With the 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 Database Administrators (DAs) can use MySQL 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 Big Data solutions for their data archiving, storage, and analysis needs. However, integrating them can be challenging. This book will show how to implement a successful Big Data strategy with Apache Hadoop and MySQL 8. It will cover real-time use case scenarios to explain integration and achieving Big Data solutions using different technologies such as Apache Hadoop, Apache Sqoop, and MySQL Applier.
The book will have discussion on topics such as features of MySQL 8, best practices for using MySQL 8, and NoSQL APIs provided by MySQL 8, and will also have a use case on using MySQL 8 for managing Big Data. By the end of this book, you will learn how to efficiently use MySQL 8 to manage data for your Big Data applications.
Chapter 1, Introduction to Big Data and MySQL 8, provides an overview of Big Data and MySQL 8, their importance, and life cycle of big data. It covers the basic idea of Big Data and its trends in the current market. Along with that, it also explains the benefits of using MySQL, takes us through the steps to install MySQL 8, and acquaints us with newly introduced features in MySQL 8.
Chapter 2, Data Query Techniques in MySQL 8, covers the basics of querying data on MySQL 8 and how to join or aggregate data set in it.
Chapter 3, Indexing your data for High-Performing Queries, explains about indexing in MySQL 8, introduces the different types of indexing available in MySQL, and shows how to do indexing for faster performance on large quantities of data.
Chapter 4, Using Memcached with MySQL 8, provides an overview of Memcached with MySQL and informs us of the various advantages of using it. It covers the Memcached installation steps, replication configuration, and various Memcached APIs in different programming languages.
Chapter 5, Partitioning High Volume Data, explains how high-volume data can be partitioned in MySQL 8 using different partitioning methods. It covers the various types of partitioning that we can implement in MySQL 8 and their use with Big Data.
Chapter 6, Replication for building highly available solutions, explains implementing group replication in MySQL 8. Chapter talks about how large data can be scaled and replicating of data can be faster using different techniques of replication.
Chapter 7, MySQL 8 Best Practices, covers the best practices of using MySQL 8 for Big Data. It has all the different kinds of dos and don'ts for using MySQL 8.
Chapter 8, NoSQL API for Integrating with Big Data Solutions, explains integration of NoSQL API for acquiring data. It also explains NoSQL and its various APIs in different programming languages for connecting NoSQL with MySQL.
Chapter 9, Case Study: Part I - Apache Sqoop for Exchanging Data between MySQL and Hadoop, explains how bulk data can be efficiently transferred between Hadoop and MySQL using Apache Sqoop.
Chapter 10, Case Study: Part II - Realtime event processing using MySQL applier, explains real-time integration of MySQL with Hadoop, and reading binary log events as soon as they are committed and writing them into a file in HDFS.
This book will guide you through the installation of all the tools that you need to follow the examples. You will need to install the following software to effectively run the code samples present in this book:
- MySQL 8.0.3
- Hadoop 2.8.1
- Apache Sqoop 1.4.6
This book is intended for MySQL database administrators and Big Data professionals looking to integrate MySQL and Hadoop to implement a high performance Big Data solution. Some previous experience with MySQL will be helpful.
In this book, you will find a number of text styles that distinguish between different kinds of information. Here are some examples of these styles and explanations of their meanings.
Code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles are shown as follows: "We can include other contexts through the use of the include directive."
A block of code is set as follows:
[default] exten => s,1,Dial(Zap/1|30) exten => s,2,Voicemail(u100) exten => s,102,Voicemail(b100) exten => i,1,Voicemail(s0)
When we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold:
[default] exten => s,1,Dial(Zap/1|30) exten => s,2,Voicemail(u100) exten => s,102,Voicemail(b100) exten => i,1,Voicemail(s0)
Any command-line input or output is written as follows:
# cp /usr/src/asterisk-addons/configs/cdr_mysql.conf.sample /etc/asterisk/cdr_mysql.confNew terms and important words are shown in bold. Words that you see on the screen, for example, in menus or dialog boxes, appear in the text like this: "Clicking the Next button moves you to the next screen".
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