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Big Data Analytics

You're reading from   Big Data Analytics Real time analytics using Apache Spark and Hadoop

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Product type Paperback
Published in Sep 2016
Publisher Packt
ISBN-13 9781785884696
Length 326 pages
Edition 1st Edition
Tools
Concepts
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Author (1):
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Venkat Ankam Venkat Ankam
Author Profile Icon Venkat Ankam
Venkat Ankam
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Table of Contents (12) Chapters Close

Preface 1. Big Data Analytics at a 10,000-Foot View 2. Getting Started with Apache Hadoop and Apache Spark FREE CHAPTER 3. Deep Dive into Apache Spark 4. Big Data Analytics with Spark SQL, DataFrames, and Datasets 5. Real-Time Analytics with Spark Streaming and Structured Streaming 6. Notebooks and Dataflows with Spark and Hadoop 7. Machine Learning with Spark and Hadoop 8. Building Recommendation Systems with Spark and Mahout 9. Graph Analytics with GraphX 10. Interactive Analytics with SparkR Index

Getting started with GraphX


You don't need any additional installation of software to get started with GraphX. GraphX is included within the Spark installation. This section introduces how to create and explore graphs using a simple family relationship graph. The family graph created will be used in all operations within this section.

Basic operations of GraphX

GraphX does not support the Python API yet. For easy understanding, let's use spark-shell to interactively work with GraphX. First of all, let's create input data (vertex and edge files) needed for our GraphX operations and then store it on HDFS.

Note

All programs in this chapter are executed on CDH 5.8 VM. For other environments, file paths might change, but the concepts are the same in any environment.

Creating a graph

We can create a graph using the following steps:

  1. Create a vertex file with vertex ID, name, and age as shown here:

    [cloudera@quickstart ~]$ cat vertex.csv
    1,Jacob,48
    2,Jessica,45
    3,Andrew,25
    4,Ryan,53
    5,Emily,22
    6,Lily,52...
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