原文网址：http://www.cse.cuhk.edu.hk/~ericlo/teaching/bigdata/lab/9-Giraph/#execute

Apache Giraph

Introduction

Apache Giraph is an open-source and distributed graph processing system based on Google's Pregel. It adopts vertex-centric programming model and is implemented by re-using Hadoop MapReduce code base.

In this lab, we will teach you

How to install Giraph
How to write Giraph programs
How to execute Giraph programs on Apache Hadoop

Installing Giraph

Installing Giraph library

Please start up your virtual box and download the prepared Giraph libaray JAR giraph-core.jar.
After that, copy giraph-core.jar to ~/Programs/hadoop/share/hadoop/common/.

Dealing with Giraph's Bug

Giraph jobs were consistently hanging if the hostname includes uppercase letters (which is a known bug). Say if you are using our VirtualBox image, you need to

using sudo vim /etc/hostname to change the content of the file /etc/hostname from

to
using sudo vim /etc/hosts to change the content of the file /etc/hosts from

to
and restart the image.

<p></p>
<!-- 	<h3>Running a Giraph Example - SimpleInDegreeCountVertex</h3>
Up to now, all configurations are done. Since Giraph programs run on Hadoop MapReduce and HDFS, let's start them first. 
<pre>
	<code class="bash">

$ cd ~/Programs/hadoop-1.2.1/bin
$ ./start-all.sh

In giraph.zip, there is an example graph file - gr1.txt. Each line below has the format [source_id,source_value,[[dest_id, edge_value],…]]. You first upload gr1.txt to HDFS.





[0,0,[[1,1],[3,3]]]

[1,0,[[0,1],[2,2],[3,1]]]

[2,0,[[1,2],[4,4]]]

[3,0,[[0,3],[1,1],[4,4]]]

[4,0,[[3,4],[2,4]]]

Then, let’s try an example in Giraph - SimpleInDegreeCountVertex which computes the number of incoming edges for each vertex.





$ cd ~/giraph_lab/

Upload gr1.txt to HDFS

$ ~/Programs/hadoop-1.2.1/bin/hadoop fs -put gr1.txt /user/bigdata/giraph/input/

Execute Giraph examlpes

$ ~/Programs/hadoop-1.2.1/bin/hadoop jar giraph-examples.jar org.apache.giraph.GiraphRunner org.apache.giraph.examples.SimpleInDegreeCountVertex -vif org.apache.giraph.io.formats.JsonLongDoubleFloatDoubleVertexInputFormat -vip /user/bigdata/giraph/input/gr1.txt -of org.apache.giraph.io.formats.IdWithValueTextOutputFormat -op /user/bigdata/giraph/output -w 1

-->

Writing Giraph Programs

Similar to developing MapReduce programs, we use Eclipse IDE to
implement Giraph programs. Now, download our lab material giraph-lab.zip here and look at some
examples.

After importing the project, you will see 3 Java files in
src folder. Also, you will find giraph-core.jar, hadoop-common-2.6.3.jar and hadoop-mapreduce-client-core-2.6.3.jar
in lib folder. The first one is the Giraph core library while the
other two are Hadoop libraries (you met before in MapReduce Lab).

MaxVertexValue program

Let’s have a quick look at MaxVertexValue.java. Its code is
shown as below.

			

package example;

import java.io.IOException;

import org.apache.giraph.graph.Vertex;
import org.apache.giraph.graph.BasicComputation;
import org.apache.hadoop.io.DoubleWritable;
import org.apache.hadoop.io.FloatWritable;
import org.apache.hadoop.io.LongWritable;

/**
Vertex ID: LongWritable
Vertex value: DoubleWritable
Edge value: FloatWritable
Message: DoubleWritable

Assumption: 
1. The graph is strongly connected

*/
public class MaxVertexValue extends BasicComputation<LongWritable, DoubleWritable, FloatWritable, DoubleWritable> {
@Override
public void compute(Vertex<LongWritable, DoubleWritable, FloatWritable> vertex,
Iterable<DoubleWritable> messages) throws IOException {
boolean changed = false;

	for (DoubleWritable msg : messages) {
		/* Collect messages from in-neighbours and update if necessary */
		if ( vertex.getValue().get() &lt; msg.get() ) {
			vertex.setValue( new DoubleWritable( msg.get() ) );
			changed = true;
		}
	}
	
	/* Send the message to out-neighbours at Superstep 0 or Vertex value is changed */
	if ( getSuperstep() == 0 || changed ) {
		sendMessageToAllEdges(vertex, getValue());
	}		
	vertex.voteToHalt();
}

}

To use Giraph’s vertex-centric model, your class should extend org.apache.giraph.graph.BasicComputation<I, V, E, M> and implement compute() method.
The meanings of <I, V, E, M> are as follows.

I: Vertex ID

V: Vertex value

E: Edge value (edge weight)

M: Message

I, V, E, M should implement Writable
interface in Hadoop API.

For example, IntWritable, FloatWritable
are valid classes.

An important member function of BasicComputation class is getSuperstep(), which obtains the current step number. Note that it starts from zero.

As an argument of compute() method, vertex with type org.apache.giraph.graph.Vertex<I,V,E> has some useful functions:

setValue(): Modify the value of a vertex. The new
value takes effect immediately after calling this function.

sendMessageToAllEdges(): Intuitively, this sends a
message to all outgoing neighbors. If you send a message to a
specific neighbor, you can use sendMessage().

MaxVertexValue program aims to find out the maximum vertex
value among all vertices. Its main idea is as follows:

Superstep 0: A vertex sends its vertex
value to its out-neighbours.

