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?
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