Hi,

I'm trying to read an avro file into a spark RDD, but I'm having
an Exception while getting task result.

The avro schema file has the following content:
{
  "type" : "record",
  "name" : "sample_schema",
  "namespace" : "com.adomik.avro",
  "fields" : [ {
    "name" : "username",
    "type" : "string",
    "doc"  : "Name of the user account"
  }, {
    "name" : "events",
    "type" : {
      "type" : "array",
      "items" : {
        "name":"Event",
        "type":"record",
        "fields":[
          {"name":"action", "type":"string"}, {"name":"value",
"type":"long"}
        ]
      }
    },
    "doc"  : "The content of the user's Events message"
  } ],
  "doc:" : "A basic schema for storing Events messages"
}

I create the avro file using avro-tools.jar file from the following json
file:
{"username":"miguno","events": [{"action":"signed", "value": 1}, {"action":
"loged", "value":1}] }
{"username":"blizzard","events": [{"action":"logout", "value": 2},
{"action": "visited", "value":3}] }

$ java -jar avro-tools-1.7.7.jar fromjson --schema-file myschema.avsc
data.json > data.avro

I can correctly read the generated avro file with the avro-tools.jar as
follows:
$ java -jar avro-tools-1.7.7.jar tojson data.avro

However I'm having an exception when I try to read this generated avro file
into a Spark RDD from spark shell as follows:

> import org.apache.avro.mapred.AvroInputFormat
> import org.apache.avro.mapred.AvroWrapper
> import org.apache.hadoop.io.NullWritable
> import org.apache.hadoop.io.Text
> import org.apache.avro.generic.GenericRecord

> val input = "/home/arbi/avro/data.avro"
> val rdd = sc.hadoopFile(
  input,
  classOf[AvroInputFormat[GenericRecord]],
  classOf[AvroWrapper[GenericRecord]],
  classOf[NullWritable]
)

Then when I call rdd.next, I see the following exception:

15/07/23 14:30:48 ERROR TaskResultGetter: Exception while getting task
result

com.esotericsoftware.kryo.KryoException: java.lang.NullPointerException

Serialization trace:

values (org.apache.avro.generic.GenericData$Record)

datum (org.apache.avro.mapred.AvroWrapper)

at
com.esotericsoftware.kryo.serializers.FieldSerializer$ObjectField.read(FieldSerializer.java:626)

at
com.esotericsoftware.kryo.serializers.FieldSerializer.read(FieldSerializer.java:221)

at com.esotericsoftware.kryo.Kryo.readObject(Kryo.java:648)

at
com.esotericsoftware.kryo.serializers.FieldSerializer$ObjectField.read(FieldSerializer.java:605)

at
com.esotericsoftware.kryo.serializers.FieldSerializer.read(FieldSerializer.java:221)

at com.esotericsoftware.kryo.Kryo.readClassAndObject(Kryo.java:729)

at com.twitter.chill.Tuple2Serializer.read(TupleSerializers.scala:41)

at com.twitter.chill.Tuple2Serializer.read(TupleSerializers.scala:33)

at com.esotericsoftware.kryo.Kryo.readClassAndObject(Kryo.java:729)

at
com.esotericsoftware.kryo.serializers.DefaultArraySerializers$ObjectArraySerializer.read(DefaultArraySerializers.java:338)

at
com.esotericsoftware.kryo.serializers.DefaultArraySerializers$ObjectArraySerializer.read(DefaultArraySerializers.java:293)

at com.esotericsoftware.kryo.Kryo.readClassAndObject(Kryo.java:729)

at
org.apache.spark.serializer.KryoSerializerInstance.deserialize(KryoSerializer.scala:173)

at org.apache.spark.scheduler.DirectTaskResult.value(TaskResult.scala:79)

at
org.apache.spark.scheduler.TaskSetManager.handleSuccessfulTask(TaskSetManager.scala:621)

at
org.apache.spark.scheduler.TaskSchedulerImpl.handleSuccessfulTask(TaskSchedulerImpl.scala:379)

at
org.apache.spark.scheduler.TaskResultGetter$$anon$2$$anonfun$run$1.apply$mcV$sp(TaskResultGetter.scala:82)

at
org.apache.spark.scheduler.TaskResultGetter$$anon$2$$anonfun$run$1.apply(TaskResultGetter.scala:51)

at
org.apache.spark.scheduler.TaskResultGetter$$anon$2$$anonfun$run$1.apply(TaskResultGetter.scala:51)

at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1618)

at
org.apache.spark.scheduler.TaskResultGetter$$anon$2.run(TaskResultGetter.scala:50)

at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)

at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)

at java.lang.Thread.run(Thread.java:745)

Caused by: java.lang.NullPointerException

at org.apache.avro.generic.GenericData$Array.add(GenericData.java:200)

at
com.esotericsoftware.kryo.serializers.CollectionSerializer.read(CollectionSerializer.java:109)

at
com.esotericsoftware.kryo.serializers.CollectionSerializer.read(CollectionSerializer.java:18)

at com.esotericsoftware.kryo.Kryo.readClassAndObject(Kryo.java:729)

at
com.esotericsoftware.kryo.serializers.DefaultArraySerializers$ObjectArraySerializer.read(DefaultArraySerializers.java:338)

at
com.esotericsoftware.kryo.serializers.DefaultArraySerializers$ObjectArraySerializer.read(DefaultArraySerializers.java:293)

at com.esotericsoftware.kryo.Kryo.readObject(Kryo.java:648)

at
com.esotericsoftware.kryo.serializers.FieldSerializer$ObjectField.read(FieldSerializer.java:605)

... 23 more

org.apache.spark.SparkException: Job aborted due to stage failure:
Exception while getting task result:
com.esotericsoftware.kryo.KryoException: java.lang.NullPointerException

Serialization trace:

values (org.apache.avro.generic.GenericData$Record)

datum (org.apache.avro.mapred.AvroWrapper)

at org.apache.spark.scheduler.DAGScheduler.org
$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1204)

at
org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1193)

at
org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1192)

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:1192)

at
org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:693)

at
org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:693)

at scala.Option.foreach(Option.scala:236)

at
org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:693)

at
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1393)

at
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1354)

at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)


Any idea what's causing this error? is the presence of arrays in avro
causes problem when generating spark RDDs??

Bests,

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