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Use Big data tools such as Vertica, Hadoop and PIG to count triangles in a graph. Experimentally compare their performance.

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README
This is a benchmark on an important graph analytics use case --
triangle counting. Read this blog post first (TBD) for the background
description.

We have provided the solutions in Hadoop, PIG and Vertica. You will be
able to test the Hadoop and PIG solutions on the data sets that we
provide. When the Vertica Community Edition is released, you will be
able to test the Vertica solution as well.

********************************************************************************
** CONTENTS
********************************************************************************
README
    This file.

build.xml
    makefile for ant.

input/few-edges.txt
    Sample graph file, contains 36 reciprocal edges and six triangles. This is
    an example of the input format required by the following three solutions.
    Edges must be {source:long, dest:long} pairs and each edge must have a
    reciprocal edges (that is, there must exist a {dest, source}). The input
    format is:
      <long> <whitespace> <long> <newline>
      <repeat>

scripts/triangle_counter.sql
    Vertica script to create an edges table, load data (from 'input/few-edges.txt'
    by default) and execute a query that computes the number of triangles in
    the corresponding graph.

scripts/triangle_counter.pig
    PIG script that computes the number of triangles in a graph. The input is an
    edges file (described above) and the output is the number of triangles.

src/com/vertica/mr/graphs/TriangleCounter.java
    MapReduce code that runs in Hadoop and counts the number of triangles in
    a graph. The input is an edges file (described above) and the output is the
    number of triangles.

third-party/pig/pig-0.8.1.tar.gz
    PIG libraries included for convenience.

third-party/hadoop/hadoop-0.20.2.tar.gz
    Hadoop libraries included for convenience.


********************************************************************************
** REQUIREMENTS
********************************************************************************

* Java 6. Please make sure it is in your path and JAVA_HOME is set correctly.

* Ant 1.6.5 or higher.


********************************************************************************
** EXAMPLES
********************************************************************************
Here are the basics. See the build.xml for other targets and full details.

Hadoop:

The following command, when executed from the base directory, runs the hadoop
solution (in standalone mode) on the input/few-edges.txt file and outputs the
result to the ant output, as well as a directory named "result".

  $ ant triangle-counter-standalone


PIG:

The following command, when executed from the base directory, runs the PIG
solution (in local mode) on the input/few-edges.txt file and outputs the result
to the ant output.

  $ ant pig-triangle-counter-local

********************************************************************************
** PERFORMANCE TESTING
********************************************************************************
Our performance study is based on an input data set of 1.3GB in
size. That data set can be downloaded here:
http://www.vertica.com/benchmark/TriangleCounting/edges.txt.gz

You are welcome to download and use it for your own testing.

Note that the above ant commands use a single-instance setup, and are
unsuitable for large-scale performance testing. The performance
results reported in our blog post are done on a 4-node cluster, where
each node has 12 cores, 96GB of RAM and 10GBit internconnect. The
hardware power is equivalent to 4 nodes from the HP Vertica Analytics
appliance:
http://h18006.www1.hp.com/storage/server-solutions/vertica-analytics-overview.html
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