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

MySQL indexing


MySQL supports various indexes on its tables for the faster access of records. Before we define indexes on the tables, it is important to know when we need to index data, and it's also equally important to select the proper field to create indexes.

The following list shows when to use indexing:

  • When grouping based on a specific column is required
  • When sorting on a specific column is required
  • When you need to find the minimum and maximum values from the table
  • When we have a large dataset and need to find a few records based on certain conditions frequently
  • When you need to fire a query that has a join between two or more tables

Index structures

There are different structures used by various indexing methods to store the index information in the database:

  • Bitmap indexes
  • Sparse indexes
  • Dense indexes
  • B-Tree indexes
  • Hash indexes

Let's quickly go through each of these indexes.

Bitmap indexes

As the name suggests, a Bitmap index stores column information as a bit. Bitmap indexing is used when there...