Github user pwendell commented on a diff in the pull request:
https://github.com/apache/spark/pull/720#discussion_r12502303
--- Diff:
graphx/src/main/scala/org/apache/spark/graphx/lib/SynthBenchmark.scala ---
@@ -0,0 +1,136 @@
+package org.apache.spark.graphx.lib
+
+import org.apache.spark.SparkContext._
+import org.apache.spark.graphx.PartitionStrategy
+import
org.apache.spark.graphx.PartitionStrategy.{CanonicalRandomVertexCut,
EdgePartition2D, EdgePartition1D, RandomVertexCut}
+import org.apache.spark.{SparkContext, SparkConf}
+import org.apache.spark.graphx.util.GraphGenerators
+import java.io.{PrintWriter, FileOutputStream}
+
+/**
+ * The SynthBenchmark application can be used to run various GraphX
algorithms on
+ * synthetic log-normal graphs. The intent of this code is to enable
users to
+ * profile the GraphX system without access to large graph datasets.
+ */
+object SynthBenchmark {
--- End diff --
Hey @jegonzal - we've generally been trying to put runnable programs like
this in the examples package. Would it be possible to do that here? The main
benefits are that (i) users understand this is not a stable API and (ii) users
can launch it with `run-example` or `spark-submit` which allows them to easily
do things like launch on YARN or ask for a specific number of executors when
running the program.
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