Hi Arpit,
To try this:
val graph = GraphLoader.edgeListFile(sc, edgesFile, minEdgePartitions =
numPartitions, edgeStorageLevel = StorageLevel.MEMORY_AND_DISK,
vertexStorageLevel = StorageLevel.MEMORY_AND_DISK)
Best,
Yifan LI
On 28 Oct 2014, at 11:17, Arpit Kumar arp8...@gmail.com
Hi Yifan LI,
I am currently working on Spark 1.0 in which we can't pass edgeStorageLevel
as parameter. It implicitly caches the edges. So I am looking for a
workaround.
http://spark.apache.org/docs/1.0.0/api/scala/index.html#org.apache.spark.graphx.GraphLoader$
Regards,
Arpit
On Tue, Oct 28,
I am not sure if it can work on Spark 1.0, but give it a try.
or, Maybe you can try:
1) to construct the edges and vertices RDDs respectively with desired storage
level.
2) then, to obtain a graph by using Graph(verticesRDD, edgesRDD).
Best,
Yifan LI
On 28 Oct 2014, at 12:10, Arpit Kumar
At 2014-10-25 08:56:34 +0530, Arpit Kumar arp8...@gmail.com wrote:
GraphLoader1.scala:49: error: class EdgePartitionBuilder in package impl
cannot be accessed in package org.apache.spark.graphx.impl
[INFO] val builder = new EdgePartitionBuilder[Int, Int]
Here's a workaround:
1. Copy and
Hi all,
I am using the GrpahLoader class to load graphs from edge list files. But
then I need to change the storage level of the graph to some other thing
than MEMORY_ONLY.
val graph = GraphLoader.edgeListFile(sc, fname,
minEdgePartitions =
