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 <zjf...@gmail.com> 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 <dav...@databricks.com> wrote: > >> Could you create a JIRA to track this bug? >> >> 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 >> > >> >> --------------------------------------------------------------------- >> To unsubscribe, e-mail: user-unsubscr...@spark.apache.org >> For additional commands, e-mail: user-h...@spark.apache.org >> >> > > > -- > Best Regards > > Jeff Zhang > -- Best Regards Jeff Zhang