaluates the partitioning expression for each value in the list, creates a list of matching partitions, and then scans only the partitions in this partition list.

Pruning can also be applied to short ranges, which the optimizer can convert into equivalent lists of values. For instance, in the previous example, the WHERE clause can be converted to WHERE region_code IN (125, 126, 127, 128, 129, 130). Then the optimizer can determine that the first three values in the list are found in partition p1, the remaining three values in partition p2, and that the other partitions contain no relevant values and so do not need to be searched for matching rows.

This type of optimization can be applied whenever the partitioning expression consists of an equality or a range which can be reduced to a set of equalities, or when the partitioning expression represents an increasing or decreasing relationship. Pruning can also be applied for tables partitioned on a DATE or DATETIME column when the partitioning expression uses the YEAR() or TO_DAYS() function.

Note

We plan to add pruning support in a future MySQL release for additional functions that act on a DATE or DATETIME value, return an integer, and are increasing or decreasing.

For example, suppose that table t2, defined as shown here, is partitioned on a DATE column:

CREATE TABLE t2 (
    fname VARCHAR(50) NOT NULL,
    lname VARCHAR(50) NOT NULL,
    region_code TINYINT UNSIGNED NOT NULL,
    dob DATE NOT NULL
)
PARTITION BY RANGE( YEAR(dob) ) (
    PARTITION d0 VALUES LESS THAN (1970),
    PARTITION d1 VALUES LESS THAN (1975),
    PARTITION d2 VALUES LESS THAN (1980),
    PARTITION d3 VALUES LESS THAN (1985),
    PARTITION d4 VALUES LESS THAN (1990),
    PARTITION d5 VALUES LESS THAN (2000),
    PARTITION d6 VALUES LESS THAN (2005),
    PARTITION d7 VALUES LESS THAN MAXVALUE
);

The following queries on t2 can make of use partition pruning:

SELECT * FROM t2 WHERE dob = '1982-06-23';

SELECT * FROM t2 WHERE dob BETWEEN '1991-02-15' AND '1997-04-25';

SELECT * FROM t2 WHERE dob >= '1984-06-21' AND dob <= '1999-06-21'

In the case of the last query, the optimizer can also act as follows:

  1. Find the partition containing the low end of the range.

    YEAR('1984-06-21') yields the value 1984, which is found in partition d3.

  2. Find the partition containing the high end of the range.

    YEAR('1999-06-21') evaluates to 1999, which is found in partition d5.

  3. Scan only these two partitions and any partitions that may lie between them.

    In this case, this means that only partitions d3, d4, and d5 are scanned. The remaining partitions may be safely ignored (and are ignored).

Important

Invalid DATE and DATETIME values referenced in the WHERE clause of a query on a partitioned table are treated as NULL. This means that a query such as SELECT * FROM partitioned_table WHERE date_column < '2008-12-00' does not return any values (see Bug#40972).

So far, we have looked only at examples using RANGE partitioning, but pruning can be applied with other partitioning types as well.

Consider a table that is partitioned by LIST, where the partitioning expression is increasing or decreasing, such as the table t3 shown here. (In this example, we assume for the sake of brevity that the region_code column is limited to values between 1 and 10 inclusive.)

CREATE TABLE t3 (
    fname VARCHAR(50) NOT NULL,
    lname VARCHAR(50) NOT NULL,
    region_code TINYINT UNSIGNED NOT NULL,
    dob DATE NOT NULL
)
PARTITION BY LIST(region_code) (
    PARTITION r0 VALUES IN (1, 3),
    PARTITION r1 VALUES IN (2, 5, 8),
    PARTITION r2 VALUES IN (4, 9),
    PARTITION r3 VALUES IN (6, 7, 10)
);

For a query such as SELECT * FROM t3 WHERE region_code BETWEEN 1 AND 3, the optimizer determines in which partitions the values 1, 2, and 3 are found (r0 and r1) and skips the remaining ones (r2 and r3).

