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https://issues.apache.org/jira/browse/TINKERPOP3-498?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Marko A. Rodriguez closed TINKERPOP3-498.
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Resolution: Won't Fix
This is crazy talk. Its cool, but I think we will keep
{{PageRankVertexProgram}} around given that it provides both an algorithm
people use and a template to study for building other {{VertexProgram}}s.
> Could we get rid of PageRankVertexProgram? -- is everything just
> TraversalVertexProgram?
> ----------------------------------------------------------------------------------------
>
> Key: TINKERPOP3-498
> URL: https://issues.apache.org/jira/browse/TINKERPOP3-498
> Project: TinkerPop 3
> Issue Type: Improvement
> Components: process
> Affects Versions: 3.0.2-incubating
> Reporter: Marko A. Rodriguez
> Assignee: Marko A. Rodriguez
>
> There is the notion of a message in {{GraphComputer}}. A {{Traverser}} is
> sufficiently complex to represent any message (i.e. {{Traverser.get()}}).
> Next, the {{MessageCombiner}} is simply {{Traverser.merge()}}. Next, is
> {{PageRankVertexProgram}} (and others) simply a combination of {{Steps}} to
> execute via a {{TraversalVertexProgram}}.
> Look at the {{execute()}} method of {{PageRankVertexProgram}}:
> {code:java}
> @Override
> public void execute(final Vertex vertex, Messenger<Double> messenger,
> final Memory memory) {
> if (memory.isInitialIteration()) {
> messenger.sendMessage(this.countMessageScope, 1.0d);
> } else if (1 == memory.getIteration()) {
> double initialPageRank = 1.0d / this.vertexCountAsDouble;
> double edgeCount =
> StreamFactory.stream(messenger.receiveMessages(this.countMessageScope)).reduce(0.0d,
> (a, b) -> a + b);
> vertex.singleProperty(PAGE_RANK, initialPageRank);
> vertex.singleProperty(EDGE_COUNT, edgeCount);
> messenger.sendMessage(this.incidentMessageScope, initialPageRank
> / edgeCount);
> } else {
> double newPageRank =
> StreamFactory.stream(messenger.receiveMessages(this.incidentMessageScope)).reduce(0.0d,
> (a, b) -> a + b);
> newPageRank = (this.alpha * newPageRank) + ((1.0d - this.alpha) /
> this.vertexCountAsDouble);
> vertex.singleProperty(PAGE_RANK, newPageRank);
> messenger.sendMessage(this.incidentMessageScope, newPageRank /
> vertex.<Double>value(EDGE_COUNT));
> }
> }
> {code}
> Lets see what that looks like as a pure Gremlin play:
> {code:java}
> __.in().fold(0,(a,b) -> a+b).sideEffect(count ->
> count.sideEffect('count',count.get())).repeat(
> __.fold(0,(a,b)->a+b)
> .sideEffect(pageRank ->
> pageRank.sideEffect('pageRank',pageRank.get()))
> .map(pageRank -> pageRank.get() / pageRank.sideEffect('count'))
> .out()).times(30)
> {code}
> In essence, the first line of the traversal gets the edge counts. The
> {{repeat()}}-traversal aggregates the incoming pageRank values, sets the
> vertex's current pageRank value, divides the pageRank value by the number of
> edges, and splits that traverser amongst all the outgoing edges. It does this
> 30 times.
> In this way, all that needs to exist is {{TraversalVertexProgram}}. Moreover,
> its all just Gremlin. Of course, we can canned algorithms, e.g.:
> {code:java}
> public Algorithms {
> public static final Traversal<Vertex,Vertex> PAGE_RANK =
> __.in().fold(0,(a,b) -> a+b).sideEffect(count ->
> count.sideEffect('count',p.get())).repeat(
> __.fold(0,(a,b)->a+b)
> .sideEffect(pageRank ->
> pageRank.sideEffect('pageRank',pageRank.get()))
> .map(pageRank -> pageRank.get() / pageRank.sideEffect('count'))
> .out()).times(30);
> public static final Traversal<Vertex,Vertex> ANOTHER_ALGORITHM = ...
> }
> {code}
> This is pretty insane.
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