Relational databases like MySQL are most popular when dealing with most of the business applications. As MySQL is open source, it is a default choice for many of the applications. Applications built using MySQL as database can belong to different domains, such as e-commerce, e-learning, medicine or health information sites, and social media applications, as mentioned in Chapter 1, Introduction to Big Data and MySQL 8. Each of these domains has the capacity to generate large number of data which has to be stored in MySQL. Some of this data is structured, like a user's registration information or a user's cart information, which can be maintained well by MySQL. On the other hand, some of the data is unstructured, like a user's last accessed page information, likes, shares, or tweets. This user's access information can be utilized very well to enhance user's experience while using application by analyzing user's behaviour or set up a recommendation engine based on the...
MySQL 8 for Big Data
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MySQL 8 for Big Data
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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.
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Current Title:
MySQL 8 for Big Data
Table of Contents (17 chapters)
Title Page
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
Free Chapter
Introduction to Big Data and MySQL 8
Data Query Techniques in MySQL 8
Indexing your data for High-Performing Queries
Using Memcached with MySQL 8
Partitioning High Volume Data
Replication for building highly available solutions
MySQL 8 Best Practices
NoSQL API for Integrating with Big Data Solutions
Case study: Part I - Apache Sqoop for exchanging data between MySQL and Hadoop
Case study: Part II - Real time event processing using MySQL applier
Customer Reviews