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Fast Data Processing with Spark 2 - Third Edition by Krishna Sankar

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Algorithms

Now we dive into the most interesting part of GraphX: algorithms and the graph parallel computation APIs to implement more algorithms. The following table shows a bird's eye view of the algorithms:

Type

GraphX method/example

Graph-Parallel Computation

The method is aggregateMessages(), Function

Pregel(). Refer to https://issues.apache.org/jira/browse/SPARK-5062 for examples.

PageRank

The method is PageRank(). As an example, refer to the influential papers in a citation network, Influencer in retweet. You can specifically check out the following:

staticPageRank(): This provides a static no of iterations and dynamic tolerance; see the parameters (tol versus numIter)

personalizedPageRank(): This is a variation of PageRank that ...

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