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From "Apache Spark (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-13082) sqlCtx.real.json() doesn't work with PythonRDD
Date Fri, 29 Jan 2016 20:52:39 GMT

    [ https://issues.apache.org/jira/browse/SPARK-13082?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15124189#comment-15124189
] 

Apache Spark commented on SPARK-13082:
--------------------------------------

User 'zsxwing' has created a pull request for this issue:
https://github.com/apache/spark/pull/10988

> 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
>
> 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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