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README.md

Parallel SimRank Algorithm

Uses the Delta-Simrank Algorithm (http://dprg.cs.uiuc.edu/docs/deltasimrank/simrank.pdf).

Takes advantage of Spark's GraphX framework and in-memory/iterative computation advantage over other MapReduce frameworks such as YARN by performing each SimRank iteration as a triple of Map and two Reduce tasks.

Map1 : Emit key value pairs where each key is a pair of vertex ids adjacent to the vertices with updated scores in the previous iterations, and the value is the marginal increase in SimRank (refer to the delta-simrank algorithm for exact calculation method for deltas).

Reduce1 : Aggregate delta values by key.

Reduce2 : Add the delta to the previous iteration SimRank score to get the current iteration's SimRank score.

Prerequisite: GraphX package.

Parameter Explained

datasource - graphEdgelistPath : The edge-list passed to GraphX's graph loader. For efficient memory storage of intermediate SimRank score calculations, the vertex ids should be in a contiguous range from 0 to (#Vertex-1). There is a utility function for re-mapping the vertex Id values : io.prediction.examples.pfriendrecommendation.DeltaSimRankRDD.normalizeGraph.

algorithms - numIterations : Number of iterations for calculating SimRank. Typical recommended is 6-8 in various papers (e.g. http://www-cs-students.stanford.edu/~glenj/simrank.pdf)

algorithms - decay : Decay constant used in calculating incremental changes to SimRank

Configurable Datasources for Sampling

Three data sources can be configured from the engine factory :

DataSource generates a GraphX graph using the entire dataset.

NodeSamplingDataSource generates a GraphX graph after performing node sampling with induced edges between the sampled nodes. This data source takes an additional parameter, sampleFraction, which is the fraction of graph nodes to sample.

ForestFireSamplingDataSource generates a graph after performing forest fire sampling. This sampling method also uses the sampleFraction parameter and takes an additional parameter, geoParam, which is the parameter for a geometric distribution that is used within forest fire sampling.

Example query

curl -H "Content-Type: application/json" -d '{"item1":0, "item2":2}' http://localhost:8000/queries.json

This queries the SimRank score between nodes with ids 0 and 2,