Also the example of Jaccard that you had linked me to used VertexCentric configuration which I understand is because that api only uses VertexCentricIteration for all the operations? But I think that is the best way in order to know what neighbors belong to the BloomFilter?
On Mon, Jul 20, 2015 at 3:43 PM, Shivani Ghatge <shgha...@gmail.com> wrote: > Hello Vasia, > > As I had mentioned before, I need a BloomFilter as well as a HashSet for > the approximation to work. In the exact solution I am getting two HashSets > and comparing them. In approximate version, if we get two BloomFilters then > we have no way to compare the neighborhood sets. > > I thought we agreed that the BloomFilters are to be sent as messages to > the vertices? > > The exact version is passing all the tests. > > On removing the final GroupReduce the program is working but I need it to > add the Partial Adamic Adar edges weights. > > On Mon, Jul 20, 2015 at 3:15 PM, Vasiliki Kalavri < > vasilikikala...@gmail.com> wrote: > >> Hi Shivani, >> >> why are you using a vertex-centric iteration to compute the approximate >> Adamic-Adar? >> It's not an iterative computation :) >> >> In fact, it should be as complex (in terms of operators) as the exact >> Adamic-Adar, only more efficient because of the different neighborhood >> representation. Are you having the same problem with the exact computation? >> >> Cheers, >> Vasia. >> >> On 20 July 2015 at 14:41, Maximilian Michels <m...@apache.org> wrote: >> >>> Hi Shivani, >>> >>> The issue is that by the time the Hash Join is executed, the >>> MutableHashTable cannot allocate enough memory segments. That means that >>> your other operators are occupying them. It is fine that this also occurs >>> on Travis because the workers there have limited memory as well. >>> >>> Till suggested to change the memory fraction through the >>> ExuectionEnvironment. Can you try that? >>> >>> Cheers, >>> Max >>> >>> On Mon, Jul 20, 2015 at 2:23 PM, Shivani Ghatge <shgha...@gmail.com> >>> wrote: >>> >>>> Hello Maximilian, >>>> >>>> Thanks for the suggestion. I will use it to check the program. But when >>>> I am creating a PR for the same implementation with a Test, I am getting >>>> the same error even on Travis build. So for that what would be the >>>> solution? >>>> >>>> Here is my PR https://github.com/apache/flink/pull/923 >>>> And here is the Travis build status >>>> https://travis-ci.org/apache/flink/builds/71695078 >>>> >>>> Also on the IDE it is working fine in Collection execution mode. >>>> >>>> Thanks and Regards, >>>> Shivani >>>> >>>> On Mon, Jul 20, 2015 at 2:14 PM, Maximilian Michels <m...@apache.org> >>>> wrote: >>>> >>>>> Hi Shivani, >>>>> >>>>> Flink doesn't have enough memory to perform a hash join. You need to >>>>> provide Flink with more memory. You can either increase the >>>>> "taskmanager.heap.mb" config variable or set "taskmanager.memory.fraction" >>>>> to some value greater than 0.7 and smaller then 1.0. The first config >>>>> variable allocates more overall memory for Flink; the latter changes the >>>>> ratio between Flink managed memory (e.g. for hash join) and user memory >>>>> (for you functions and Gelly's code). >>>>> >>>>> If you run this inside an IDE, the memory is configured automatically >>>>> and you don't have control over that at the moment. You could, however, >>>>> start a local cluster (./bin/start-local) after you adjusted your >>>>> flink-conf.yaml and run your programs against that configured cluster. You >>>>> can do that either through your IDE using a RemoteEnvironment or by >>>>> submitting the packaged JAR to the local cluster using the command-line >>>>> tool (./bin/flink). >>>>> >>>>> Hope that helps. >>>>> >>>>> Cheers, >>>>> Max >>>>> >>>>> On Mon, Jul 20, 2015 at 2:04 PM, Shivani Ghatge <shgha...@gmail.com> >>>>> wrote: >>>>> >>>>>> Hello, >>>>>> I am working on a problem which implements Adamic Adar Algorithm >>>>>> using Gelly. >>>>>> I am running into this exception for all the Joins (including the one >>>>>> that are part of the reduceOnNeighbors function) >>>>>> >>>>>> Too few memory segments provided. Hash Join needs at least 33 memory >>>>>> segments. >>>>>> >>>>>> >>>>>> The problem persists even when I comment out some of the joins. >>>>>> >>>>>> Even after using edg = edg.join(graph.getEdges(), >>>>>> JoinOperatorBase.JoinHint.BROADCAST_HASH_SECOND).where(0,1).equalTo(0,1).with(new >>>>>> JoinEdge()); >>>>>> >>>>>> as suggested by @AndraLungu the problem persists. >>>>>> >>>>>> The code is >>>>>> >>>>>> >>>>>> DataSet<Tuple2<Long, Long>> degrees = graph.getDegrees(); >>>>>> >>>>>> //get neighbors of each vertex in the HashSet for it's value >>>>>> computedNeighbors = graph.reduceOnNeighbors(new >>>>>> GatherNeighbors(), EdgeDirection.ALL); >>>>>> >>>>>> //get vertices with updated values for the final Graph which >>>>>> will be used to get Adamic Edges >>>>>> Vertices = computedNeighbors.join(degrees, >>>>>> JoinOperatorBase.JoinHint.BROADCAST_HASH_FIRST).where(0).equalTo(0).with(new >>>>>> JoinNeighborDegrees()); >>>>>> >>>>>> Graph<Long, Tuple3<Double, HashSet<Long>, List<Tuple3<Long, >>>>>> Long, Double>>>, Double> updatedGraph = >>>>>> Graph.fromDataSet(Vertices, edges, env); >>>>>> >>>>>> //configure Vertex Centric Iteration >>>>>> VertexCentricConfiguration parameters = new >>>>>> VertexCentricConfiguration(); >>>>>> >>>>>> parameters.setName("Find Adamic Adar Edge Weights"); >>>>>> >>>>>> parameters.setDirection(EdgeDirection.ALL); >>>>>> >>>>>> //run Vertex Centric Iteration to get the Adamic Adar Edges >>>>>> into the vertex Value >>>>>> updatedGraph = updatedGraph.runVertexCentricIteration(new >>>>>> GetAdamicAdarEdges<Long>(), new NeighborsMessenger<Long>(), 1, >>>>>> parameters); >>>>>> >>>>>> //Extract Vertices of the updated graph >>>>>> DataSet<Vertex<Long, Tuple3<Double, HashSet<Long>, >>>>>> List<Tuple3<Long, Long, Double>>>>> vertices = >>>>>> updatedGraph.getVertices(); >>>>>> >>>>>> //Extract the list of Edges from the vertex values >>>>>> DataSet<Tuple3<Long, Long, Double>> edg = >>>>>> vertices.flatMap(new GetAdamicList()); >>>>>> >>>>>> //Partial weights for the edges are added >>>>>> edg = edg.groupBy(0,1).reduce(new AdamGroup()); >>>>>> >>>>>> //Graph is updated with the Adamic Adar Edges >>>>>> edg = edg.join(graph.getEdges(), >>>>>> JoinOperatorBase.JoinHint.BROADCAST_HASH_SECOND).where(0,1).equalTo(0,1).with(new >>>>>> JoinEdge()); >>>>>> >>>>>> Any idea how I could tackle this Exception? >>>>>> >>>>> >>>>> >>>> >>> >> >
