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Apache Spark 2.x Cookbook

You're reading from   Apache Spark 2.x Cookbook Over 70 cloud-ready recipes for distributed Big Data processing and analytics

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Product type Paperback
Published in May 2017
Publisher
ISBN-13 9781787127265
Length 294 pages
Edition 1st Edition
Languages
Concepts
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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 (13) Chapters Close

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

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 1.8 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 of the heap:
       $ echo "export _JAVA_OPTIONS="-XX:MaxPermSize=1G""  >> 
/home/hduser/.bashrc
  1. Open a new terminal window and download the Spark source code from GitHub:
        $ wget https://github.com/apache/spark/archive/branch-2.1.zip
  1. Unpack the archive:
        $ unzip branch-2.1.zip
  1. Rename unzipped folder to spark:
        $ mv spark-branch-2.1 spark
  1. Move to the spark directory:
        $ cd spark
  1. Compile the sources with the YARN-enabled, Hadoop version 2.7, and Hive-enabled flags and skip the tests for faster compilation:
      $ mvn -Pyarn -Phadoop-2.7 -Dhadoop.version=2.7.0 -Phive -
DskipTests clean package
  1. Move the conf folder to the etc folder so that it can be turned into a symbolic link:
        $ sudo mv spark/conf /etc/
  1. Move the spark directory to /opt as it's an add-on software package:
        $ sudo mv spark /opt/infoobjects/spark
  1. Change the ownership of the spark home directory to root:
        $ sudo chown -R root:root /opt/infoobjects/spark
  1. Change the permissions of the spark home directory, namely 0755 = user:rwx group:r-x world:r-x:
        $ sudo chmod -R 755 /opt/infoobjects/spark
  1. Move to the spark home directory:
        $ cd /opt/infoobjects/spark
  1. Create a symbolic link:
        $ sudo ln -s /etc/spark conf
  1. Put the Spark executable in the path by editing .bashrc:
        $ echo "export PATH=$PATH:/opt/infoobjects/spark/bin" >> 
/home/hduser/.bashrc
  1. Create the log directory in /var:
        $ sudo mkdir -p /var/log/spark
  1. Make hduser the owner of Spark's log directory:
        $ sudo chown -R hduser:hduser /var/log/spark
  1. Create Spark's tmp directory:
        $ mkdir /tmp/spark
  1. 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
You have been reading a chapter from
Apache Spark 2.x Cookbook
Published in: May 2017
Publisher:
ISBN-13: 9781787127265
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