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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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Summary

You now have good knowledge of the different types of index structures supported by MySQL and now how to create an index in MySQL. You also learned different types of indexes available in MySQL 8 such as clustered index, covering index, descending index, and invisible index. We got a good understanding of fulltext indexing and how natural language fulltext indexes and fulltext indexes on Boolean mode works.

In the next chapter, we will cover some interesting things to boost MySQL performance such as how to set up Memcache, usage of Memcache, Memcache configuration, using Memcache APIs, how to analyze data stored in Memcache, and how to use Memcache APIs in MySQL 8.

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