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

Summary


In this chapter, we understood how log analysis can help an e-commerce store to convert its visitors log information into increasing the sales volume and enhancing user experience, in turn increasing the profit from the business. We found out how MySQL 8 and Hadoop can be used to generate reports for user behavior. We went through how Sqoop can be very useful in exchanging data between MySQL 8 and Hadoop HDFS. We had a brief explanation about Hadoop, went through in detail about Apache Sqoop, and learnt how to use import and export operations of Sqoop.

In the next chapter, we will learn what is real time processing of data and how MySQL's applier can be used for real time processing of the data.