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Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2016/01/29 21:52:40 UTC
[jira] [Assigned] (SPARK-13082) sqlCtx.real.json() doesn't work
with PythonRDD
[ https://issues.apache.org/jira/browse/SPARK-13082?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Apache Spark reassigned SPARK-13082:
------------------------------------
Assignee: (was: 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: Gaëtan Lehmann
>
> 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
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