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Mastering Apache Spark 2.x

You're reading from   Mastering Apache Spark 2.x Advanced techniques in complex Big Data processing, streaming analytics and machine learning

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Product type Paperback
Published in Jul 2017
Publisher Packt
ISBN-13 9781786462749
Length 354 pages
Edition 2nd Edition
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Author (1):
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Romeo Kienzler Romeo Kienzler
Author Profile Icon Romeo Kienzler
Romeo Kienzler
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Table of Contents (15) Chapters Close

Preface 1. A First Taste and What’s New in Apache Spark V2 2. Apache Spark SQL FREE CHAPTER 3. The Catalyst Optimizer 4. Project Tungsten 5. Apache Spark Streaming 6. Structured Streaming 7. Apache Spark MLlib 8. Apache SparkML 9. Apache SystemML 10. Deep Learning on Apache Spark with DeepLearning4j and H2O 11. Apache Spark GraphX 12. Apache Spark GraphFrames 13. Apache Spark with Jupyter Notebooks on IBM DataScience Experience 14. Apache Spark on Kubernetes

Importing and saving data

We wanted to add this section about importing and saving data here, even though it is not purely about Spark SQL, so that concepts such as Parquet and JSON file formats could be introduced. This section also allows us to cover how to access saved data in loose text as well as the CSV, Parquet, and JSON formats conveniently in one place.

Processing the text files

Using SparkContext, it is possible to load a text file in RDD using the textFile method. Additionally, the wholeTextFile method can read the contents of a directory to RDD. The following examples show you how a file, based on the local filesystem (file://) or HDFS (hdfs://), can be read to a Spark RDD. These examples show you that the data will...

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Mastering Apache Spark 2.x - Second Edition
Published in: Jul 2017
Publisher: Packt
ISBN-13: 9781786462749
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