The MySQL Partitioning is used to divide large tables into smaller partitions that are stored in different physical locations and are treated as separate tables. Even though the smaller partitions are managed individually, they are still part of the main table.

There are two forms of partitioning in MySQL: Horizontal Partitioning and Vertical Partitioning.

The MySQL Vertical Partitioning

The MySQL Vertical partitioning divides the table into multiple tables based on columns, rather than rows.

There are two main types of vertical partitioning in MySQL, each serving specific purposes −

• RANGE Columns Partitioning
• LIST Columns Partitioning

Both Range Columns Partitioning and List Columns Partitioning support various data types, including integer types (TINYINT, SMALLINT, MEDIUMINT, INT, and BIGINT), string types (CHAR, VARCHAR, BINARY, and VARBINARY), as well as DATE and DATETIME data types.

Range Columns Partitioning

The MySQL Range Columns partitioning uses one or more columns as partition keys to divide the data into partitions based on a defined range of column values.

The values in these columns are compared to predefined ranges, and each row is assigned to the partition that encompasses the range containing its column values.

Example

In the following query, we are creating a table named INVENTORY and dividing it into three partitions based on “product_quantity” and “product_price” columns. Rows with specific values in these columns are stored in their corresponding partitions −

CREATE TABLE INVENTORY (
   id INT,
   product_name VARCHAR(50),
   product_quantity INT,
   product_price int
)
   PARTITION BY RANGE COLUMNS(product_quantity, product_price) (
   PARTITION P_low_stock VALUES LESS THAN (10, 100),
   PARTITION P_medium_stock VALUES LESS THAN (50, 500),
   PARTITION P_high_stock VALUES LESS THAN (200, 1200)
);

Here, we are inserting rows into the above-created table −

INSERT INTO INVENTORY VALUES
(1, ''Headphones'', 5, 50),
(2, ''Mouse'', 15, 200),
(3, ''Monitor'', 30, 300),
(4, ''Keyboard'', 60, 600),
(5, ''CPU'', 100, 1000);

Following is the INVENTORY table obtained −

id	product_name	product_quantity	product_price
1	Headphones	5	50
2	Mouse	15	200
3	Monitor	30	300
4	Keyboard	60	600
5	CPU	100	1000

Now that we have some data in the INVENTORY table, we can display the partition status to see how the data is distributed among the partitions using the following query −

SELECT PARTITION_NAME, TABLE_ROWS
FROM INFORMATION_SCHEMA.PARTITIONS 
WHERE TABLE_NAME=''inventory

You will see in the output below that the respective columns are assigned to their respective partitions based on the defined range values −

PARTITION_NAME	TABLE_ROWS
P_high_stock	2
P_low_stock	1
P_medium_stock	2

Displaying Partitions −

We can also display data from specific partitions using the PARTITION clause. For instance, to retrieve data from partition P_high_stock, we use the following query −

SELECT * FROM inventory PARTITION (P_high_stock);

It will display all the records in partition P_high_stock −

ID	NAME	AGE	ADDRESS	SALARY
4	Keyboard	60	600
5	CPU	100	1000

Similarly, we can display other partitions using the same syntax.

List Columns Partitioning

The MySQL List columns partitioning uses one or more columns as partition keys and assigns records to partitions based on specific values in those columns. This method is handy when you want to group data into partitions based on discrete values or categories.

Example

Let us create a table named “EMPLOYEES” and partition it using LIST COLUMNS partitioning based on the “department” column −

CREATE TABLE EMPLOYEES (
   id INT,
   first_name VARCHAR(50),
   last_name VARCHAR(50),
   hiring_date DATE,
   department VARCHAR(50)
)
   PARTITION BY LIST COLUMNS(department) (
   PARTITION p_sales VALUES IN (''Sales'', ''Marketing''),
   PARTITION p_engineering VALUES IN (''Engineering'', ''Research''),
   PARTITION p_operations VALUES IN (''Operations'')
);

Here, we are inserting records into above-created table −

INSERT INTO EMPLOYEES VALUES 
(1, ''John'', ''Doe'', ''2020-01-01'', ''Sales''),
(2, ''Jane'', ''Doe'', ''2020-02-01'', ''Marketing''),
(3, ''Bob'', ''Smith'', ''2020-03-01'', ''Engineering''),
(4, ''Alice'', ''Johnson'', ''2020-04-01'', ''Research''),
(5, ''Mike'', ''Brown'', ''2020-05-01'', ''Operations'');

Following is the EMPLOYEES table obtained −

id	first_name	last_name	hiring_date	department
1	John	Doe	2020-01-01	Sales
2	Jane	Doe	2020-02-01	Marketing
3	Bob	Smith	2020-03-01	Engineering
4	Alice	Johnson	2020-04-01	Research
5	Mike	Brown	2020-05-01	Operations

We can display the partition status of the EMPLOYEES table to see how the data is distributed among partitions using the following query −

SELECT PARTITION_NAME, TABLE_ROWS 
FROM INFORMATION_SCHEMA.PARTITIONS 
WHERE TABLE_NAME=''EMPLOYEES

It will display the partitions and the number of rows in each partition based on the department values −

PARTITION_NAME	TABLE_ROWS
p_engineering	2
p_operations	1
p_sales	2