Re: [GraphX] how to set memory configurations to avoid OutOfMemoryError GC overhead limit exceeded

2014-09-09 Thread Ankur Dave
At 2014-09-05 12:13:18 +0200, Yifan LI iamyifa...@gmail.com wrote: But how to assign the storage level to a new vertices RDD that mapped from an existing vertices RDD, e.g. *val newVertexRDD = graph.collectNeighborIds(EdgeDirection.Out).map{case(id:VertexId, a:Array[VertexId]) = (id,

Re: [GraphX] how to set memory configurations to avoid OutOfMemoryError GC overhead limit exceeded

2014-09-05 Thread Yifan LI
Thank you, Ankur! :) But how to assign the storage level to a new vertices RDD that mapped from an existing vertices RDD, e.g. *val newVertexRDD = graph.collectNeighborIds(EdgeDirection.Out).map{case(id:VertexId, a:Array[VertexId]) = (id, initialHashMap(a))}* the new one will be combined with

Re: [GraphX] how to set memory configurations to avoid OutOfMemoryError GC overhead limit exceeded

2014-09-03 Thread Yifan LI
Hi Ankur, Thanks so much for your advice. But it failed when I tried to set the storage level in constructing a graph. val graph = GraphLoader.edgeListFile(sc, edgesFile, minEdgePartitions = numPartitions).partitionBy(PartitionStrategy.EdgePartition2D).persist(StorageLevel.MEMORY_AND_DISK)

Re: [GraphX] how to set memory configurations to avoid OutOfMemoryError GC overhead limit exceeded

2014-09-03 Thread Ankur Dave
At 2014-09-03 17:58:09 +0200, Yifan LI iamyifa...@gmail.com wrote: val graph = GraphLoader.edgeListFile(sc, edgesFile, minEdgePartitions = numPartitions).partitionBy(PartitionStrategy.EdgePartition2D).persist(StorageLevel.MEMORY_AND_DISK) Error: java.lang.UnsupportedOperationException: Cannot

Re: [GraphX] how to set memory configurations to avoid OutOfMemoryError GC overhead limit exceeded

2014-08-18 Thread Ankur Dave
On Mon, Aug 18, 2014 at 6:29 AM, Yifan LI iamyifa...@gmail.com wrote: I am testing our application(similar to personalised page rank using Pregel, and note that each vertex property will need pretty much more space to store after new iteration) [...] But when we ran it on larger graph(e.g.