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

Chapter 3. Indexing your data for High-Performing Queries

In the previous chapter, you learned to apply queries on your data stored in the MySQL database. You learned the different syntax of the select query, how to join tables, and how to apply aggregate functions on the table.

In this chapter, you will learn below topics on what is indexing and different types of indexes:

  • MySQL indexing
  • MySQL index types
  • Indexing JSON data

Let's assume that we have a database table that has more then 50 lakh records of email addresses and you want to fetch one record out of this table. Now, if you write a query to fetch an email address, MySQL will have to check in each and every row for the values matching your queried email address. If MySQL takes one microsecond to scan one record, then it will take around five seconds to load just one record and, as the number of records increases in a table, the time taken will also increase exponentially, which would affect performance!

Fortunately, current relational...