# Partitioning
# 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:
ALTER TABLE employees 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
);
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).
based on MySQL official document (opens new window).
# LIST Partitioning
List partitioning is similar to range partitioning in many ways. As in partitioning by RANGE, each partition must be explicitly defined. The chief difference between the two types of partitioning is that, in list partitioning, each partition is defined and selected based on the membership of a column value in one of a set of value lists, rather than in one of a set of contiguous ranges of values. This is done by using PARTITION BY LIST(expr) where expr is a column value or an expression based on a column value and returning an integer value, and then defining each partition by means of a VALUES IN (value_list), where value_list is a comma-separated list of integers.
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
);
Suppose that there are 20 video stores distributed among 4 franchises as shown in the following table.
| Region | Store ID Numbers |
|---|---|
| North | 3, 5, 6, 9, 17 |
| East | 1, 2, 10, 11, 19, 20 |
| West | 4, 12, 13, 14, 18 |
| Central | 7, 8, 15, 16 |
To partition this table in such a way that rows for stores belonging to the same region are stored in the same partition
ALTER TABLE employees 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)
);
based on MySQL official document (opens new window).
# 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.
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.
based on MySQL official document (opens new window).