[ https://issues.apache.org/jira/browse/SPARK-14229?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Russell Jurney updated SPARK-14229: ----------------------------------- Shepherd: Matei Zaharia > PySpark DataFrame.rdd's can't be saved to an arbitrary Hadoop OutputFormat > -------------------------------------------------------------------------- > > Key: SPARK-14229 > URL: https://issues.apache.org/jira/browse/SPARK-14229 > Project: Spark > Issue Type: Bug > Components: Input/Output, PySpark, Spark Shell > Affects Versions: 1.6.1 > Reporter: Russell Jurney > > I am able to save data to MongoDB from any RDD... provided that RDD does not > belong to a DataFrame. If I use DataFrame.rdd, it is not possible to save via > saveAsNewAPIHadoopFile whatsoever. I have tested that this applies to saving > to MongoDB, BSON Files, and ElasticSearch. > I get the following error when I try to save to a HadoopFile: > config = {"mongo.output.uri": > "mongodb://localhost:27017/agile_data_science.on_time_performance"} > n [3]: 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=config > ...: ) > 16/03/28 19:59:57 INFO storage.MemoryStore: Block broadcast_1 stored as > values in memory (estimated size 62.7 KB, free 147.3 KB) > 16/03/28 19:59:57 INFO storage.MemoryStore: Block broadcast_1_piece0 stored > as bytes in memory (estimated size 20.4 KB, free 167.7 KB) > 16/03/28 19:59:57 INFO storage.BlockManagerInfo: Added broadcast_1_piece0 in > memory on localhost:61301 (size: 20.4 KB, free: 511.1 MB) > 16/03/28 19:59:57 INFO spark.SparkContext: Created broadcast 1 from > javaToPython at NativeMethodAccessorImpl.java:-2 > 16/03/28 19:59:57 INFO Configuration.deprecation: mapred.min.split.size is > deprecated. Instead, use mapreduce.input.fileinputformat.split.minsize > 16/03/28 19:59:57 INFO parquet.ParquetRelation: Reading Parquet file(s) from > file:/Users/rjurney/Software/Agile_Data_Code_2/data/on_time_performance.parquet/part-r-00000-32089f1b-5447-4a75-b008-4fd0a0a8b846.gz.parquet > 16/03/28 19:59:57 INFO spark.SparkContext: Starting job: take at > SerDeUtil.scala:231 > 16/03/28 19:59:57 INFO scheduler.DAGScheduler: Got job 1 (take at > SerDeUtil.scala:231) with 1 output partitions > 16/03/28 19:59:57 INFO scheduler.DAGScheduler: Final stage: ResultStage 1 > (take at SerDeUtil.scala:231) > 16/03/28 19:59:57 INFO scheduler.DAGScheduler: Parents of final stage: List() > 16/03/28 19:59:57 INFO scheduler.DAGScheduler: Missing parents: List() > 16/03/28 19:59:57 INFO scheduler.DAGScheduler: Submitting ResultStage 1 > (MapPartitionsRDD[6] at mapPartitions at SerDeUtil.scala:146), which has no > missing parents > 16/03/28 19:59:57 INFO storage.MemoryStore: Block broadcast_2 stored as > values in memory (estimated size 14.9 KB, free 182.6 KB) > 16/03/28 19:59:57 INFO storage.MemoryStore: Block broadcast_2_piece0 stored > as bytes in memory (estimated size 7.5 KB, free 190.1 KB) > 16/03/28 19:59:57 INFO storage.BlockManagerInfo: Added broadcast_2_piece0 in > memory on localhost:61301 (size: 7.5 KB, free: 511.1 MB) > 16/03/28 19:59:57 INFO spark.SparkContext: Created broadcast 2 from broadcast > at DAGScheduler.scala:1006 > 16/03/28 19:59:57 INFO scheduler.DAGScheduler: Submitting 1 missing tasks > from ResultStage 1 (MapPartitionsRDD[6] at mapPartitions at > SerDeUtil.scala:146) > 16/03/28 19:59:57 INFO scheduler.TaskSchedulerImpl: Adding task set 1.0 with > 1 tasks > 16/03/28 19:59:57 INFO scheduler.TaskSetManager: Starting task 0.0 in stage > 1.0 (TID 8, localhost, partition 0,PROCESS_LOCAL, 2739 bytes) > 16/03/28 19:59:57 INFO executor.Executor: Running task 0.0 in stage 1.0 (TID > 8) > 16/03/28 19:59:58 INFO > parquet.ParquetRelation$$anonfun$buildInternalScan$1$$anon$1: Input split: > ParquetInputSplit{part: > file:/Users/rjurney/Software/Agile_Data_Code_2/data/on_time_performance.parquet/part-r-00000-32089f1b-5447-4a75-b008-4fd0a0a8b846.gz.parquet > start: 0 end: 134217728 length: 134217728 hosts: []} > 16/03/28 19:59:59 INFO compress.CodecPool: Got brand-new decompressor [.gz] > 16/03/28 19:59:59 ERROR executor.Executor: Exception in task 0.0 in stage 1.0 > (TID 8) > 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) > Traceback (most recent call last): > File > "/Users/rjurney/Software/Agile_Data_Code_2/spark/python/lib/pyspark.zip/pyspark/daemon.py", > line 157, in manager > File > "/Users/rjurney/Software/Agile_Data_Code_2/spark/python/lib/pyspark.zip/pyspark/daemon.py", > line 61, in worker > File > "/Users/rjurney/Software/Agile_Data_Code_2/spark/python/lib/pyspark.zip/pyspark/worker.py", > line 136, in main > if read_int(infile) == SpecialLengths.END_OF_STREAM: > File > "/Users/rjurney/Software/Agile_Data_Code_2/spark/python/lib/pyspark.zip/pyspark/serializers.py", > line 545, in read_int > raise EOFError > EOFError > 16/03/28 19:59:59 WARN scheduler.TaskSetManager: Lost task 0.0 in stage 1.0 > (TID 8, 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 19:59:59 ERROR scheduler.TaskSetManager: Task 0 in stage 1.0 failed > 1 times; aborting job > 16/03/28 19:59:59 INFO scheduler.TaskSchedulerImpl: Removed TaskSet 1.0, > whose tasks have all completed, from pool > 16/03/28 19:59:59 INFO scheduler.TaskSchedulerImpl: Cancelling stage 1 > 16/03/28 19:59:59 INFO scheduler.DAGScheduler: ResultStage 1 (take at > SerDeUtil.scala:231) failed in 1.683 s > 16/03/28 19:59:59 INFO scheduler.DAGScheduler: Job 1 failed: take at > SerDeUtil.scala:231, took 1.703169 s > --------------------------------------------------------------------------- > Py4JJavaError Traceback (most recent call last) > <ipython-input-3-c91c1bc7b72a> in <module>() > 4 keyClass='org.apache.hadoop.io.Text', > 5 valueClass='org.apache.hadoop.io.MapWritable', > ----> 6 conf=config > 7 ) > /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 1.0 failed 1 times, most recent failure: Lost task 0.0 in stage 1.0 > (TID 8, 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 -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org