For tables that are partitioned by HASH or KEY, partition pruning is also possible in cases in which the WHERE clause uses a simple = relation against a column used in the partitioning expression. Consider a table created like this:

CREATE TABLE t4 (
    fname VARCHAR(50) NOT NULL,
    lname VARCHAR(50) NOT NULL,
    region_code TINYINT UNSIGNED NOT NULL,
    dob DATE NOT NULL
)
PARTITION BY KEY(region_code)
PARTITIONS 8;

Any query such as this one can be pruned:

SELECT * FROM t4 WHERE region_code = 7;

Pruning can also be employed for short ranges, because the optimizer can turn such conditions into IN relations. For example, using the same table t4 as defined previously, queries such as these can be pruned:

SELECT * FROM t4 WHERE region_code > 2 AND region_code < 6;

SELECT * FROM t4 WHERE region_code BETWEEN 3 AND 5;

In both these cases, the WHERE clause is transformed by the optimizer into WHERE region_code IN (3, 4, 5).

Important

This optimization is used only if the range size is smaller than the number of partitions. Consider this query:

SELECT * FROM t4 WHERE region_code BETWEEN 4 AND 8;

The range in the WHERE clause covers 5 values (4, 5, 6, 7, 8), but t4 has only 4 partitions. This means that the previous query cannot be pruned.

Pruning can be used only on integer columns of tables partitioned by HASH or KEY. For example, this query on table t4 cannot use pruning because dob is a DATE column:

SELECT * FROM t4 WHERE dob >= '2001-04-14' AND dob <= '2005-10-15';

However, if the table stores year values in an INT column, then a query having WHERE year_col >= 2001 AND year_col <= 2005 can be pruned.

17.5. Restrictions and Limitations on Partitioning

This section discusses current restrictions and limitations on MySQL partitioning support, as listed here:

  • Prohibited constructs.  The following constructs are not permitted in partitioning expressions:

    • Stored functions, stored procedures, UDFs, or plugins.

    • Declared variables or user variables.

    For a list of SQL functions which are permitted in partitioning expressions, see Section 17.5.3, “Partitioning Limitations Relating to Functions”.

  • Arithmetic and logical operators.  Use of the arithmetic operators +, , and * is permitted in partitioning expressions. However, the result must be an integer value or NULL (except in the case of [LINEAR] KEY partitioning, as discussed elswhere in this chapter — see Section 17.2, “Partition Types”, for more information).

    Beginning with MySQL 6.0.4, the DIV operator is also supported, and the / operator is disallowed. (Bug#30188, Bug#33182)

    The bit operators |, &, ^, <<, >>, and ~ are not permitted in partitioning expressions.

  • Server SQL mode.  Tables employing user-defined partitioning do not preserve the SQL mode in effect at the time that they were created. As discussed in Section 5.1.8, “Server SQL Modes”, the results of many MySQL functions and operators may change according to the server SQL mode. Therefore, a change in the SQL mode at any time after the creation of partitioned tables may lead to major changes in the behavior of such tables, and could easily lead to corruption or loss of data. For these reasons, it is strongly recommended that you never change the server SQL mode after creating partitioned tables.

    Examples.  The following examples illustrate some changes in behavior of partitioned tables due to a change in the server SQL mode:

    1. Error handling.  Suppose you create a partitioned table whose partitioning expression is one such as column DIV 0 or column MOD 0, as shown here:

      mysql> CREATE TABLE tn (c1 INT)
          ->     PARTITION BY LIST(1 DIV c1) (
          ->       PARTITION p0 VALUES IN (NULL),
          ->       PARTITION p1 VALUES IN (1)
          -> );
      Query OK, 0 rows affected (0.05 sec)
      

      The default behavior for MySQL is to return NULL for the result of a division by zero, without producing any errors:

      mysql> SELECT @@SQL_MODE;
      +------------+
      | @@SQL_MODE |
      +------------+
      |            |
      +------------+
      1 row in set (0.00 sec)
      
      
      mysql> INSERT INTO tn VALUES (NULL), (0), (1);
      Query OK, 3 rows affected (0.00 sec)
      Records: 3  Duplicates: 0  Warnings: 0
      

      However, changing the server SQL mode to treat division by zero as an error and to enforce strict error handling causes the same INSERT statement to fail, as shown here:

      mysql> SET SQL_MODE='STRICT_ALL_TABLES,ERROR_FOR_DIVISION_BY_ZERO';
      Query OK, 0 rows affected (0.00 sec)
      
      mysql> INSERT INTO tn VALUES (NULL), (0), (1);
      ERROR 1365 (22012): Division by 0
      

