You are correct, that was the issue.
On Tue, Oct 20, 2015 at 10:18 PM, Jeff Zhang wrote:
> BTW, I think Json Parser should verify the json format at least when
> inferring the schema of json.
>
> On Wed, Oct 21, 2015 at 12:59 PM, Jeff Zhang wrote:
>
>> I think this is due to the json file format. DataFrame can only accept
>> json file with one valid record per line. Multiple line per record is
>> invalid for DataFrame.
>>
>>
>> On Tue, Oct 6, 2015 at 2:48 AM, Davies Liu wrote:
>>
>>> Could you create a JIRA to track this bug?
>>>
>>> On Fri, Oct 2, 2015 at 1:42 PM, balajikvijayan
>>> 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
