Hi, I'm working on having "SparkPerf" (
https://github.com/databricks/spark-perf) run with Spark 2.0, noticed a
few pull requests not yet accepted so concerned this project's been
abandoned - it's proven very useful in the past for quality assurance as
we can easily exercise lots of Spark functions with a cluster (perhaps
exposing problems that don't surface with the Spark unit tests).
I want to use Scala 2.11.8 and Spark 2.0.0 so I'm making my way through
various files, currently faced with a NoSuchMethod exception
NoSuchMethodError:
org/apache/spark/SparkContext.rddToPairRDDFunctions(Lorg/apache/spark/rdd/RDD;Lscala/reflect/ClassTag;Lscala/reflect/ClassTag;Lscala/math/Ordering;)Lorg/apache/spark/rdd/PairRDDFunctions;
at spark.perf.AggregateByKey.runTest(KVDataTest.scala:137)
class AggregateByKey(sc: SparkContext) extends KVDataTest(sc) {
override def runTest(rdd: RDD[_], reduceTasks: Int) {
rdd.asInstanceOf[RDD[(String, String)]]
.map{case (k, v) => (k, v.toInt)}.reduceByKey(_ + _,
reduceTasks).count()
}
}
Grepping shows
./spark-tests/target/streams/compile/incCompileSetup/$global/streams/inc_compile_2.10:/home/aroberts/Desktop/spark-perf/spark-tests/src/main/scala/spark/perf/KVDataTest.scala
-> rddToPairRDDFunctions
The scheduling-throughput tests complete fine but the problem here is seen
with agg-by-key (and likely other modules to fix owing to API changes
between 1.x and 2.x which I guess is the cause of the above problem).
Has anybody already made good progress here? Would like to work together
and get this available for everyone, I'll be churning through it either
way. Will be looking at HiBench also.
Next step for me is to use sbt -Dspark.version=2.0.0 (2.0.0-preview?) and
work from there, although I figured the prep tests stage would do this for
me (how else is it going to build?).
Cheers,
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