MySQL 8 for Big Data
- Length: 296 pages
- Edition: 1
- Language: English
- Publisher: Packt Publishing
- Publication Date: 2017-10-20
- ISBN-10: 1788397185
- ISBN-13: 9781788397186
- Sales Rank: #2264918 (See Top 100 Books)
MySQL 8 for Big Data: Effective data processing with MySQL 8, Hadoop, NoSQL APIs, and other Big Data tools
Uncover the power of MySQL 8 for Big Data
About This Book
- Combine the powers of MySQL and Hadoop to build a solid Big Data solution for your organization
- Integrate MySQL with different NoSQL APIs and Big Data tools such as Apache Sqoop
- A comprehensive guide with practical examples on building a high performance Big Data pipeline with MySQL
Who This Book Is For
This book is intended for MySQL database administrators and Big Data professionals looking to integrate MySQL 8 and Hadoop to implement a high performance Big Data solution. Some previous experience with MySQL will be helpful, although the book will highlight the newer features introduced in MySQL 8.
What You Will Learn
- Explore the features of MySQL 8 and how they can be leveraged to handle Big Data
- Unlock the new features of MySQL 8 for managing structured and unstructured Big Data
- Integrate MySQL 8 and Hadoop for efficient data processing
- Perform aggregation using MySQL 8 for optimum data utilization
- Explore different kinds of join and union in MySQL 8 to process Big Data efficiently
- Accelerate Big Data processing with Memcached
- Integrate MySQL with the NoSQL API
- Implement replication to build highly available solutions for Big Data
In Detail
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
Table of Contents
Chapter 1. Introduction To Big Data And Mysql 8
Chapter 2. Data Query Techniques In Mysql 8
Chapter 3. Indexing Your Data For High-Performing Queries
Chapter 4. Using Memcached With Mysql 8
Chapter 5. Partitioning High Volume Data
Chapter 6. Replication For Building Highly Available Solutions
Chapter 7. Mysql 8 Best Practices
Chapter 8. Nosql Api For Integrating With Big Data Solutions
Chapter 9. Case Study: Part I – Apache Sqoop For Exchanging Data Between Mysql And Hadoop
Chapter 10. Case Study: Part Ii – Real Time Event Processing Using Mysql Applier
