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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

Setting up Memcached

MySQL has its own Memcached plugin, daemon_memcached, which is tightly integrated with the MySQL server. This improves the performance and avoids network traffic over the traditional Memcached approach.

In the traditional way, Memcached was running on a separate port and as a different process; hence, it would have an overhead of network communication between MySQL and Memcached. However, this plugin made it easy to use and lightweight as it is integrated with the MySQL server itself.

Supported environments for this plugin are as follows:

  • Linux
  • Solaris
  • OS X

Let's see to how to set up the daemon_memcached plugin in the MySQL server. We would have to install this plugin on each of the MySQL server instances, in case we are using the cluster environment of MySQL.

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