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MySQL 8 for Big Data

You're reading from   MySQL 8 for Big Data Effective data processing with MySQL 8, Hadoop, NoSQL APIs, and other Big Data tools

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Product type Paperback
Published in Oct 2017
Publisher Packt
ISBN-13 9781788397186
Length 296 pages
Edition 1st Edition
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Authors (4):
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Chintan Mehta Chintan Mehta
Author Profile Icon Chintan Mehta
Chintan Mehta
Shabbir Challawala Shabbir Challawala
Author Profile Icon Shabbir Challawala
Shabbir Challawala
Jaydip Lakhatariya Jaydip Lakhatariya
Author Profile Icon Jaydip Lakhatariya
Jaydip Lakhatariya
Kandarp Patel Kandarp Patel
Author Profile Icon Kandarp Patel
Kandarp Patel
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Toc

Table of Contents (11) Chapters Close

Preface 1. Introduction to Big Data and MySQL 8 FREE CHAPTER 2. Data Query Techniques in MySQL 8 3. Indexing your data for High-Performing Queries 4. Using Memcached with MySQL 8 5. Partitioning High Volume Data 6. Replication for building highly available solutions 7. MySQL 8 Best Practices 8. NoSQL API for Integrating with Big Data Solutions 9. Case study: Part I - Apache Sqoop for exchanging data between MySQL and Hadoop 10. Case study: Part II - Real time event processing using MySQL applier

Using Memcached with MySQL 8

In the previous chapter, we saw how indexing works in MySQL 8 and how it can be useful for better performance. You also learned how to create indexes and saw the 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 this chapter, we will discuss using Memcached with MySQL 8. The following are the topics that will be covered:

  • Setting up Memcached
  • Using Memcached
  • Analyzing data stored in Memcached
  • Memcached replication configuration
  • Memcached APIs for different technologies

Let's first start with an overview of Memcached with MySQL 8 followed by other details of Memcached.

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