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

Case study overview


MySQL is a proven solution to store transactional data that is used to maintain ACID properties during write operations. Starting from MySQL 5.6, it also includes the new NoSQL Memcached API for InnoDB, which improves performance for high volume data ingestion. Hadoop is used to store a huge amount of data (in petabytes) and processing it for many scenarios such as storing archived data or various historical data. Analytical processing of data was handled offline and was not an integrated part of the data processing. However, the technology has evolved and nowadays, Hadoop is an active part of data flows for many use cases where we require real-time data processing and provisioning of data to the user.

We can use MySQL to store the transnational data and Hadoop to store huge amount of data which can easily process the data using a map-reduce algorithm. We can take advantages of both technology to unlock the Big Data analysis. There are various use cases where we need to...