    2. Table accessibility.  Sometimes a change in the server SQL mode can make partitioned tables unusable. The following CREATE TABLE statement can be executed successfully only if the NO_UNSIGNED_SUBTRACTION mode is in effect:

      mysql> SELECT @@SQL_MODE;
      +------------+
      | @@SQL_MODE |
      +------------+
      |            |
      +------------+
      1 row in set (0.00 sec)
      
      mysql> CREATE TABLE tu (c1 BIGINT UNSIGNED)
          ->   PARTITION BY RANGE(c1 - 10) (
          ->     PARTITION p0 VALUES LESS THAN (-5),
          ->     PARTITION p1 VALUES LESS THAN (0),
          ->     PARTITION p2 VALUES LESS THAN (5),
          ->     PARTITION p3 VALUES LESS THAN (10),
          ->     PARTITION p4 VALUES LESS THAN (MAXVALUE)
          -> );
      ERROR 1563 (HY000): Partition constant is out of partition function domain
      
      mysql> SET SQL_MODE='NO_UNSIGNED_SUBTRACTION';
      Query OK, 0 rows affected (0.00 sec)
      
      mysql> SELECT @@SQL_MODE;
      +-------------------------+
      | @@SQL_MODE              |
      +-------------------------+
      | NO_UNSIGNED_SUBTRACTION |
      +-------------------------+
      1 row in set (0.00 sec)
      
      mysql> CREATE TABLE tu (c1 BIGINT UNSIGNED)
          ->   PARTITION BY RANGE(c1 - 10) (
          ->     PARTITION p0 VALUES LESS THAN (-5),
          ->     PARTITION p1 VALUES LESS THAN (0),
          ->     PARTITION p2 VALUES LESS THAN (5),
          ->     PARTITION p3 VALUES LESS THAN (10),
          ->     PARTITION p4 VALUES LESS THAN (MAXVALUE)
          -> );
      Query OK, 0 rows affected (0.05 sec)
      

      If you remove the NO_UNSIGNED_SUBTRACTION server SQL mode after creating tu, you may no longer be able to access this table:

      mysql> SET SQL_MODE='';
      Query OK, 0 rows affected (0.00 sec)
      
      mysql> SELECT * FROM tu;
      ERROR 1563 (HY000): Partition constant is out of partition function domain
      mysql> INSERT INTO tu VALUES (20);
      ERROR 1563 (HY000): Partition constant is out of partition function domain
      

  • Performance considerations. 

    • File system operations.  Partitioning and repartitioning operations (such as ALTER TABLE with PARTITION BY ..., REORGANIZE PARTITIONS, or REMOVE PARTITIONING) depend on file system operations for their implementation. This means that the speed of these operations is affected by such factors as file system type and characteristics, disk speed, swap space, file handling efficiency of the operating system, and MySQL server options and variables that relate to file handling. In particular, you should make sure that large_files_support is enabled and that open_files_limit is set properly. For partitioned tables using the MyISAM storage engine, increasing myisam_max_sort_file_size may improve performance; partitioning and repartitioning operations involving InnoDB tables may be made more efficient by enabling innodb_file_per_table.

    • Table locks.  The process executing a partitioning operation on a table takes a write lock on the table. Reads from such tables are relatively unaffected; pending INSERT and UPDATE operations are performed as soon as the partitioning operation has completed.

    • Storage engine.  Partitioning operations, queries, and update operations generally tend to be faster with MyISAM tables than with InnoDB or NDB tables.

    • Use of indexes and partition pruning.  As with nonpartitioned tables, proper use of indexes can speed up queries on partitioned tables significantly. In addition, designing partitioned tables and queries on these tables to take advantage of partition pruning can improve performance dramatically. See Section 17.4, “Partition Pruning”, for more information.

    • Performance with LOAD DATA Prior to MySQL 6.0.4, LOAD DATA performed very poorly when importing into partitioned tables. The statement now uses buffering to improve performance; however, the buffer uses 130 KB memory per partition to achieve this. (Bug#26527)

  • Maximum number of partitions.  The maximum number of partitions possible for a given table is 1024. This includes subpartitions.

    If, when creating tables with a very large number of partitions (but which is less than the maximum stated previously), you encounter an error message such as Got error 24 from storage engine, this means that you may need to increase the value of the open_files_limit system variable. See Section B.1.2.18, “'File' Not Found and Similar Errors”.

  • Foreign keys not supported.  Partitioned tables do not support foreign keys. This means that:

    1. Definitions of tables employing user-defined partitioning may not contain foreign key references to other tables.

    2. No table definition may contain a foreign key reference to a partitioned table.

    The scope of these restrictions includes tables that use the InnoDB storage engine.