Superstep > 0: Check if the incoming
messages are larger than its current value. If so, update its
current value and propagate the value to its out-neighbours.

Output: All vertices have the maximum
vertex value in the graph.

PageRank program

PageRank
algorithm is used by Google to rank search engine results.
PageRank represents the importance of a web page. PageRank
algorithm in vertex-centric implementation is as follows, assuming
we are given the maximum number of supersteps MAX_STEPS.

			

package example;

import java.io.IOException;

import org.apache.giraph.graph.Vertex;
import org.apache.hadoop.io.DoubleWritable;
import org.apache.hadoop.io.FloatWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.giraph.graph.BasicComputation;

public class PageRank extends BasicComputation<LongWritable, DoubleWritable, FloatWritable, DoubleWritable> {
/* Maximum number of iterations */
public final static long MAX_STEPS = 30;

@Override
public void compute(Vertex&lt;LongWritable, DoubleWritable, FloatWritable&gt; vertex,
	Iterable&lt;DoubleWritable&gt; messages) throws IOException {
	
	if (getSuperstep() &gt;= 1) {
		double sum = 0;
		/* Collect PageRank from in-neighbors */
		for (DoubleWritable msg : messages) {
			sum += msg.get();
		}
		
		/* Update PageRank */
		DoubleWritable vertexValue = 
			new DoubleWritable((0.15d / getTotalNumVertices()) + 0.85d * sum);
		vertex.setValue(vertexValue);
	}
	
	if (getSuperstep() &lt; MAX_STEPS) {
		/* Send updated PageRank to out-neighbors */
		sendMessageToAllEdges(vertex,
				new DoubleWritable(vertex.getValue().get() / vertex.getNumEdges()));
	} else {
		/* Stop */
		vertex.voteToHalt();
	}
}

}

The idea of PageRank:

Superstep 0: Disseminate vertex’s initial
value to its out-neighbours

0 < Superstep < MAX_STEPS: Update its
current PageRank and disseminate the value to its out-neighbours

Superstep >= MAX_STEPS : All vertices
are set to halt for termination

Executing Giraph Programs

Exporting Eclipse project to JAR

Export your project to a JAR with the following settings.

After that, copy your exported JAR giraph-lab.jar to ~/Programs/hadoop/share/hadoop/common.
This helps Hadoop to recognize your JAR.

Please download two example graph data files graph-data1.txt and graph-data2.txt.

They have the following format: Each line below has the
adjacency-list format [source_id,source_value,[[dest_id,edge_weight],[dest_id,edge_weight],…]].

This format is called JsonLongDoubleFloatDoubleVertexInputFormat.
The content of graph-data1.txt is as follows:

			

[0,100,[[1,1],[3,3]]]

[1,20,[[0,1],[2,2],[3,1]]]

[2,90,[[1,2],[4,4]]]

[3,50,[[0,3],[1,1],[4,4]]]

[4,80,[[3,4],[2,4]]]

For example, [2,90,[[1,2],[4,4]]] means Node 2 has vertex
value of 90. It has an edge to Node 1 with weight 2 and has another
edge to Node 4 with weight 4.

Now, you start Hadoop, upload graph-data1.txt to HDFS
and execute your Giraph programs.

Start Hadoop

$ cd ~/Programs/hadoop/sbin
$ ./start-all.sh
$ cd …/bin

Note: current directory is ~/Programs/hadoop/bin

Create folder in HDFS if not exist

$ ./hadoop fs -mkdir -p /user/bigdata/giraph/input

Upload graph-data1.txt to HDFS, assume it is at ~/

$ ./hadoop fs -put ~/graph-data1.txt /user/bigdata/giraph/input/graph-data1.txt

Execute Giraph program

$ ./hadoop jar …/share/hadoop/common/giraph-core.jar org.apache.giraph.GiraphRunner example.MaxVertexValue -vif org.apache.giraph.io.formats.JsonLongDoubleFloatDoubleVertexInputFormat -vip /user/bigdata/giraph/input/graph-data1.txt -vof org.apache.giraph.io.formats.IdWithValueTextOutputFormat -op /user/bigdata/giraph/output -w 1 -ca giraph.SplitMasterWorker=false

Display output file

$ ./hadoop fs -cat /user/bigdata/giraph/output/part-m-00000

Explanation:

org.apache.giraph.GiraphRunner: A Giraph Job Runner
that executes any BasicComputation class.

-vif: specifies the vertex input format, i.e., how
to read the graph file. JsonLongDoubleFloatDoubleVertexInputFormat
is one of the built-in input formats.

-vof: specifies the vertex output format, i.e., how
to write the output. IdWithValueTextOutputFormat is
one of the built-in output formats, which results in <VertexID, VertexValue> format line by line.

-vip/-op: Input/output paths.

-w: Number of workers used. A worker is a host that
performs the computation and stores data in HDFS. It can either
be a physical server or even a virtualized server.

-ca giraph.SplitMasterWorker=false: We have this setting
because our master and worker are in the same node.

Remarks

TextVertexInputFormat

TextVertexOutputFormat

org.apache.giraph.io.formats

The expected output of MaxVertexValue is

Executing PageRank

Let’s upload graph-data2.txt to HDFS and execute
PageRank. The expected output is as follows.

Exercise

Write a Giraph program that computes the in-degree of each
vertex.

We have prepared a Java file InDegreeCount.java in src
folder. Try to fill up the missing statements in compute()
method.

Code Snippet 1:

sendMessage(edge.getTargetVertexId(), new DoubleWritable(1.0));

Code Snippet 2:

sum++;

Giraph入门