#### Description

This patch an extension based on my paper, From "Think Like a Vertex" to "Think Like a Graph", published in PVLDB 2013 (http://researcher.watson.ibm.com/researcher/files/us-ytian/giraph++.pdf).

The basic motivation is as follows. Giraphs divides input graphs into partitions, and employs a “think like a vertex" programming model to support iterative graph computation. This vertex-centric model is easy to program and has been proved useful for many graph algorithms. However, this model hides the partitioning information from the users, thus prevents many algorithm-specific optimizations. This often results in longer execution time due to excessive network messages. To address this limitation, we propose a new “think like a graph" programming paradigm. Under this graph-centric model, the partition structure is opened up to the users, and can be utilized so that communication within a partition can bypass the heavy message passing. For example, on a web graph with 118 million vertices and 855 million edges, the graph-centric version of connected component detection algorithm runs 63X faster and uses 204X fewer network messages than its vertex-centric counterpart. For more details of this new model, please refer to the paper.

Note that since the work is done last year, the extension is based on an old version of Giraph downloaded in June 2012. So, the patch essential rolls back all the changes in Giraph since June 2012. Performing a diff with a June 2012 version of Giraph will show what changes I made to support the extension.

To compile the code, simply run “mvn compile”, then the jar file named giraph-0.2-SNAPSHOT-jar-with-dependencies.jar is generated under the target directory. Also note that while I was creating the patch and run “mvn clean verify”, testBspPageRank and testBspPageRankWithAggregatorWriter failed.

In this patch, I also included 4 example algorithms to test the new graph-centric model. To test-run these examples, please download the two example graphs: enron.tgz (the enron email graph) and enron_undirected.tgz (an undirected version of the enron graph). Unzip them and put them on hdfs. Then these are the command to run the tests:

- compute the NCut amd Imbalande factor of a partitioning scheme

hadoop-0.20.203.0/bin/hadoop jar giraph-0.2-SNAPSHOT-jar-with-dependencies.jar com.ibm.giraph.graph.example.NCut enron 7 true 7 output

- weakly connected component on an undirected graph
- the graph-centric model

hadoop-0.20.203.0/bin/hadoop jar giraph-0.2-SNAPSHOT-jar-with-dependencies.jar com.ibm.giraph.graph.example.wcc.WCCGraph enron_undirected out 7 true 7

the hybrid model

hadoop-0.20.203.0/bin/hadoop jar giraph-0.2-SNAPSHOT-jar-with-dependencies.jar com.ibm.giraph.graph.example.wcc.WCCVertex enron_undirected out 7 true 7 true - the basic vertex-centric model

hadoop-0.20.203.0/bin/hadoop jar giraph-0.2-SNAPSHOT-jar-with-dependencies.jar com.ibm.giraph.graph.example.wcc.WCCVertex enron_undirected out 7 true 7 false

- pagerank on a directed graph
- the graph-centric model

hadoop-0.20.203.0/bin/hadoop jar giraph-0.2-SNAPSHOT-jar-with-dependencies.jar com.ibm.giraph.graph.example.pagerank.DeltaPRGraph enron output 7 true 7 - the hybrid model

hadoop-0.20.203.0/bin/hadoop jar giraph-0.2-SNAPSHOT-jar-with-dependencies.jar com.ibm.giraph.graph.example.pagerank.DeltaPRVertex enron output 7 true 7 true - the vertex-centric model

hadoop-0.20.203.0/bin/hadoop jar giraph-0.2-SNAPSHOT-jar-with-dependencies.jar com.ibm.giraph.graph.example.pagerank.DeltaPRVertex enron output 7 true 7 false

- graph coarsening on an undirected graph
- the graph-centric model

hadoop-0.20.203.0/bin/hadoop jar giraph-0.2-SNAPSHOT-jar-with-dependencies.jar com.ibm.giraph.graph.example.coarsen.CoarsenGraph enron_undirected 7 output 7 - the vertex-centricl mdoel

hadoop-0.20.203.0/bin/hadoop jar giraph-0.2-SNAPSHOT-jar-with-dependencies.jar com.ibm.giraph.graph.example.coarsen.CoarsenVertex enron_undirected 7 output 7