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MySQL 8 for Big Data

MySQL 8 for Big Data

By : Challawala, Jaydip Lakhatariya, Mehta, Patel
5 (1)
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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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MySQL 8 index types

In the previous topics, you learned different index structures and how to create indexes on a table. Now let's see different indexes in detail that are available in MySQL and their importance.

When you create a table in MySQL, there are five types of index options available:

  • PRIMARY
  • UNIQUE
  • COLUMN
  • FULLTEXT
  • SPATIAL

You can choose any of these indexes on your table based on your database design; the frequency of data and columns used in the query would accordingly help you define where indexes need to be applied.

Defining a primary index

The primary key is used to identify each row uniquely. The column on which the primary key is defined is unique in nature and contains not null values. In the following...

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