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Apache Spark 2.x Cookbook

You're reading from   Apache Spark 2.x Cookbook Over 70 cloud-ready recipes for distributed Big Data processing and analytics

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Product type Paperback
Published in May 2017
Publisher
ISBN-13 9781787127265
Length 294 pages
Edition 1st Edition
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Author (1):
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Rishi Yadav Rishi Yadav
Author Profile Icon Rishi Yadav
Rishi Yadav
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Table of Contents (13) Chapters Close

Preface 1. Getting Started with Apache Spark FREE CHAPTER 2. Developing Applications with Spark 3. Spark SQL 4. Working with External Data Sources 5. Spark Streaming 6. Getting Started with Machine Learning 7. Supervised Learning with MLlib — Regression 8. Supervised Learning with MLlib — Classification 9. Unsupervised Learning 10. Recommendations Using Collaborative Filtering 11. Graph Processing Using GraphX and GraphFrames 12. Optimizations and Performance Tuning

Spark Streaming

Spark Streaming adds the holy grail of big data processing—that is, real-time analytics—to Apache Spark. It enables Spark to ingest live data streams and provides real-time intelligence at a very low latency of a few seconds.

In this chapter, we are going to cover the following recipes:

  • WordCount using Structured Streaming
  • Diving into Structured Streaming
  • Streaming Twitter data
  • Streaming using Kafka
  • Understanding streaming challenges
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