See this method:
lazy val rdd: RDD[T] = {
On Mon, Mar 28, 2016 at 6:30 PM, Russell Jurney <russell.jur...@gmail.com>
wrote:
> 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
>
