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 5. Partitioning High Volume Data

In the previous chapter, you learned the basics of Memcached and its wonderful features. We also went into detail about working in different scenarios and how we can use Memcached APIs to improve the performance of our MySQL query. Let's now learn different partitioning methods and how partitioning can help in case of large data tables in this chapter.

We will cover below topics in this chapter about partitioning in MySQL 8:

  • Partitioning in MySQL 8
  • Horizontal partitioning in MySQL 8
  • Vertical partitioning
  • Pruning partitions in MySQL
  • Querying on partitioned data

When we talk about big data, it is automatically considered that we need to deal with large data tables where different information is stored. For any organization, it is very important to store data in such a way that the database provides scalability, performance, availability, and security. For instance, in a highly accessed e-commerce store, there are thousands, or more, of orders placed frequently...