Re: Too few memory segments provided exception
If it might help anyone else, I had a similar issue when running my unit tests, I could solve it by increasing memory of sbt export SBT_OPTS="-Xmx3G -XX:+UseConcMarkSweepGC -XX:+CMSClassUnloadingEnabled -Xss1G" -- Sent from: http://apache-flink-user-mailing-list-archive.2336050.n4.nabble.com/
Too few memory segments provided exception
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 DataSetTuple2Long, 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()); GraphLong, Tuple3Double, HashSetLong, ListTuple3Long, 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 GetAdamicAdarEdgesLong(), new NeighborsMessengerLong(), 1, parameters); //Extract Vertices of the updated graph DataSetVertexLong, Tuple3Double, HashSetLong, ListTuple3Long, Long, Double vertices = updatedGraph.getVertices(); //Extract the list of Edges from the vertex values DataSetTuple3Long, 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?
Re: Too few memory segments provided exception
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 DataSetTuple2Long, 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()); GraphLong, Tuple3Double, HashSetLong, ListTuple3Long, 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 GetAdamicAdarEdgesLong(), new NeighborsMessengerLong(), 1, parameters); //Extract Vertices of the updated graph DataSetVertexLong, Tuple3Double, HashSetLong, ListTuple3Long, Long, Double vertices = updatedGraph.getVertices(); //Extract the list of Edges from the vertex values DataSetTuple3Long, 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?
Re: Too few memory segments provided exception
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 DataSetTuple2Long, 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()); GraphLong, Tuple3Double, HashSetLong, ListTuple3Long, 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 GetAdamicAdarEdgesLong(), new NeighborsMessengerLong(), 1, parameters); //Extract Vertices of the updated graph DataSetVertexLong, Tuple3Double, HashSetLong, ListTuple3Long, Long, Double vertices = updatedGraph.getVertices(); //Extract the list of Edges from the vertex values DataSetTuple3Long, 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?
Re: Too few memory segments provided exception
I also questioned the vertex-centric approach before. The exact computation does not throw this exception so I guess adapting the approximate version will do the trick [I also suggested improving the algorithm to use less operators offline]. However, the issue still persists. We saw it in Affinity Propagation as well... So even if the problem will disappear for this example, I am curious how we should handle it in the future. 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 DataSetTuple2Long, 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()); GraphLong, Tuple3Double, HashSetLong, ListTuple3Long, 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 GetAdamicAdarEdgesLong(), new NeighborsMessengerLong(), 1, parameters); //Extract Vertices of the updated graph DataSetVertexLong, Tuple3Double, HashSetLong, ListTuple3Long, Long, Double vertices = updatedGraph.getVertices(); //Extract the list of Edges from the vertex values
Re: Too few memory segments provided exception
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 DataSetTuple2Long, 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()); GraphLong, Tuple3Double, HashSetLong, ListTuple3Long, 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 GetAdamicAdarEdgesLong(), new NeighborsMessengerLong(), 1, parameters); //Extract Vertices of the updated graph DataSetVertexLong, Tuple3Double, HashSetLong, ListTuple3Long, Long, Double vertices = updatedGraph.getVertices(); //Extract the list of Edges from the vertex values DataSetTuple3Long, 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?
Re: Too few memory segments provided exception
The taskmanager.memory.fraction you can also set from within the IDE by giving the corresponding configuration object to the LocalEnvironment using the setConfiguration method. However, the taskmanager.heap.mb is basically the -Xmx value with which you start your JVM. Usually, you can set this in your program run settings. Cheers, Till 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 DataSetTuple2Long, 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()); GraphLong, Tuple3Double, HashSetLong, ListTuple3Long, 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 GetAdamicAdarEdgesLong(), new NeighborsMessengerLong(), 1, parameters); //Extract Vertices of the updated graph DataSetVertexLong, Tuple3Double, HashSetLong, ListTuple3Long, Long, Double vertices = updatedGraph.getVertices(); //Extract the list of Edges from the vertex values DataSetTuple3Long, 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?
Re: Too few memory segments provided exception
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 DataSetTuple2Long, 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()); GraphLong, Tuple3Double, HashSetLong, ListTuple3Long, 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 GetAdamicAdarEdgesLong(), new NeighborsMessengerLong(), 1, parameters); //Extract Vertices of the updated graph DataSetVertexLong, Tuple3Double, HashSetLong, ListTuple3Long, Long, Double vertices = updatedGraph.getVertices(); //Extract the list of Edges from the vertex values DataSetTuple3Long, 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?
Re: Too few memory segments provided exception
BTW we should add an entry for this to the faq and point to the configuration or faq entry in the exception message. On 20 Jul 2015, at 15:15, 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 DataSetTuple2Long, 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()); GraphLong, Tuple3Double, HashSetLong, ListTuple3Long, 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 GetAdamicAdarEdgesLong(), new NeighborsMessengerLong(), 1, parameters); //Extract Vertices of the updated graph DataSetVertexLong, Tuple3Double, HashSetLong, ListTuple3Long, Long, Double vertices = updatedGraph.getVertices(); //Extract the list of Edges from the vertex values DataSetTuple3Long, Long, Double edg = vertices.flatMap(new GetAdamicList()); //Partial weights for the edges are added edg = edg.groupBy(0,1).reduce(new AdamGroup()); //Graph is
Re: Too few memory segments provided exception
I believe there was some work in progress to reduce memory fragmentation and solve similar problems. Anyone knows what's happening with that? On 20 July 2015 at 16:29, Andra Lungu lungu.an...@gmail.com wrote: I also questioned the vertex-centric approach before. The exact computation does not throw this exception so I guess adapting the approximate version will do the trick [I also suggested improving the algorithm to use less operators offline]. However, the issue still persists. We saw it in Affinity Propagation as well... So even if the problem will disappear for this example, I am curious how we should handle it in the future. 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 DataSetTuple2Long, 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()); GraphLong, Tuple3Double, HashSetLong, ListTuple3Long, 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 GetAdamicAdarEdgesLong(), new NeighborsMessengerLong(), 1, parameters); //Extract
Re: Too few memory segments provided exception
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 DataSetTuple2Long, 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()); GraphLong, Tuple3Double, HashSetLong, ListTuple3Long, 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 GetAdamicAdarEdgesLong(), new NeighborsMessengerLong(), 1, parameters); //Extract Vertices of the updated graph DataSetVertexLong, Tuple3Double, HashSetLong, ListTuple3Long, Long, Double
Re: Too few memory segments provided exception
But it will need to build BloomFilters for each vertex for each edge so idk how efficient that would be. On Mon, Jul 20, 2015 at 4:02 PM, Shivani Ghatge shgha...@gmail.com wrote: Hello Vasia, I will adapt the exact method for BloomFilter. (I think it can be done. Sorry. My mistake). On Mon, Jul 20, 2015 at 3:45 PM, Shivani Ghatge shgha...@gmail.com wrote: 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 DataSetTuple2Long, 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()); GraphLong,
Re: Too few memory segments provided exception
Hi Shivani, the Jaccard example is implemented in Giraph, and therefore uses iterations. However, in Gelly we are not forced to do that for non-iterative computations. I see that there is some confusion with the implementation specifics. Let me try to write down some skeleton code / detailed description on how to do this properly in Gelly and let's move this discussion to the corresponding issue. Cheers, -Vasia. On 20 July 2015 at 16:45, Shivani Ghatge shgha...@gmail.com wrote: 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 DataSetTuple2Long, 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,
