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MySQL 8 for Big Data

MySQL 8 for Big Data

By : Challawala, Jaydip Lakhatariya, Mehta, Patel
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MySQL 8 for Big Data

MySQL 8 for Big Data

5 (1)
By: Challawala, Jaydip Lakhatariya, Mehta, Patel

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 (11 chapters)
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Apache Sqoop overview


Relational databases like MySQL are most popular when dealing with most of the business applications. As MySQL is open source, it is a default choice for many of the applications. Applications built using MySQL as database can belong to different domains, such as e-commerce, e-learning, medicine or health information sites, and social media applications, as mentioned in Chapter 1, Introduction to Big Data and MySQL 8. Each of these domains has the capacity to generate large number of data which has to be stored in MySQL. Some of this data is structured, like a user's registration information or a user's cart information, which can be maintained well by MySQL. On the other hand, some of the data is unstructured, like a user's last accessed page information, likes, shares, or tweets. This user's access information can be utilized very well to enhance user's experience while using application by analyzing user's behaviour or set up a recommendation engine based on the...

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