Ok, I'm also unable to save to Elasticsearch using a dataframe's RDD. This seems related to DataFrames. Is there a way to convert a DataFrame's RDD to a 'normal' RDD?
On Mon, Mar 28, 2016 at 6:20 PM, Russell Jurney <russell.jur...@gmail.com> wrote: > I filed a JIRA <https://jira.mongodb.org/browse/HADOOP-276> in the > mongo-hadoop project, but I'm curious if anyone else has seen this issue. > Anyone have any idea what to do? I can't save to Mongo from PySpark. A > contrived example works, but a dataframe does not. > > I activate pymongo_spark and load a dataframe: > > import pymongo > import pymongo_spark > # Important: activate pymongo_spark. > pymongo_spark.activate() > > on_time_dataframe = > sqlContext.read.parquet('../data/on_time_performance.parquet') > > Then I try saving to MongoDB in two ways: > > > on_time_dataframe.rdd.saveToMongoDB('mongodb://localhost:27017/agile_data_science.on_time_performance') > > on_time_dataframe.rdd.saveAsNewAPIHadoopFile( > path='file://unused', > outputFormatClass='com.mongodb.hadoop.MongoOutputFormat', > keyClass='org.apache.hadoop.io.Text', > valueClass='org.apache.hadoop.io.MapWritable', > conf={"mongo.output.uri": > "mongodb://localhost:27017/agile_data_science.on_time_performance"} > ) > > > But I always get this error: > > In [7]: > on_time_rdd.saveToMongoDB('mongodb://localhost:27017/agile_data_science.on_time_performance') > > 16/03/28 18:04:06 INFO mapred.FileInputFormat: Total input paths to > process : 1 > > 16/03/28 18:04:06 INFO spark.SparkContext: Starting job: runJob at > PythonRDD.scala:393 > > 16/03/28 18:04:06 INFO scheduler.DAGScheduler: Got job 2 (runJob at > PythonRDD.scala:393) with 1 output partitions > > 16/03/28 18:04:06 INFO scheduler.DAGScheduler: Final stage: ResultStage 2 > (runJob at PythonRDD.scala:393) > > 16/03/28 18:04:06 INFO scheduler.DAGScheduler: Parents of final stage: > List() > > 16/03/28 18:04:06 INFO scheduler.DAGScheduler: Missing parents: List() > > 16/03/28 18:04:06 INFO scheduler.DAGScheduler: Submitting ResultStage 2 > (PythonRDD[13] at RDD at PythonRDD.scala:43), which has no missing parents > > 16/03/28 18:04:06 INFO storage.MemoryStore: Block broadcast_5 stored as > values in memory (estimated size 19.3 KB, free 249.2 KB) > > 16/03/28 18:04:06 INFO storage.MemoryStore: Block broadcast_5_piece0 > stored as bytes in memory (estimated size 9.7 KB, free 258.9 KB) > > 16/03/28 18:04:06 INFO storage.BlockManagerInfo: Added broadcast_5_piece0 > in memory on localhost:59881 (size: 9.7 KB, free: 511.1 MB) > > 16/03/28 18:04:06 INFO spark.SparkContext: Created broadcast 5 from > broadcast at DAGScheduler.scala:1006 > > 16/03/28 18:04:06 INFO scheduler.DAGScheduler: Submitting 1 missing tasks > from ResultStage 2 (PythonRDD[13] at RDD at PythonRDD.scala:43) > > 16/03/28 18:04:06 INFO scheduler.TaskSchedulerImpl: Adding task set 2.0 > with 1 tasks > > 16/03/28 18:04:06 INFO scheduler.TaskSetManager: Starting task 0.0 in > stage 2.0 (TID 2, localhost, partition 0,PROCESS_LOCAL, 2666 bytes) > > 16/03/28 18:04:06 INFO executor.Executor: Running task 0.0 in stage 2.0 > (TID 2) > > 16/03/28 18:04:06 INFO rdd.HadoopRDD: Input split: > file:/Users/rjurney/Software/Agile_Data_Code_2/data/On_Time_On_Time_Performance_2015.csv.gz:0+312456777 > > 16/03/28 18:04:06 INFO compress.CodecPool: Got brand-new decompressor [.gz] > > 16/03/28 18:04:07 INFO python.PythonRunner: Times: total = 1310, boot = > 1249, init = 58, finish = 3 > > 16/03/28 18:04:07 INFO executor.Executor: Finished task 0.0 in stage 2.0 > (TID 2). 