[ https://issues.apache.org/jira/browse/SPARK-13082?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Apache Spark reassigned SPARK-13082: ------------------------------------ Assignee: Apache Spark > sqlCtx.real.json() doesn't work with PythonRDD > ---------------------------------------------- > > Key: SPARK-13082 > URL: https://issues.apache.org/jira/browse/SPARK-13082 > Project: Spark > Issue Type: Bug > Components: PySpark > Affects Versions: 1.6.0 > Environment: Tested on macosx 10.10 using Spark 1.6 > Reporter: Gaƫtan Lehmann > Assignee: Apache Spark > > This code works without problem: > sqlCtx.read.json(sqlCtx.range(10).toJSON()) > but these ones fail with the traceback below: > sqlCtx.read.json(sc.parallelize(['{"id":1}']*10)) > sqlCtx.read.json(sqlCtx.range(10).toJSON().pipe("cat")) > sqlCtx.read.json(sqlCtx.range(10).toJSON().map(lambda x: x)) > --------------------------------------------------------------------------- > Py4JJavaError Traceback (most recent call last) > <ipython-input-93-91a986fee7f9> in <module>() > ----> 1 sqlCtx.read.json(sqlCtx.range(10).toJSON().map(lambda x: x)) > /usr/local/Cellar/apache-spark/1.6.0/libexec/python/pyspark/sql/readwriter.pyc > in json(self, path, schema) > 178 return > self._df(self._jreader.json(self._sqlContext._sc._jvm.PythonUtils.toSeq(path))) > 179 elif isinstance(path, RDD): > --> 180 return self._df(self._jreader.json(path._jrdd)) > 181 else: > 182 raise TypeError("path can be only string or RDD") > /usr/local/Cellar/apache-spark/1.6.0/libexec/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: > /usr/local/Cellar/apache-spark/1.6.0/libexec/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() > /usr/local/Cellar/apache-spark/1.6.0/libexec/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 o961.json. > : org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 > in stage 55.0 failed 1 times, most recent failure: Lost task 0.0 in stage > 55.0 (TID 149, localhost): java.lang.ClassCastException: [B cannot be cast to > java.lang.String > at > org.apache.spark.sql.execution.datasources.json.InferSchema$$anonfun$1$$anonfun$apply$1.apply(InferSchema.scala:53) > at scala.collection.Iterator$$anon$11.next(Iterator.scala:328) > at scala.collection.Iterator$class.foreach(Iterator.scala:727) > at scala.collection.AbstractIterator.foreach(Iterator.scala:1157) > at > scala.collection.TraversableOnce$class.foldLeft(TraversableOnce.scala:144) > at scala.collection.AbstractIterator.foldLeft(Iterator.scala:1157) > at > scala.collection.TraversableOnce$class.aggregate(TraversableOnce.scala:201) > at scala.collection.AbstractIterator.aggregate(Iterator.scala:1157) > at > org.apache.spark.rdd.RDD$$anonfun$treeAggregate$1$$anonfun$23.apply(RDD.scala:1121) > at > org.apache.spark.rdd.RDD$$anonfun$treeAggregate$1$$anonfun$23.apply(RDD.scala:1121) > at > org.apache.spark.rdd.RDD$$anonfun$treeAggregate$1$$anonfun$24.apply(RDD.scala:1122) > at > org.apache.spark.rdd.RDD$$anonfun$treeAggregate$1$$anonfun$24.apply(RDD.scala:1122) > at > org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$20.apply(RDD.scala:710) > at > org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$20.apply(RDD.scala:710) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:270) > at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66) > at org.apache.spark.scheduler.Task.run(Task.scala:89) > at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213) > at > java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) > at > java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) > at java.lang.Thread.run(Thread.java:745) > Driver stacktrace: > at > org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$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$$anon$1.run(EventLoop.scala:48) > at > org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:620) > at org.apache.spark.SparkContext.runJob(SparkContext.scala:1832) > at org.apache.spark.SparkContext.runJob(SparkContext.scala:1952) > at org.apache.spark.rdd.RDD$$anonfun$reduce$1.apply(RDD.scala:1025) > at > org.apache.spark.rdd.RDDOperationScope$.