Practical Real-time Data Processing and Analytics

Practical Real-time Data Processing and Analytics1787281205

Practical Real-time Data Processing and Analytics
by: Shilpi Saxena - Saurabh Gupta
ISBN-10 书号: 1787281205
ISBN-13 书号: 9781787281202
Release Finelybook 出版日期: 2017-10-10
pages 页数: 351


Book Description
A practical guide to help you tackle different real-time data processing and analytics problems using the best tools for each scenario
About This Book
Learn about the various challenges in real-time data processing and use the right tools to overcome them
This book covers popular tools and frameworks such as Spark,Flink,and Apache Storm to solve all your distributed processing problems
A practical guide filled with examples,tips,and tricks to help you perform efficient Big Data processing in real-time
Who This Book Is For
If you are a Java developer who would like to be equipped with all the tools required to devise an end-to-end practical solution on real-time data streaming,then this book is for you. Basic knowledge of real-time processing would be helpful,and knowing the fundamentals of Maven,Shell,and Eclipse would be great.
What You Will Learn
Get an introduction to the established real-time stack
Understand the key integration of all the components
Get a thorough understanding of the basic building blocks for real-time solution designing
Garnish the search and visualization aspects for your real-time solution
Get conceptually and practically acquainted with real-time analytics
Be well equipped to apply the knowledge and create your own solutions
In Detail
With the rise of Big Data,there is an increasing need to process large amounts of data continuously,with a shorter turnaround time. Real-time data processing involves continuous input,processing and output of data,with the condition that the time required for processing is as short as
Contents
Chapter 1. Introducing Real-Time Analytics
Chapter 2. Real Time Applications – The Basic Ingredients
Chapter 3. Understanding And Tailing Data Streams
Chapter 4. Setting Up The Infrastructure For Storm
Chapter 5. Configuring Apache Spark And Flink
Chapter 6. Integrating Storm With A Data Source
Chapter 7. From Storm To Sink
Chapter 8. Storm Trident
Chapter 9. Working With Spark
Chapter 10. Working With Spark Operations
Chapter 11. Spark Streaming
Chapter 12. Working With Apache Flink
Chapter 13. Case Study

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