Micah,
Just to follow up, I pulled the project off git, and rebuilt my stuff
using the artifacts from building master, and that did the trick.
Thanks!
On Fri, Apr 27, 2018 at 4:18 PM David Ortiz <[email protected]> wrote:
> Looks like scrunch-0.15.0 relies on version 2.10.4 of scala libraries.
> would that create the issue?
>
> On Fri, Apr 27, 2018 at 4:11 PM David Ortiz <[email protected]> wrote:
>
>> Would that throw the AbstractMethodError on a crunch framework method
>> though?
>>
>> On Fri, Apr 27, 2018 at 4:06 PM Micah Whitacre <[email protected]>
>> wrote:
>>
>>> The next thing to check is if you are mixing versions of Scala (2.11 vs
>>> 2.12) Or more specifically if you are compiling against a different
>>> version than is being packaged in your assembly.
>>>
>>> On Fri, Apr 27, 2018 at 3:02 PM, David Ortiz <[email protected]> wrote:
>>>
>>>> Alright. After double checking all the versions, and rebuilding as a
>>>> fat jar, I'm now getting this.
>>>>
>>>> Driver stacktrace:
>>>> at org.apache.spark.scheduler.DAGScheduler.org
>>>> $apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1708)
>>>> at
>>>> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1696)
>>>> at
>>>> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1695)
>>>> at
>>>> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
>>>> at
>>>> scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
>>>> at
>>>> org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1695)
>>>> at
>>>> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:855)
>>>> at
>>>> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:855)
>>>> at scala.Option.foreach(Option.scala:257)
>>>> at
>>>> org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:855)
>>>> at
>>>> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1923)
>>>> at
>>>> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1878)
>>>> at
>>>> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1867)
>>>> at
>>>> org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
>>>> at
>>>> org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:671)
>>>> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2029)
>>>> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2050)
>>>> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2082)
>>>> at org.apache.spark.internal.io
>>>> .SparkHadoopMapReduceWriter$.write(SparkHadoopMapReduceWriter.scala:88)
>>>> ... 19 more
>>>> Caused by: java.lang.AbstractMethodError:
>>>> org.apache.crunch.impl.spark.fn.CrunchPairTuple2.call(Ljava/lang/Object;)Ljava/util/Iterator;
>>>> at
>>>> org.apache.spark.api.java.JavaRDDLike$$anonfun$fn$7$1.apply(JavaRDDLike.scala:186)
>>>> at
>>>> org.apache.spark.api.java.JavaRDDLike$$anonfun$fn$7$1.apply(JavaRDDLike.scala:186)
>>>> at
>>>> org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:797)
>>>> at
>>>> org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:797)
>>>> at
>>>> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
>>>> at
>>>> org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
>>>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
>>>> at
>>>> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
>>>> at
>>>> org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
>>>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
>>>> at
>>>> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
>>>> at
>>>> org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
>>>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
>>>> at
>>>> org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
>>>> at org.apache.spark.scheduler.Task.run(Task.scala:108)
>>>> at
>>>> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:338)
>>>> at
>>>> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
>>>> at
>>>> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
>>>> ... 1 more
>>>>
>>>> On Thu, Apr 26, 2018 at 6:54 PM David Ortiz <[email protected]> wrote:
>>>>
>>>>> Oh wow. I'll take a look tomorrow morning and see if I can figure it
>>>>> out.
>>>>>
>>>>> On Thu, Apr 26, 2018, 6:08 PM Josh Wills <[email protected]> wrote:
>>>>>
>>>>>> It means that a hadoop1 dependency is getting into the jar somehow,
>>>>>> although it's not obvious to me how...do you have a dependency tree you
>>>>>> can
>>>>>> tease apart?
