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Learning Apache Spark 2

You're reading from   Learning Apache Spark 2 A beginner's guide to real-time Big Data processing using the Apache Spark framework

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Product type Paperback
Published in Mar 2017
Publisher Packt
ISBN-13 9781785885136
Length 356 pages
Edition 1st Edition
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Author (1):
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Muhammad Asif Abbasi Muhammad Asif Abbasi
Author Profile Icon Muhammad Asif Abbasi
Muhammad Asif Abbasi
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Table of Contents (12) Chapters Close

Preface 1. Architecture and Installation FREE CHAPTER 2. Transformations and Actions with Spark RDDs 3. ETL with Spark 4. Spark SQL 5. Spark Streaming 6. Machine Learning with Spark 7. GraphX 8. Operating in Clustered Mode 9. Building a Recommendation System 10. Customer Churn Prediction Theres More with Spark

Commonly Supported File Formats

We've already seen the ease with which you can manipulate text files using Spark with the textFile() method on SparkContext. However, you'll be pleased to know that Apache Spark supports a large number of other formats, which are increasing with every release of Spark. With Apache Spark release 2.0, the following file formats are supported out of the box:

  • TextFiles (already covered)
  • JSON files
  • CSV Files
  • Sequence Files
  • Object Files

Text Files

We've already seen various examples in Chapter 1, Architecture and Installation and Chapter 2, Transformations and Actions with Spark RDDs on how to read text files using the textFile() function. Each line in the text file is assumed to be a new record. We've also seen examples of wholeTextFiles(), which return a PairRDD, with the key being the identifier of the file. This is very useful in ETL jobs, where you might want to process data differently based on the key, or even pass that on...

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