Understand the partitioning and sharding technology of MySQL and PostgreSQL

Understand the partitioning and sharding technology of MySQL and PostgreSQL

Abstract:
MySQL and PostgreSQL are two common relational database management systems (RDBMS), and they both provide partitioning and sharding technology To optimize data storage and query efficiency. This article will introduce the basic concepts of partitioning and sharding in MySQL and PostgreSQL, as well as show some sample code to illustrate how to use these technologies.

1. MySQL’s partitioning technology

1. The concept of partition
   MySQL’s partitioning technology is to divide a table into multiple independent partitions. Each partition can be independently Store and query data, thereby improving query efficiency and providing better scalability. Usually partitioning can be performed based on a certain column in the table (such as date, region, etc.), or partitioning rules can be defined through ranges, lists, hashes, etc.
2. Sample code for partitioning
   The following is a sample code using MySQL's partitioning technology:

Create a table containing dates and sales:
CREATE TABLE sales (

id INT NOT NULL AUTO_INCREMENT,
date DATE,
amount DECIMAL(10,2),
PRIMARY KEY (id)

) ENGINE=InnoDB;

Partition the table by date range:
ALTER TABLE sales
PARTITION BY RANGE (YEAR(date))
(

PARTITION p0 VALUES LESS THAN (2010),
PARTITION p1 VALUES LESS THAN (2011),
PARTITION p2 VALUES LESS THAN (2012),
PARTITION p3 VALUES LESS THAN (2013),
PARTITION p4 VALUES LESS THAN MAXVALUE

);

Through the above code, the sales table is partitioned according to the date range, and the data in each partition can be stored and queried independently.

2. PostgreSQL partitioning technology

1. The concept of partition
   PostgreSQL’s partitioning technology is to split a table into multiple sub-tables, each sub-table contains a part of the data, This improves query efficiency and reduces storage space usage. Partitioning rules can be defined using ranges, lists, hashes, etc., and each sub-table can store and query data independently.
2. Sample code for partitioning
   The following is a sample code using PostgreSQL's partitioning technology:

Create a table containing dates and sales:
CREATE TABLE sales (

id SERIAL,
date DATE,
amount DECIMAL(10,2),
PRIMARY KEY (id)

);

Create a parent table and define partitioning rules:
CREATE TABLE sales_partition (

date_range TSRANGE,
CHECK (date_range IS NOT NULL)

) PARTITION BY RANGE (date_range);

Create two child tables:
CREATE TABLE sales_jan2018 PARTITION OF sales_partition

FOR VALUES FROM ('2018-01-01', '2018-02-01');

CREATE TABLE sales_feb2018 PARTITION OF sales_partition

FOR VALUES FROM ('2018-02-01', '2018-03-01');

Through the above code, a parent table sales_partition and two child tables are created Tables sales_jan2018, sales_feb2018, each sub-table contains data within the specified date range.

Conclusion:
Both MySQL and PostgreSQL provide partitioning and sharding technologies to help optimize data storage and query efficiency. By using these techniques, you can achieve better performance and scalability when processing large amounts of data. However, it is necessary to select appropriate partitioning and sharding strategies based on specific business needs and scenarios, and to reasonably design and manage the partition/sharding structure.

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