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Practical Real-time Data Processing and Analytics

You're reading from   Practical Real-time Data Processing and Analytics Distributed Computing and Event Processing using Apache Spark, Flink, Storm, and Kafka

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Product type Paperback
Published in Sep 2017
Publisher Packt
ISBN-13 9781787281202
Length 360 pages
Edition 1st Edition
Languages
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Authors (2):
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Shilpi Saxena Shilpi Saxena
Author Profile Icon Shilpi Saxena
Shilpi Saxena
Saurabh Gupta Saurabh Gupta
Author Profile Icon Saurabh Gupta
Saurabh Gupta
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Table of Contents (14) Chapters Close

Preface 1. Introducing Real-Time Analytics FREE CHAPTER 2. Real Time Applications – The Basic Ingredients 3. Understanding and Tailing Data Streams 4. Setting up the Infrastructure for Storm 5. Configuring Apache Spark and Flink 6. Integrating Storm with a Data Source 7. From Storm to Sink 8. Storm Trident 9. Working with Spark 10. Working with Spark Operations 11. Spark Streaming 12. Working with Apache Flink 13. Case Study

NRT – technology view

In this section, we introduce you to various technological choices for NRT components and their pros and cons in certain situations. As the book progresses, we will revisit this section in more detail to help you understand why certain tools and stacks are better suited to solving certain use cases.

Before moving on, it's very important to understand the key aspects against which all the tools and technologies are generally evaluated. The aspects mentioned here are generic to software, we move on to the specifics of NRT tools later:

  • Performance: This is basically gauging the performance of the software component on a given set of hardware at a given load.
  • Capacity: This is a very crucial aspect because it decides the breaking point for any application.
  • Management: How easy or cumbersome is the management of the component? Would I need specialized...
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