4475 bytes result sent to driver > > 16/03/28 18:04:07 INFO scheduler.TaskSetManager: Finished task 0.0 in > stage 2.0 (TID 2) in 1345 ms on localhost (1/1) > > 16/03/28 18:04:07 INFO scheduler.TaskSchedulerImpl: Removed TaskSet 2.0, > whose tasks have all completed, from pool > > 16/03/28 18:04:07 INFO scheduler.DAGScheduler: ResultStage 2 (runJob at > PythonRDD.scala:393) finished in 1.346 s > > 16/03/28 18:04:07 INFO scheduler.DAGScheduler: Job 2 finished: runJob at > PythonRDD.scala:393, took 1.361003 s > > 16/03/28 18:04:07 INFO spark.SparkContext: Starting job: take at > SerDeUtil.scala:231 > > 16/03/28 18:04:07 INFO scheduler.DAGScheduler: Got job 3 (take at > SerDeUtil.scala:231) with 1 output partitions > > 16/03/28 18:04:07 INFO scheduler.DAGScheduler: Final stage: ResultStage 3 > (take at SerDeUtil.scala:231) > > 16/03/28 18:04:07 INFO scheduler.DAGScheduler: Parents of final stage: > List() > > 16/03/28 18:04:07 INFO scheduler.DAGScheduler: Missing parents: List() > > 16/03/28 18:04:07 INFO scheduler.DAGScheduler: Submitting ResultStage 3 > (MapPartitionsRDD[15] at mapPartitions at SerDeUtil.scala:146), which has > no missing parents > > 16/03/28 18:04:07 INFO storage.MemoryStore: Block broadcast_6 stored as > values in memory (estimated size 19.6 KB, free 278.4 KB) > > 16/03/28 18:04:07 INFO storage.MemoryStore: Block broadcast_6_piece0 > stored as bytes in memory (estimated size 9.8 KB, free 288.2 KB) > > 16/03/28 18:04:07 INFO storage.BlockManagerInfo: Added broadcast_6_piece0 > in memory on localhost:59881 (size: 9.8 KB, free: 511.1 MB) > > 16/03/28 18:04:07 INFO spark.SparkContext: Created broadcast 6 from > broadcast at DAGScheduler.scala:1006 > > 16/03/28 18:04:07 INFO scheduler.DAGScheduler: Submitting 1 missing tasks > from ResultStage 3 (MapPartitionsRDD[15] at mapPartitions at > SerDeUtil.scala:146) > > 16/03/28 18:04:07 INFO scheduler.TaskSchedulerImpl: Adding task set 3.0 > with 1 tasks > > 16/03/28 18:04:07 INFO scheduler.TaskSetManager: Starting task 0.0 in > stage 3.0 (TID 3, localhost, partition 0,PROCESS_LOCAL, 2666 bytes) > > 16/03/28 18:04:07 INFO executor.Executor: Running task 0.0 in stage 3.0 > (TID 3) > > 16/03/28 18:04:07 INFO rdd.HadoopRDD: Input split: > file:/Users/rjurney/Software/Agile_Data_Code_2/data/On_Time_On_Time_Performance_2015.csv.gz:0+312456777 > > 16/03/28 18:04:07 INFO compress.CodecPool: Got brand-new decompressor [.gz] > > 16/03/28 18:04:07 ERROR executor.Executor: Exception in task 0.0 in stage > 3.0 (TID 3) > > net.razorvine.pickle.PickleException: expected zero arguments for > construction of ClassDict (for pyspark.sql.types._create_row) > > at > net.razorvine.pickle.objects.ClassDictConstructor.construct(ClassDictConstructor.java:23) > > at net.razorvine.pickle.Unpickler.load_reduce(Unpickler.java:707) > > at net.razorvine.pickle.Unpickler.dispatch(Unpickler.java:175) > > at net.razorvine.pickle.Unpickler.load(Unpickler.java:99) > > at net.razorvine.pickle.Unpickler.loads(Unpickler.java:112) > > at > org.apache.spark.api.python.SerDeUtil$$anonfun$pythonToJava$1$$anonfun$apply$1.apply(SerDeUtil.scala:150) > > at > org.apache.spark.api.python.SerDeUtil$$anonfun$pythonToJava$1$$anonfun$apply$1.apply(SerDeUtil.scala:149) > > at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371) > > at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:308) > > at scala.collection.Iterator$class.foreach(Iterator.scala:727) > > at scala.collection.AbstractIterator.foreach(Iterator.scala:1157) > > at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48) > > at > scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103) > > at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47) > > at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:273) > > at scala.collection.AbstractIterator.to(Iterator.scala:1157) > > at > scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265) > > at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157) > > at > scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252) > > at scala.collection.AbstractIterator.toArray(Iterator.scala:1157) > > at > org.apache.spark.rdd.RDD$$anonfun$take$1$$anonfun$28.apply(RDD.scala:1328) > > at > org.apache.spark.rdd.RDD$$anonfun$take$1$$anonfun$28.apply(RDD.scala:1328) > > at > org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1858) > > at > org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1858) > > at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66) > > at org.apache.spark.scheduler.Task.run(Task.scala:89) > > at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214) > > at > java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) > > at > java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) > > at