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.reduce(RDD.scala:1007) > at > org.apache.spark.rdd.RDD$$anonfun$treeAggregate$1.apply(RDD.scala:1136) > at > org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150) > at > org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:111) > at org.apache.spark.rdd.RDD.withScope(RDD.scala:316) > at org.apache.spark.rdd.RDD.treeAggregate(RDD.scala:1113) > at > org.apache.spark.sql.execution.datasources.json.InferSchema$.infer(InferSchema.scala:65) > at > org.apache.spark.sql.execution.datasources.json.JSONRelation$$anonfun$4.apply(JSONRelation.scala:114) > at > org.apache.spark.sql.execution.datasources.json.JSONRelation$$anonfun$4.apply(JSONRelation.scala:109) > at scala.Option.getOrElse(Option.scala:120) > at > org.apache.spark.sql.execution.datasources.json.JSONRelation.dataSchema$lzycompute(JSONRelation.scala:109) > at > org.apache.spark.sql.execution.datasources.json.JSONRelation.dataSchema(JSONRelation.scala:108) > at > org.apache.spark.sql.sources.HadoopFsRelation.schema$lzycompute(interfaces.scala:636) > at > org.apache.spark.sql.sources.HadoopFsRelation.schema(interfaces.scala:635) > at > org.apache.spark.sql.execution.datasources.LogicalRelation.<init>(LogicalRelation.scala:37) > at > org.apache.spark.sql.SQLContext.baseRelationToDataFrame(SQLContext.scala:442) > at org.apache.spark.sql.DataFrameReader.json(DataFrameReader.scala:288) > at org.apache.spark.sql.DataFrameReader.json(DataFrameReader.scala:275) > at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) > at > sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) > at > sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) > at java.lang.reflect.Method.invoke(Method.java:497) > at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231) > at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:381) > at py4j.Gateway.invoke(Gateway.java:259) > at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:133) > at py4j.commands.CallCommand.execute(CallCommand.java:79) > at py4j.GatewayConnection.run(GatewayConnection.java:209) > at java.lang.Thread.run(Thread.java:745) > Caused by: java.lang.ClassCastException: [B cannot be cast to java.lang.String > at > org.apache.spark.sql.execution.datasources.json.InferSchema$$anonfun$1$$anonfun$apply$1.apply(InferSchema.scala:53) > at scala.collection.Iterator$$anon$11.next(Iterator.scala:328) > at scala.collection.Iterator$class.foreach(Iterator.scala:727) > at scala.collection.AbstractIterator.foreach(Iterator.scala:1157) > at > scala.collection.TraversableOnce$class.foldLeft(TraversableOnce.scala:144) > at scala.collection.AbstractIterator.foldLeft(Iterator.scala:1157) > at > scala.collection.TraversableOnce$class.aggregate(TraversableOnce.scala:201) > at scala.collection.AbstractIterator.aggregate(Iterator.scala:1157) > at > org.apache.spark.rdd.RDD$$anonfun$treeAggregate$1$$anonfun$23.apply(RDD.scala:1121) > at > org.apache.spark.rdd.RDD$$anonfun$treeAggregate$1$$anonfun$23.apply(RDD.scala:1121) > at > org.apache.spark.rdd.RDD$$anonfun$treeAggregate$1$$anonfun$24.apply(RDD.scala:1122) > at > org.apache.spark.rdd.RDD$$anonfun$treeAggregate$1$$anonfun$24.apply(RDD.scala:1122) > at > org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$20.apply(RDD.scala:710) > at > org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$20.apply(RDD.scala:710) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:270) > at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66) > at org.apache.spark.scheduler.Task.run(Task.scala:89) > at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213) > at > java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) > at > java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) > ... 1 more > This seems related to SPARK-9964 -- 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