  • ALTER TABLE ... ORDER BY An ALTER TABLE ... ORDER BY column statement run against a partitioned table causes ordering of rows only within each partition.

  • FULLTEXT indexes.  Partitioned tables do not support FULLTEXT indexes. This includes partitioned tables employing the MyISAM storage engine.

  • Spatial columns.  Columns with spatial data types such as POINT or GEOMETRY cannot be used in partitioned tables.

  • Temporary tables.  Temporary tables cannot be partitioned. (Bug#17497)

  • Log tables.  It is not possible to partition the log tables; an ALTER TABLE ... PARTITION BY ... statement on such a table fails with an error. (Bug#27816)

  • Data type of partitioning key.  A partitioning key must be either an integer column or an expression that resolves to an integer. The column or expression value may also be NULL. (See Section 17.2.6, “How MySQL Partitioning Handles NULL.)

    The lone exception to this restriction occurs when partitioning by [LINEAR] KEY, where it is possible to use columns of other types as partitioning keys, because MySQL's internal key-hashing functions produce the correct data type from these types. For example, the following CREATE TABLE statement is valid:

    CREATE TABLE tkc (c1 CHAR)
    PARTITION BY KEY(c1)
    PARTITIONS 4;
    

    This exception does not apply to BLOB or TEXT column types.

  • Subqueries.  A partitioning key may not be a subquery, even if that subquery resolves to an integer value or NULL.

  • Subpartitions.  Subpartitions are limited to HASH or KEY partitioning. HASH and KEY partitions cannot be subpartitioned.

  • Key caches not supported.  Key caches are not supported for partitioned tables. The CACHE INDEX and LOAD INDEX INTO CACHE statements, when you attempt to use them on tables having user-defined partitioning, fail with the errors The storage engine for the table doesn't support assign_to_keycache and The storage engine for the table doesn't support preload_keys, respectively.

  • DELAYED option not supported.  Use of INSERT DELAYED to insert rows into a partitioned table is not supported. Beginning with MySQL 6.0.4, attempting to do so fails with an error. (Bug#31210)

  • DATA DIRECTORY and INDEX DIRECTORY options.  DATA DIRECTORY and INDEX DIRECTORY are subject to the following restrictions when used with partitioned tables:

    • Beginning with MySQL 6.0.4, table-level DATA DIRECTORY and INDEX DIRECTORY options are ignored. (Bug#32091)

    • On Windows, the DATA DIRECTORY and INDEX DIRECTORY options are not supported for individual partitions or subpartitions (Bug#30459).

  • Repairing and rebuilding partitioned tables.  The statements CHECK TABLE, OPTIMIZE TABLE, ANALYZE TABLE, and REPAIR TABLE are supported for partitioned tables beginning with MySQL 6.0.6. (See Bug#20129.) mysqlcheck and myisamchk are not supported with partitioned tables.

    In addition, you can use ALTER TABLE ... REBUILD PARTITION to rebuild one or more partitions of a partitioned table; ALTER TABLE ... REORGANIZE PARTITION also causes partitions to be rebuilt. See Section 12.1.6, “ALTER TABLE Syntax”, for more information about these two statements.

17.5.1. Partitioning Keys, Primary Keys, and Unique Keys

This section discusses the relationship of partitioning keys with primary keys and unique keys. The rule governing this relationship can be expressed as follows: All columns used in the partitioning expression for a partitioned table must be part of every unique key that the table may have.

In other words, every unique key on the table must use every column in the table's partitioning expression. (This also includes the table's primary key, since it is by definition a unique key. This particular case is discussed later in this section.) For example, each of the following table creation statements is invalid:

CREATE TABLE t1 (
    col1 INT NOT NULL,
    col2 DATE NOT NULL,
    col3 INT NOT NULL,
    col4 INT NOT NULL,
    UNIQUE KEY (col1, col2)
)
PARTITION BY HASH(col3)
PARTITIONS 4;

CREATE TABLE t2 (
    col1 INT NOT NULL,
    col2 DATE NOT NULL,
    col3 INT NOT NULL,
    col4 INT NOT NULL,
    UNIQUE KEY (col1),
    UNIQUE KEY (col3)
)
PARTITION BY HASH(col1 + col3)
PARTITIONS 4;

In each case, the proposed table would have at least one unique key that does not include all columns used in the partitioning expression.

