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
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface

Partitioning in MySQL 8


In general terms, partitioning is logically dividing anything into multiple subgroups so that each subgroup can be identified independently and can be combined into a single partition. Let's understand what partitioning means in terms of RDBMS.

What is partitioning?

Partitioning is generally used to divide data into multiple logical file groups for the purpose of performance, availability, and manageability. When dealing with big data, the normal tendency of data is to be in terms of billions of records. So to improve performance of the database, it is better to divide data among multiple file groups. These file groups can be on a single machine or shared across multiple machines and identified by a key. These file groups are known as partitioned data.

Partitioning types

Data in the table can be partitioned in two ways:

  • Horizontal partitioning
  • Vertical partitioning

Horizontal partitioning

When the number of rows in the table is very large, the table can be divided into multiple...