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Hadoop Real-World Solutions Cookbook- Second Edition

You're reading from   Hadoop Real-World Solutions Cookbook- Second Edition Over 90 hands-on recipes to help you learn and master the intricacies of Apache Hadoop 2.X, YARN, Hive, Pig, Oozie, Flume, Sqoop, Apache Spark, and Mahout

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Product type Paperback
Published in Mar 2016
Publisher
ISBN-13 9781784395506
Length 290 pages
Edition 2nd Edition
Tools
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Author (1):
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Tanmay Deshpande Tanmay Deshpande
Author Profile Icon Tanmay Deshpande
Tanmay Deshpande
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Table of Contents (12) Chapters Close

Preface 1. Getting Started with Hadoop 2.X FREE CHAPTER 2. Exploring HDFS 3. Mastering Map Reduce Programs 4. Data Analysis Using Hive, Pig, and Hbase 5. Advanced Data Analysis Using Hive 6. Data Import/Export Using Sqoop and Flume 7. Automation of Hadoop Tasks Using Oozie 8. Machine Learning and Predictive Analytics Using Mahout and R 9. Integration with Apache Spark 10. Hadoop Use Cases Index

Running Spark standalone


Spark can be executed in various modes. To get started, we are going to take a look at how to install Apache Spark on a standalone machine.

Getting ready

To perform this recipe, you should download the latest version of Spark. For this recipe, I am using Apache Spark 1.6.0. You can visit the download page at http://spark.apache.org/downloads.html.

How to do it...

Apache Spark is a computation engine. It has a built-in cluster manager. It can also use other cluster managers such as YARN/Mesos and so on. In this recipe, we are going to use the built-in resource manager that's provided by Spark:

  1. Copy the downloaded Spark binary to a desired location.

  2. Extract the tar ball:

    $sudo tar –xzfspark-1.6.0-bin-hadoop2.6.tgz
    
  3. Rename the spark folder for ease of use:

    $sudo mv spark-1.6.0-bin-hadoop2.6 spark
    
  4. Add environment variables in ~/.bashrc:

    export SPARK_HOME=/usr/local/spark
    export PATH=$PATH:$SPARK_HOME/bin
  5. Source ~/.bashrc to make the changes effective:

    $source ~/.bashrc
    
  6. In case you...

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