Each of the following statements is valid, and represents one way in which the corresponding invalid table creation statement could be made to work:

CREATE TABLE t1 (
    col1 INT NOT NULL,
    col2 DATE NOT NULL,
    col3 INT NOT NULL,
    col4 INT NOT NULL,
    UNIQUE KEY (col1, col2, col3)
)
PARTITION BY HASH(col3)
PARTITIONS 4;

CREATE TABLE t2 (
    col1 INT NOT NULL,
    col2 DATE NOT NULL,
    col3 INT NOT NULL,
    col4 INT NOT NULL,
    UNIQUE KEY (col1, col3)
)
PARTITION BY HASH(col1 + col3)
PARTITIONS 4;

This example shows the error produced in such cases:

mysql> CREATE TABLE t3 (
    ->     col1 INT NOT NULL,
    ->     col2 DATE NOT NULL,
    ->     col3 INT NOT NULL,
    ->     col4 INT NOT NULL,
    ->     UNIQUE KEY (col1, col2),
    ->     UNIQUE KEY (col3)
    -> )
    -> PARTITION BY HASH(col1 + col3)
    -> PARTITIONS 4;
ERROR 1491 (HY000): A PRIMARY KEY must include all columns in the table's partitioning function

The CREATE statement fails because both col1 and col3 are included in the proposed partitioning key, but neither of these columns is part of both of unique keys on the table. This shows one possible fix for the invalid table definition;

mysql> CREATE TABLE t3 (
    ->     col1 INT NOT NULL,
    ->     col2 DATE NOT NULL,
    ->     col3 INT NOT NULL,
    ->     col4 INT NOT NULL,
    ->     UNIQUE KEY (col1, col2, col3),
    ->     UNIQUE KEY (col3)
    -> )
    -> PARTITION BY HASH(col3)
    -> PARTITIONS 4;
Query OK, 0 rows affected (0.05 sec)

In this case, the proposed partitioning key col3 is part of both unique keys, and the table creation statement succeeds.

Since every primary key is by definition a unique key, this restriction also includes the table's primary key, if it has one. For example, the next two statements are invalid:

CREATE TABLE t4 (
    col1 INT NOT NULL,
    col2 DATE NOT NULL,
    col3 INT NOT NULL,
    col4 INT NOT NULL,
    PRIMARY KEY(col1, col2)
)
PARTITION BY HASH(col3)
PARTITIONS 4;

CREATE TABLE t5 (
    col1 INT NOT NULL,
    col2 DATE NOT NULL,
    col3 INT NOT NULL,
    col4 INT NOT NULL,
    PRIMARY KEY(col1, col3),
    UNIQUE KEY(col2)
)
PARTITION BY HASH( YEAR(col2) )
PARTITIONS 4;

In both cases, the primary key does not include all columns referenced in the partitioning expression. However, both of the next two statements are valid:

CREATE TABLE t6 (
    col1 INT NOT NULL,
    col2 DATE NOT NULL,
    col3 INT NOT NULL,
    col4 INT NOT NULL,
    PRIMARY KEY(col1, col2)
)
PARTITION BY HASH(col1 + YEAR(col2))
PARTITIONS 4;

CREATE TABLE t7 (
    col1 INT NOT NULL,
    col2 DATE NOT NULL,
    col3 INT NOT NULL,
    col4 INT NOT NULL,
    PRIMARY KEY(col1, col2, col4),
    UNIQUE KEY(col2, col1)
)
PARTITION BY HASH(col1 + YEAR(col2))
PARTITIONS 4;

If a table has no unique keys — this includes having no primary key — then this restriction does not apply, and you may use any column or columns in the partitioning expression as long as the column type is compatible with the partitioning type.

For the same reason, you cannot later add a unique key to a partitioned table unless the key includes all columns used by the table's partitioning expression. Consider given the partitioned table defined as shown here:

mysql> CREATE TABLE t_no_pk (c1 INT, c2 INT)
    ->     PARTITION BY RANGE(c1) (
    ->         PARTITION p0 VALUES LESS THAN (10),
    ->         PARTITION p1 VALUES LESS THAN (20),
    ->         PARTITION p2 VALUES LESS THAN (30),
    ->         PARTITION p3 VALUES LESS THAN (40)
    ->     );
Query OK, 0 rows affected (0.12 sec)

It is possible to add a primary key to t_no_pk using either of these ALTER TABLE statements:

#  possible PK
mysql> ALTER TABLE t_no_pk ADD PRIMARY KEY(c1);
Query OK, 0 rows affected (0.13 sec)
Records: 0  Duplicates: 0  Warnings: 0