>>>>>>
>>>>>> On Thu, Apr 26, 2018 at 12:17 PM, David Ortiz <[email protected]>
>>>>>> wrote:
>>>>>>
>>>>>>> Hello,
>>>>>>>
>>>>>>> I am playing around with trying to run a mapreduce pipeline
>>>>>>> we've had in production for a little while on Spark. When I switch to
>>>>>>> the
>>>>>>> spark pipeline and try to run it, I have run into the following
>>>>>>> exception:
>>>>>>>
>>>>>>> Exception in thread "Thread-32"
>>>>>>> java.lang.IncompatibleClassChangeError: Found interface
>>>>>>> org.apache.hadoop.mapreduce.JobContext, but class was expected
>>>>>>> at
>>>>>>> org.apache.crunch.impl.mr.run.CrunchInputFormat.getSplits(CrunchInputFormat.java:44)
>>>>>>> at
>>>>>>> org.apache.spark.rdd.NewHadoopRDD.getPartitions(NewHadoopRDD.scala:124)
>>>>>>> at
>>>>>>> org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:239)
>>>>>>> at
>>>>>>> org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:237)
>>>>>>> at scala.Option.getOrElse(Option.scala:120)
>>>>>>> at org.apache.spark.rdd.RDD.partitions(RDD.scala:237)
>>>>>>> at
>>>>>>> org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35)
>>>>>>> at
>>>>>>> org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:239)
>>>>>>> at
>>>>>>> org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:237)
>>>>>>> at scala.Option.getOrElse(Option.scala:120)
>>>>>>> at org.apache.spark.rdd.RDD.partitions(RDD.scala:237)
>>>>>>> at
>>>>>>> org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35)
>>>>>>> at
>>>>>>> org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:239)
>>>>>>> at
>>>>>>> org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:237)
>>>>>>> at scala.Option.getOrElse(Option.scala:120)
>>>>>>> at org.apache.spark.rdd.RDD.partitions(RDD.scala:237)
>>>>>>> at
>>>>>>> org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35)
>>>>>>> at
>>>>>>> org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:239)
>>>>>>> at
>>>>>>> org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:237)
>>>>>>> at scala.Option.getOrElse(Option.scala:120)
>>>>>>> at org.apache.spark.rdd.RDD.partitions(RDD.scala:237)
>>>>>>> at
>>>>>>> org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35)
>>>>>>> at
>>>>>>> org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:239)
>>>>>>> at
>>>>>>> org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:237)
>>>>>>> at scala.Option.getOrElse(Option.scala:120)
>>>>>>> at org.apache.spark.rdd.RDD.partitions(RDD.scala:237)
>>>>>>> at
>>>>>>> org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35)
>>>>>>> at
>>>>>>> org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:239)
>>>>>>> at
>>>>>>> org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:237)
>>>>>>> at scala.Option.getOrElse(Option.scala:120)
>>>>>>> at org.apache.spark.rdd.RDD.partitions(RDD.scala:237)
>>>>>>> at
>>>>>>> org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35)
>>>>>>> at
>>>>>>> org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:239)
>>>>>>> at
>>>>>>> org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:237)
>>>>>>> at scala.Option.getOrElse(Option.scala:120)
>>>>>>> at org.apache.spark.rdd.RDD.partitions(RDD.scala:237)
>>>>>>> at
>>>>>>> org.apache.spark.SparkContext.runJob(SparkContext.scala:1952)
>>>>>>> at
>>>>>>> org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopDataset$1.apply$mcV$sp(PairRDDFunctions.scala:1144)
>>>>>>> at
>>>>>>> org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopDataset$1.apply(PairRDDFunctions.scala:1074)
>>>>>>> at
>>>>>>> org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopDataset$1.apply(PairRDDFunctions.scala:1074)
>>>>>>> at
>>>>>>> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
>>>>>>> at
>>>>>>> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:111)
>>>>>>> at org.apache.spark.rdd.RDD.withScope(RDD.scala:316)
>>>>>>> at
>>>>>>> org.apache.spark.rdd.PairRDDFunctions.saveAsNewAPIHadoopDataset(PairRDDFunctions.scala:1074)
>>>>>>> at
>>>>>>> org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopFile$2.apply$mcV$sp(PairRDDFunctions.scala:994)
>>>>>>> at
>>>>>>> org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopFile$2.apply(PairRDDFunctions.scala:985)
>>>>>>> at
>>>>>>> org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopFile$2.apply(PairRDDFunctions.scala:985)
>>>>>>> at
>>>>>>> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
>>>>>>> at
>>>>>>> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:111)
>>>>>>> at org.apache.spark.rdd.RDD.withScope(RDD.scala:316)
>>>>>>> at
>>>>>>> org.apache.spark.rdd.PairRDDFunctions.saveAsNewAPIHadoopFile(PairRDDFunctions.scala:985)
>>>>>>> at
>>>>>>> org.apache.spark.api.java.JavaPairRDD.saveAsNewAPIHadoopFile(JavaPairRDD.scala:800)
>>>>>>> at
>>>>>>> org.apache.crunch.impl.spark.SparkRuntime.monitorLoop(SparkRuntime.java:321)
>>>>>>> at
>>>>>>> org.apache.crunch.impl.spark.SparkRuntime.access$000(SparkRuntime.java:77)
>>>>>>> at
>>>>>>> org.apache.crunch.impl.spark.SparkRuntime$2.run(SparkRuntime.java:136)
>>>>>>> at java.lang.Thread.run(Thread.java:745)
>>>>>>>
>>>>>>> This happens both on EMR 5.12.0 using the 0.15.0 artifacts, as well
>>>>>>> as on a non-production CDH cluster running CDH 5.13.1 parcels.
>>>>>>>
>>>>>>> Any idea what would cause this?
>>>>>>>
>>>>>>> Thanks,
>>>>>>> Dave
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>
>>>