java.lang.Thread.run(Thread.java:745) > > 16/03/28 18:04:07 WARN scheduler.TaskSetManager: Lost task 0.0 in stage > 3.0 (TID 3, localhost): net.razorvine.pickle.PickleException: expected zero > arguments for construction of ClassDict (for pyspark.sql.types._create_row) > > at > net.razorvine.pickle.objects.ClassDictConstructor.construct(ClassDictConstructor.java:23) > > at net.razorvine.pickle.Unpickler.load_reduce(Unpickler.java:707) > > at net.razorvine.pickle.Unpickler.dispatch(Unpickler.java:175) > > at net.razorvine.pickle.Unpickler.load(Unpickler.java:99) > > at net.razorvine.pickle.Unpickler.loads(Unpickler.java:112) > > at > org.apache.spark.api.python.SerDeUtil$$anonfun$pythonToJava$1$$anonfun$apply$1.apply(SerDeUtil.scala:150) > > at > org.apache.spark.api.python.SerDeUtil$$anonfun$pythonToJava$1$$anonfun$apply$1.apply(SerDeUtil.scala:149) > > at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371) > > at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:308) > > at scala.collection.Iterator$class.foreach(Iterator.scala:727) > > at scala.collection.AbstractIterator.foreach(Iterator.scala:1157) > > at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48) > > at > scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103) > > at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47) > > at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:273) > > at scala.collection.AbstractIterator.to(Iterator.scala:1157) > > at > scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265) > > at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157) > > at > scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252) > > at scala.collection.AbstractIterator.toArray(Iterator.scala:1157) > > at > org.apache.spark.rdd.RDD$$anonfun$take$1$$anonfun$28.apply(RDD.scala:1328) > > at > org.apache.spark.rdd.RDD$$anonfun$take$1$$anonfun$28.apply(RDD.scala:1328) > > at > org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1858) > > at > org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1858) > > at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66) > > at org.apache.spark.scheduler.Task.run(Task.scala:89) > > at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214) > > at > java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) > > at > java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) > > at java.lang.Thread.run(Thread.java:745) > > > 16/03/28 18:04:07 ERROR scheduler.TaskSetManager: Task 0 in stage 3.0 > failed 1 times; aborting job > > 16/03/28 18:04:07 INFO scheduler.TaskSchedulerImpl: Removed TaskSet 3.0, > whose tasks have all completed, from pool > > 16/03/28 18:04:07 INFO scheduler.TaskSchedulerImpl: Cancelling stage 3 > > 16/03/28 18:04:07 INFO scheduler.DAGScheduler: ResultStage 3 (take at > SerDeUtil.scala:231) failed in 0.117 s > > 16/03/28 18:04:07 INFO scheduler.DAGScheduler: Job 3 failed: take at > SerDeUtil.scala:231, took 0.134593 s > > --------------------------------------------------------------------------- > > Py4JJavaError Traceback (most recent call > last) > > <ipython-input-7-d1f984f17e27> in <module>() > > ----> 1 on_time_rdd.saveToMongoDB > ('mongodb://localhost:27017/agile_data_science.on_time_performance') > > > /Users/rjurney/Software/Agile_Data_Code_2/lib/pymongo_spark.pyc in > saveToMongoDB(self, connection_string, config) > > 104 keyConverter='com.mongodb.spark.pickle.NoopConverter', > > 105 valueConverter='com.mongodb.spark.pickle.NoopConverter', > > --> 106 conf=conf) > > 107 > > 108 > > > /Users/rjurney/Software/Agile_Data_Code_2/spark/python/pyspark/rdd.pyc in > saveAsNewAPIHadoopFile(self, path, outputFormatClass, keyClass, > valueClass, keyConverter, valueConverter, conf) > > 1372 > outputFormatClass, > > 1373 keyClass, > valueClass, > > -> 1374 > keyConverter, valueConverter, jconf) > > 1375 > > 1376 def saveAsHadoopDataset(self, conf, keyConverter=None, > valueConverter=None): > > > > /Users/rjurney/Software/Agile_Data_Code_2/spark/python/lib/py4j-0.9-src.zip/py4j/java_gateway.py > in __call__(self, *args) > > 811 answer = self.gateway_client.send_command(command) > > 