I got the following when parsing your input with master branch (Python version 2.6.6):
http://pastebin.com/1w8WM3tz FYI On Fri, Oct 2, 2015 at 1:42 PM, balajikvijayan <balaji.k.vija...@gmail.com> wrote: > Running Windows 8.1, Python 2.7.x, Scala 2.10.5, Spark 1.4.1. > > I'm trying to read in a large quantity of json data in a couple of files > and > I receive a scala.MatchError when I do so. Json, Python and stack trace all > shown below. > > Json: > > { > "dataunit": { > "page_view": { > "nonce": 438058072, > "person": { > "user_id": 5846 > }, > "page": { > "url": "http://mysite.com/blog"; > } > } > }, > "pedigree": { > "true_as_of_secs": 1438627992 > } > } > > Python: > > import pyspark > sc = pyspark.SparkContext() > sqlContext = pyspark.SQLContext(sc) > pageviews = sqlContext.read.json("[Path to folder containing file with > above > json]") > pageviews.collect() > > Stack Trace: > Py4JJavaError: An error occurred while calling > z:org.apache.spark.api.python.PythonRDD.collectAndServe. > : org.apache.spark.SparkException: Job aborted due to stage failure: Task 1 > in stage 32.0 failed 1 times, most recent failure: Lost task 1.0 in stage > 32.0 (TID 133, localhost): scala.MatchError: > (VALUE_STRING,ArrayType(StructType(),true)) (of class scala.Tuple2) > at > > org.apache.spark.sql.json.JacksonParser$.convertField(JacksonParser.scala:49) > at > > org.apache.spark.sql.json.JacksonParser$$anonfun$parseJson$1$$anonfun$apply$1.apply(JacksonParser.scala:201) > at > > org.apache.spark.sql.json.JacksonParser$$anonfun$parseJson$1$$anonfun$apply$1.apply(JacksonParser.scala:193) > at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371) > at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327) > at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327) > at > > org.apache.spark.api.python.SerDeUtil$AutoBatchedPickler.hasNext(SerDeUtil.scala:116) > at scala.collection.Iterator$class.foreach(Iterator.scala:727) > at > > org.apache.spark.api.python.SerDeUtil$AutoBatchedPickler.foreach(SerDeUtil.scala:111) > at > scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48) > at > scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103) > at > scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47) > at scala.collection.TraversableOnce$class.to > (TraversableOnce.scala:273) > at > > org.apache.spark.api.python.SerDeUtil$AutoBatchedPickler.to(SerDeUtil.scala:111) > at > scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265) > at > > org.apache.spark.api.python.SerDeUtil$AutoBatchedPickler.toBuffer(SerDeUtil.scala:111) > at > scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252) > at > > org.apache.spark.api.python.SerDeUtil$AutoBatchedPickler.toArray(SerDeUtil.scala:111) > at > > org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$12.apply(RDD.scala:885) > at > > org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$12.apply(RDD.scala:885) > at > > org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1767) > at > > org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1767) > at > org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:63) > at org.apache.spark.scheduler.Task.run(Task.scala:70) > at > org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213) > at > > java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) > at > > java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) > at java.lang.Thread.run(Thread.java:745) > > Driver stacktrace: > at > org.apache.spark.scheduler.DAGScheduler.org > $apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1273) > at > > org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1264) > at > > org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1263) > at > > scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) > at > scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47) > at > org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1263) > at > > org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:730) > at > > org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:730) > at scala.Option.foreach(Option.scala:236) > at > > org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:730) > at > > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1457) > at > > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1418) > at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48) > > It seems like this issue has been resolved in scala per SPARK-3390 > <https://issues.apache.org/jira/browse/SPARK-3390> ; any thoughts on the > root cause of this in pyspark? > > > > -- > View this message in context: > http://apache-spark-user-list.1001560.n3.nabble.com/Reading-JSON-in-Pyspark-throws-scala-MatchError-tp24911.html > Sent from the Apache Spark User List mailing list archive at Nabble.com. > > --------------------------------------------------------------------- > To unsubscribe, e-mail: user-unsubscr...@spark.apache.org > For additional commands, e-mail: user-h...@spark.apache.org > >
