Table partitioning in SQL, as the name suggests, is a process of dividing large data tables into small manageable parts, such that each part has its own name and characteristics.

Table partitioning helps in significantly improving database server performance as less number of rows have to be read, processed and returned. We can also use partitioning techniques for dividing indexes and index-organized tables.

Table partitioning can be of two types, namely, vertical partitioning or horizontal partitioning. In vertical partitioning, we divide the table column wise. While in horizontal partitioning, we divide the table row wise on the basis of range of values in a certain column.

Syntax and parameters

The basic syntax for partitioning a table using range is as follows :

Main table creation :

CREATE TABLE main_table_name (

column_1 data type,

column_2 data type,

.

.

. ) PARTITION BY RANGE (column_2);

Partition table creation :

CREATE TABLE partition_name

PARTITION OF main_table_name FOR VALUES FROM (start_value) TO (end_value);

The parameters used in the above mentioned syntax are similar to CREATE TABLE statement, except these :

PARTITION BY RANGE (column_2) : column_2 is the field on the basis of which partitions will be created.

partition_name : name of the partition table

FROM (start_value) TO (end_value) : The range of values in column_2, which forms the part of this partition. Note that start_value is inclusive, while end_value is exclusive.

Here is an example to illustrate it further.

Example

Imagine that you are working as a data engineer for an e-com firm that gets a huge number of orders on a daily basis. You usually store data such as order_id, order_at, customer_id etc. in a SQL table called “e-transactions’’. Since, the table has a humongous amount of data in it, the low load speed and high return time etc. have become a problem for data analysts, who use this table for preparing KPIs on a daily basis.

What will you do to improvise this table, so that data analysts can run queries quickly?

A logical step would be partitioning the table into smaller parts. Let’s say we create partitions such that the partition stores data pertaining to specified order dates only. This way, we will have less data in each partition and working on it will be more fun.

We can partition the table using declarative partitioning i.e. by using a PARTITION BY RANGE (column_name) function as shown below.

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