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Mastering Apache Spark 2.x - Second Edition

You're reading from Mastering Apache Spark 2.x - Second Edition

Product type Book

Published in Jul 2017

Publisher Packt

ISBN-13 9781786462749

Pages 354 pages

Edition 2nd Edition

Languages

Concepts

Table of Contents (21) Chapters

Title Page

Credits

About the Author

About the Reviewer

www.PacktPub.com

Customer Feedback

Preface

1. A First Taste and What’s New in Apache Spark V2

2. Apache Spark SQL

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

Understanding the DataSource API

The DataSource API was introduced in Apache Spark 1.1, but is constantly being extended. You have already used the DataSource API without knowing when reading and writing data using SparkSession or DataFrames.

The DataSource API provides an extensible framework to read and write data to and from an abundance of different data sources in various formats. There is built-in support for Hive, Avro, JSON, JDBC, Parquet, and CSV and a nearly infinite number of third-party plugins to support, for example, MongoDB, Cassandra, ApacheCouchDB, Cloudant, or Redis.

Usually, you never directly use classes from the DataSource API as they are wrapped behind the read method of SparkSession or the write method of the DataFrame or Dataset. Another thing that is hidden from the user is schema discovery.

Implicit schema discovery

One important aspect of the DataSource API is implicit schema discovery. For a subset of data sources, implicit schema discovery is possible. This means...

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