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

Vertical partitioning


As stated earlier, vertical partitioning divides the columns into multiple file groups.

Vertical partitioning can be achieved by the following:

  • Row splitting into multiple file groups that can be stored at multiple locations
  • Organizing data into multiple tables by breaking large data tables into smaller database tables

In row splitting, columns from one table are vertically separated into multiple file groups. When there are large datasets stored in a table, it may be difficult to manage large database files on a single location or server. So we can divide some of the columns from the database into a separate file group where can be managed on a separate disk.

Consider the following screenshot for vertical partitioning of the user table. As stated earlier, the database table, users, has been split into two separate partitions stored on different storage.

There can be more than two partitions of the table:

Vertical partitioning of a single table into multiple file groups is...