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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

Building the Spark source code with Maven

Installing Spark using binaries works fine in most cases. For advanced cases, such as the following (but not limited to), compiling from the source code is a better option:

  • Compiling for a specific Hadoop version
  • Adding the Hive integration
  • Adding the YARN integration

Getting ready

The following are the prerequisites for this recipe to work:

  • Java 1.6 or a later version
  • Maven 3.x

How to do it...

The following are the steps to build the Spark source code with Maven:

  1. Increase MaxPermSize for heap:
    $ echo "export _JAVA_OPTIONS=\"-XX:MaxPermSize=1G\""  >> /home/hduser/.bashrc
    
  2. Open a new terminal window and download the Spark source code from GitHub:
    $ wget https://github.com/apache/spark/archive/branch-1.4.zip
    
  3. Unpack the archive:
    $ gunzip branch-1.4.zip
    
  4. Move to the spark directory:
    $ cd spark
    
  5. Compile the sources with these flags: Yarn enabled, Hadoop version 2.4, Hive enabled, and skipping tests for faster compilation:
    $ mvn -Pyarn -Phadoop-2.4 -Dhadoop.version=2.4.0 -Phive -DskipTests clean package
    
  6. Move the conf folder to the etc folder so that it can be made a symbolic link:
    $ sudo mv spark/conf /etc/
    
  7. Move the spark directory to /opt as it's an add-on software package:
    $ sudo mv spark /opt/infoobjects/spark
    
  8. Change the ownership of the spark home directory to root:
    $ sudo chown -R root:root /opt/infoobjects/spark
    
  9. Change the permissions of the spark home directory 0755 = user:rwx group:r-x world:r-x:
    $ sudo chmod -R 755 /opt/infoobjects/spark
    
  10. Move to the spark home directory:
    $ cd /opt/infoobjects/spark
    
  11. Create a symbolic link:
    $ sudo ln -s /etc/spark conf
    
  12. Put the Spark executable in the path by editing .bashrc:
    $ echo "export PATH=$PATH:/opt/infoobjects/spark/bin" >> /home/hduser/.bashrc
    
  13. Create the log directory in /var:
    $ sudo mkdir -p /var/log/spark
    
  14. Make hduser the owner of the Spark log directory:
    $ sudo chown -R hduser:hduser /var/log/spark
    
  15. Create the Spark tmp directory:
    $ mkdir /tmp/spark
    
  16. Configure Spark with the help of the following command lines:
    $ cd /etc/spark
    $ echo "export HADOOP_CONF_DIR=/opt/infoobjects/hadoop/etc/hadoop" >> spark-env.sh
    $ echo "export YARN_CONF_DIR=/opt/infoobjects/hadoop/etc/Hadoop" >> spark-env.sh
    $ echo "export SPARK_LOG_DIR=/var/log/spark" >> spark-env.sh
    $ echo "export SPARK_WORKER_DIR=/tmp/spark" >> spark-env.sh
    
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