# drop this PK
mysql> ALTER TABLE t_no_pk DROP PRIMARY KEY;
Query OK, 0 rows affected (0.10 sec)
Records: 0  Duplicates: 0  Warnings: 0

#  use another possible PK
mysql> ALTER TABLE t_no_pk ADD PRIMARY KEY(c1, c2);
Query OK, 0 rows affected (0.12 sec)
Records: 0  Duplicates: 0  Warnings: 0

# drop this PK
mysql> ALTER TABLE t_no_pk DROP PRIMARY KEY;
Query OK, 0 rows affected (0.09 sec)
Records: 0  Duplicates: 0  Warnings: 0

However, the next statement fails, because c1 is part of the partitioning key, but is not part of the proposed primary key:

#  fails with error 1503
mysql> ALTER TABLE t_no_pk ADD PRIMARY KEY(c2);
ERROR 1503 (HY000): A PRIMARY KEY must include all columns in the table's partitioning function

Since t_no_pk has only c1 in its partitioning expression, attempting to adding a unique key on c2 alone fails. However, you can add a unique key that uses both c1 and c2.

These rules also apply to existing nonpartitioned tables that you wish to partition using ALTER TABLE ... PARTITION BY. Consider a table np_pk defined as shown here:

mysql> CREATE TABLE np_pk (
    ->     id INT NOT NULL AUTO_INCREMENT,
    ->     name VARCHAR(50),
    ->     added DATE,
    ->     PRIMARY KEY (id)
    -> );
Query OK, 0 rows affected (0.08 sec)

The following ALTER TABLE statements fails with an error, because the added column is not part of any unique key in the table:

mysql> ALTER TABLE np_pk
    ->     PARTITION BY HASH( TO_DAYS(added) )
    ->     PARTITIONS 4;
ERROR 1503 (HY000): A PRIMARY KEY must include all columns in the table's partitioning function

However, this statement using the id column for the partitioning column is valid, as shown here:

mysql> ALTER TABLE np_pk
    ->     PARTITION BY HASH(id)
    ->     PARTITIONS 4;
Query OK, 0 rows affected (0.11 sec)
Records: 0  Duplicates: 0  Warnings: 0

In the case of np_pk, the only column that may be used as part of a partitioning expression is id; if you wish to partition this table using any other column or columns in the partitioning expression, you must first modify the table, either by adding the desired column or columns to the primary key, or by dropping the primary key altogether.

We are working to remove this limitation in a future MySQL release series.

17.5.2. Partitioning Limitations Relating to Storage Engines

The following limitations apply to the use of storage engines with user-defined partitioning of tables.

MERGE storage engine.  User-defined partitioning and the MERGE storage engine are not compatible. Tables using the MERGE storage engine cannot be partitioned. Partitioned tables cannot be merged.

FEDERATED storage engine.  Partitioning of FEDERATED tables is not supported; it is not possible to create partitioned FEDERATED tables. We are working to remove this limitation in a future MySQL release.

CSV storage engine.  Partitioned tables using the CSV storage engine are not supported; it is not possible to create partitioned CSV tables.

Upgrading partitioned tables.  When performing an upgrade, tables which are partitioned by KEY must be dumped and reloaded.

Same storage engine for all partitions.  All partitions of a partitioned table must use the same storage engine and it must be the same storage engine used by the table as a whole. In addition, if one does not specify an engine on the table level, then one must do either of the following when creating or altering a partitioned table:

  • Do not specify any engine for any partition or subpartition

  • Specify the engine for all partitions or subpartitions

We are working to remove this limitation in a future MySQL release.

17.5.3. Partitioning Limitations Relating to Functions

This section discusses limitations in MySQL Partitioning relating specifically to functions used in partitioning expressions.

Only the following MySQL functions are supported in partitioning expressions:

Note

CEILING() and FLOOR() Each of these functions returns an integer only if it is passed an integer argument. This means, for example, that the following CREATE TABLE statement fails with an error, as shown here:

mysql> CREATE TABLE t (c FLOAT) PARTITION BY LIST( FLOOR(c) )(
    ->     PARTITION p0 VALUES IN (1,3,5),
    ->     PARTITION p1 VALUES IN (2,4,6)
    -> );
ERROR 1490 (HY000): The PARTITION function returns the wrong type

See Section 11.5.2, “Mathematical Functions”, for more information about the return types of these functions.