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Spark Cookbook

You're reading from   Spark Cookbook With over 60 recipes on Spark, covering Spark Core, Spark SQL, Spark Streaming, MLlib, and GraphX libraries this is the perfect Spark book to always have by your side

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Product type Paperback
Published in Jul 2015
Publisher
ISBN-13 9781783987061
Length 226 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 (14) Chapters Close

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

Loading data from HDFS using a custom InputFormat

Sometimes you need to load data in a specific format and TextInputFormat is not a good fit for that. Spark provides two methods for this purpose:

  • sparkContext.hadoopFile: This supports the old MapReduce API
  • sparkContext.newAPIHadoopFile: This supports the new MapReduce API

These two methods provide support for all of Hadoop's built-in InputFormats interfaces as well as any custom InputFormat.

How to do it...

We are going to load text data in key-value format and load it in Spark using KeyValueTextInputFormat:

  1. Create the currency directory by using the following command:
    $ mkdir currency
  2. Change the current directory to currency:
    $ cd currency
  3. Create the na.txt text file and enter currency values in key-value format delimited by tab (key: country, value: currency):
    $ vi na.txt
    United States of America        US Dollar
    Canada  Canadian Dollar
    Mexico  Peso
    

    You can create more files for each continent.

  4. Upload the currency folder to HDFS:
    $ hdfs dfs ...
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