Book Image

MySQL 8 for Big Data

By : Shabbir Challawala, Chintan Mehta, Kandarp Patel, Jaydip Lakhatariya
Book Image

MySQL 8 for Big Data

By: Shabbir Challawala, Chintan Mehta, Kandarp Patel, Jaydip Lakhatariya

Overview of this book

With organizations handling large amounts of data on a regular basis, MySQL has become a popular solution to handle this structured Big Data. In this book, you will see how DBAs can use MySQL 8 to handle billions of records, and load and retrieve data with performance comparable or superior to commercial DB solutions with higher costs. Many organizations today depend on MySQL for their websites and a Big Data solution for their data archiving, storage, and analysis needs. However, integrating them can be challenging. This book will show you how to implement a successful Big Data strategy with Apache Hadoop and MySQL 8. It will cover real-time use case scenario to explain integration and achieve Big Data solutions using technologies such as Apache Hadoop, Apache Sqoop, and MySQL Applier. Also, the book includes case studies on Apache Sqoop and real-time event processing. By the end of this book, you will know how to efficiently use MySQL 8 to manage data for your Big Data applications.
Table of Contents (17 chapters)
Title Page
About the Authors
About the Reviewers
Customer Feedback

Horizontal partitioning in MySQL 8

As mentioned, horizontal partitioning will create more than one partition of the data. Each partition will have the same number of columns. Different partitioning techniques are used to divide the page into multiple partitions. Consider the following figure for horizontal partitioning:

The following is the list of partitioning types supported in MySQL 8:

  • Range partitioning
  • List partitioning
  • Hash partitioning
  • Columns partitioning
  • Key partitioning
  • Sub partitioning

Let's understand each partitioning type in detail.

Range partitioning

When partitioning is done based on expressions that contain contiguous non-repetitive values of ranges, it is known as range partitioning. The expression for range partitioning contains the key VALUE LESS THAN operator.

There are multiple data types, based on which we can partition the table:

CREATE TABLE access_log ( 
log_id INT NOT NULL, 
type VARCHAR(100), 
access_url VARCHAR(100), 
access_date TIMESTAMP NOT NULL, 
response_time INT NOT...