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Big Data Analytics with Hadoop 3

You're reading from   Big Data Analytics with Hadoop 3 Build highly effective analytics solutions to gain valuable insight into your big data

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Product type Paperback
Published in May 2018
Publisher Packt
ISBN-13 9781788628846
Length 482 pages
Edition 1st Edition
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Author (1):
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Sridhar Alla Sridhar Alla
Author Profile Icon Sridhar Alla
Sridhar Alla
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Table of Contents (13) Chapters Close

Preface 1. Introduction to Hadoop FREE CHAPTER 2. Overview of Big Data Analytics 3. Big Data Processing with MapReduce 4. Scientific Computing and Big Data Analysis with Python and Hadoop 5. Statistical Big Data Computing with R and Hadoop 6. Batch Analytics with Apache Spark 7. Real-Time Analytics with Apache Spark 8. Batch Analytics with Apache Flink 9. Stream Processing with Apache Flink 10. Visualizing Big Data 11. Introduction to Cloud Computing 12. Using Amazon Web Services

Real-Time Analytics with Apache Spark

In this chapter, we will introduce the stream-processing model of Apache Spark, and show you how to build streaming-based, real-time analytical applications. This chapter will focus on Spark Streaming, and will show you how to process data streams using the Spark API.

More specifically, the reader will learn how to process Twitter's tweets, as well as how to process real-time data streams in several ways. Basically, the chapter will focus on the following:

  • A short introduction to streaming
  • Spark Streaming
  • Discretized Streams
  • Stateful and stateless transformations
  • Checkpointing
  • Operating with other streaming platforms (such as Apache Kafka)
  • Structured Streaming
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