MySQL 8 for Big Data: Effective data processing with MySQL 8, Hadoop, NoSQL APIs, and other Big Data tools
Language: English
Published by Packt Publishing, 2017
- Softcover
- New

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In English.
Seller Inventory # ria9781788397186_new
- Title
- MySQL 8 for Big Data: Effective data processing with MySQL 8, Hadoop, NoSQL APIs, and other Big Data tools
- Author
- Mehta, Chintan; Challawala, Shabbir; Patel, Kandarp
- Publisher
- Packt Publishing
- Publication year
- 2017
- Condition
- New
- Binding
- Soft cover
- Language
- English
- ISBN 10
- 1788397185
- ISBN 13
- 9781788397186
- Item weight
- 634 grams
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 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.
Style and approach
Step by Step guide filled with real-world practical examples.
"Synopsis" may belong to another edition of this title.
About the Author
2005 implementation team as a joint management representative. Chintan has authored Hadoop Backup and Recovery Solutions and reviewed Liferay Portal Performance Best Practices and Building Serverless Web Applications.He has a Diploma in Computer Hardware and Network from a reputed institute in India.Kandarp Patel leads PHP practices at KNOWARTH Technologies. He has vast experience in providing end-to-end solutions in CMS, LMS, WCM, and e-commerce, along with various integrations for enterprise customers. He has over 9 years of rich experience in providing solutions in MySQL, MongoDB, and PHP-based frameworks. Kandarp is also a certified MongoDB and Magento developer.Kandarp has experience in various Enterprise Application development phases of the Software Development Life Cycle and has played prominent role in requirement gathering, architecture design, database design, application development, performance tuning, and CD/CI.Kandarp has a Bachelor of Engineering in Information Technology from a reputed university in India..
"About the title" may belong to another edition of this title.
Ria Christie Collections
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