812 return_value = get_return_value( > > --> 813 answer, self.gateway_client, self.target_id, self.name > ) > > 814 > > 815 for temp_arg in temp_args: > > > > /Users/rjurney/Software/Agile_Data_Code_2/spark/python/pyspark/sql/utils.pyc > in deco(*a, **kw) > > 43 def deco(*a, **kw): > > 44 try: > > ---> 45 return f(*a, **kw) > > 46 except py4j.protocol.Py4JJavaError as e: > > 47 s = e.java_exception.toString() > > > > /Users/rjurney/Software/Agile_Data_Code_2/spark/python/lib/py4j-0.9-src.zip/py4j/protocol.py > in get_return_value(answer, gateway_client, target_id, name) > > 306 raise Py4JJavaError( > > 307 "An error occurred while calling > {0}{1}{2}.\n". > > --> 308 format(target_id, ".", name), value) > > 309 else: > > 310 raise Py4JError( > > > Py4JJavaError: An error occurred while calling > z:org.apache.spark.api.python.PythonRDD.saveAsNewAPIHadoopFile. > > : org.apache.spark.SparkException: Job aborted due to stage failure: Task > 0 in stage 3.0 failed 1 times, most recent failure: Lost task 0.0 in stage > 3.0 (TID 3, localhost): net.razorvine.pickle.PickleException: expected zero > arguments for construction of ClassDict (for pyspark.sql.types._create_row) > > at > net.razorvine.pickle.objects.ClassDictConstructor.construct(ClassDictConstructor.java:23) > > at net.razorvine.pickle.Unpickler.load_reduce(Unpickler.java:707) > > at net.razorvine.pickle.Unpickler.dispatch(Unpickler.java:175) > > at net.razorvine.pickle.Unpickler.load(Unpickler.java:99) > > at net.razorvine.pickle.Unpickler.loads(Unpickler.java:112) > > at > org.apache.spark.api.python.SerDeUtil$$anonfun$pythonToJava$1$$anonfun$apply$1.apply(SerDeUtil.scala:150) > > at > org.apache.spark.api.python.SerDeUtil$$anonfun$pythonToJava$1$$anonfun$apply$1.apply(SerDeUtil.scala:149) > > at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371) > > at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:308) > > at scala.collection.Iterator$class.foreach(Iterator.scala:727) > > at scala.collection.AbstractIterator.foreach(Iterator.scala:1157) > > at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48) > > at > scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103) > > at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47) > > at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:273) > > at scala.collection.AbstractIterator.to(Iterator.scala:1157) > > at > scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265) > > at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157) > > at > scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252) > > at scala.collection.AbstractIterator.toArray(Iterator.scala:1157) > > at > org.apache.spark.rdd.RDD$$anonfun$take$1$$anonfun$28.apply(RDD.scala:1328) > > at > org.apache.spark.rdd.RDD$$anonfun$take$1$$anonfun$28.apply(RDD.scala:1328) > > at > org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1858) > > at > org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1858) > > at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66) > > at org.apache.spark.scheduler.Task.run(Task.scala:89) > > at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214) > > at > java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) > > at > java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) > > at java.lang.Thread.run(Thread.java:745) > > > Driver stacktrace: > > at org.apache.spark.scheduler.DAGScheduler.org > $apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1431) > > at > org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1419) > > at > org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1418) > > at > scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) > > at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47) > > at > org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1418) > > at > org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:799) > > at > org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:799) > > at scala.Option.foreach(Option.scala:236) > > at > org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:799) > > at > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1640) > > at > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1599) > > at > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1588) > > at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48) > > at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:620) > > at org.apache.spark.SparkContext.runJob(SparkContext.scala:1832) > > at org.apache.spark.SparkContext.runJob(SparkContext.scala:1845) > > at org.apache.spark.SparkContext.runJob(SparkContext.scala:1858) > > at org.apache.spark.rdd.RDD$$anonfun$take$1.apply(RDD.scala:1328) > > at > org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150) > > at > org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:111) > > at org.apache.spark.rdd.RDD.withScope(RDD.scala:316) > > at org.apache.spark.rdd.RDD.take(RDD.scala:1302) > > at > org.apache.spark.api.python.SerDeUtil$.pythonToPairRDD(SerDeUtil.scala:231) > > at > org.apache.spark.api.python.PythonRDD$.saveAsNewAPIHadoopFile(PythonRDD.scala:775) > > at > org.apache.spark.api.python.PythonRDD.saveAsNewAPIHadoopFile(PythonRDD.scala) > > at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) > > at > sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) > > at > sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) > > at java.lang.reflect.Method.invoke(Method.java:497) > > at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231) > > at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:381) > > at py4j.Gateway.invoke(Gateway.java:259) > > at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:133) > > at py4j.commands.CallCommand.execute(CallCommand.java:79) > > at py4j.GatewayConnection.run(GatewayConnection.java:209) > > at java.lang.Thread.run(Thread.java:745) > > Caused by: net.razorvine.pickle.PickleException: expected zero arguments > for construction of ClassDict (for pyspark.sql.types._create_row) > > at > net.razorvine.pickle.objects.ClassDictConstructor.construct(ClassDictConstructor.java:23) > > at net.razorvine.pickle.Unpickler.load_reduce(Unpickler.java:707) > > at net.razorvine.pickle.Unpickler.dispatch(Unpickler.java:175) > > at net.razorvine.pickle.Unpickler.load(Unpickler.java:99) > > at net.razorvine.pickle.Unpickler.loads(Unpickler.java:112) > > at > org.apache.spark.api.python.SerDeUtil$$anonfun$pythonToJava$1$$anonfun$apply$1.apply(SerDeUtil.scala:150) > > at > org.apache.spark.api.python.SerDeUtil$$anonfun$pythonToJava$1$$anonfun$apply$1.apply(SerDeUtil.scala:149) > > at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371) > > at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:308) > > at scala.collection.Iterator$class.foreach(Iterator.scala:727) > > at scala.collection.AbstractIterator.foreach(Iterator.scala:1157) > > at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48) > > at > scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103) > > at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47) > > at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:273) > > at scala.collection.AbstractIterator.to(Iterator.scala:1157) > > at > scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265) > > at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157) > > at > scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252) > > at scala.collection.AbstractIterator.toArray(Iterator.scala:1157) > > at > org.apache.spark.rdd.RDD$$anonfun$take$1$$anonfun$28.apply(RDD.scala:1328) > > at > org.apache.spark.rdd.RDD$$anonfun$take$1$$anonfun$28.apply(RDD.scala:1328) > > at > org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1858) > > at > org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1858) > > at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66) > > at org.apache.spark.scheduler.Task.run(Task.scala:89) > > at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214) > > at > java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) > > at > java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) > > ... 1 more > > > -- > Russell Jurney twitter.com/rjurney russell.jur...@gmail.com relato.io > -- Russell Jurney twitter.com/rjurney russell.jur...@gmail.com relato.io
