Here is the code snippet, starting line 365 in KafkaCluster.scala:
type Err = ArrayBuffer[Throwable]
/** If the result is right, return it, otherwise throw SparkException */
def checkErrors[T](result: Either[Err, T]): T = {
result.fold(
errs => throw new SparkException(errs.mkString("Throwing this errir\n")),
ok => ok
)
}
On Thu, Sep 24, 2015 at 3:00 PM, Sourabh Chandak <sourabh3...@gmail.com>
wrote:
> I was able to get pass this issue. I was pointing the SSL port whereas
> SimpleConsumer should point to the PLAINTEXT port. But after fixing that I
> am getting the following error:
>
> Exception in thread "main" org.apache.spark.SparkException:
> java.nio.BufferUnderflowException
> at
> org.apache.spark.streaming.kafka.KafkaCluster$$anonfun$checkErrors$1.apply(KafkaCluster.scala:366)
> at
> org.apache.spark.streaming.kafka.KafkaCluster$$anonfun$checkErrors$1.apply(KafkaCluster.scala:366)
> at scala.util.Either.fold(Either.scala:97)
> at
> org.apache.spark.streaming.kafka.KafkaCluster$.checkErrors(KafkaCluster.scala:365)
> at
> org.apache.spark.streaming.kafka.KafkaUtils$.createDirectStream(KafkaUtils.scala:309)
> at
> org.ofe.weve.test.KafkaTest$.setupProcessingContext(KafkaTest.scala:36)
> at org.ofe.weve.test.KafkaTest$.main(KafkaTest.scala:59)
> at org.ofe.weve.test.KafkaTest.main(KafkaTest.scala)
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at
> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
> at
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:497)
> at
> org.apache.spark.deploy.SparkSubmit$.launch(SparkSubmit.scala:358)
> at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:75)
> at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
>
> Thanks,
> Sourabh
>
> On Thu, Sep 24, 2015 at 2:04 PM, Cody Koeninger <c...@koeninger.org>
> wrote:
>
>> That looks like the OOM is in the driver, when getting partition metadata
>> to create the direct stream. In that case, executor memory allocation
>> doesn't matter.
>>
>> Allocate more driver memory, or put a profiler on it to see what's taking
>> up heap.
>>
>>
>>
>> On Thu, Sep 24, 2015 at 3:51 PM, Sourabh Chandak <sourabh3...@gmail.com>
>> wrote:
>>
>>> Adding Cody and Sriharsha
>>>
>>> On Thu, Sep 24, 2015 at 1:25 PM, Sourabh Chandak <sourabh3...@gmail.com>
>>> wrote:
>>>
>>>> Hi,
>>>>
>>>> I have ported receiver less spark streaming for kafka to Spark 1.2 and
>>>> am trying to run a spark streaming job to consume data form my broker, but
>>>> I am getting the following error:
>>>>
>>>> 15/09/24 20:17:45 ERROR BoundedByteBufferReceive: OOME with size
>>>> 352518400
>>>> java.lang.OutOfMemoryError: Java heap space
>>>> at java.nio.HeapByteBuffer.<init>(HeapByteBuffer.java:57)
>>>> at java.nio.ByteBuffer.allocate(ByteBuffer.java:335)
>>>> at
>>>> kafka.network.BoundedByteBufferReceive.byteBufferAllocate(BoundedByteBufferReceive.scala:80)
>>>> at
>>>> kafka.network.BoundedByteBufferReceive.readFrom(BoundedByteBufferReceive.scala:63)
>>>> at
>>>> kafka.network.Receive$class.readCompletely(Transmission.scala:56)
>>>> at
>>>> kafka.network.BoundedByteBufferReceive.readCompletely(BoundedByteBufferReceive.scala:29)
>>>> at
>>>> kafka.network.BlockingChannel.receive(BlockingChannel.scala:111)
>>>> at
>>>> kafka.consumer.SimpleConsumer.liftedTree1$1(SimpleConsumer.scala:83)
>>>> at
>>>> kafka.consumer.SimpleConsumer.kafka$consumer$SimpleConsumer$$sendRequest(SimpleConsumer.scala:80)
>>>> at kafka.consumer.SimpleConsumer.send(SimpleConsumer.scala:103)
>>>> at
>>>> org.apache.spark.streaming.kafka.KafkaCluster$$anonfun$getPartitionMetadata$1.apply(KafkaCluster.scala:126)
>>>> at
>>>> org.apache.spark.streaming.kafka.KafkaCluster$$anonfun$getPartitionMetadata$1.apply(KafkaCluster.scala:125)
>>>> at
>>>> org.apache.spark.streaming.kafka.KafkaCluster$$anonfun$org$apache$spark$streaming$kafka$KafkaCluster$$withBrokers$1.apply(KafkaCluster.scala:346)
>>>> at
>>>> org.apache.spark.streaming.kafka.KafkaCluster$$anonfun$org$apache$spark$streaming$kafka$KafkaCluster$$withBrokers$1.apply(KafkaCluster.scala:342)
>>>> at
>>>> scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
>>>> at
>>>> scala.collection.mutable.WrappedArray.foreach(WrappedArray.scala:34)
>>>> at org.apache.spark.streaming.kafka.KafkaCluster.org
>>>> $apache$spark$streaming$kafka$KafkaCluster$$withBrokers(KafkaCluster.scala:342)
>>>> at
>>>> org.apache.spark.streaming.kafka.KafkaCluster.getPartitionMetadata(KafkaCluster.scala:125)
>>>> at
>>>> org.apache.spark.streaming.kafka.KafkaCluster.getPartitions(KafkaCluster.scala:112)
>>>> at
>>>> org.apache.spark.streaming.kafka.KafkaUtils$.createDirectStream(KafkaUtils.scala:296)
>>>> at
>>>> org.ofe.weve.test.KafkaTest$.setupProcessingContext(KafkaTest.scala:35)
>>>> at org.ofe.weve.test.KafkaTest$.main(KafkaTest.scala:58)
>>>> at org.ofe.weve.test.KafkaTest.main(KafkaTest.scala)
>>>> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
>>>> at
>>>> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
>>>> at
>>>> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
>>>> at java.lang.reflect.Method.invoke(Method.java:497)
>>>> at
>>>> org.apache.spark.deploy.SparkSubmit$.launch(SparkSubmit.scala:358)
>>>> at
>>>> org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:75)
>>>> at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
>>>>
>>>>
>>>>
>>>> I have tried allocating 100G of memory with 1 executor but it is still
>>>> failing.
>>>>
>>>> Spark version: 1.2.2
>>>> Kafka version ported: 0.8.2
>>>> Kafka server version: trunk version with SSL enabled
>>>>
>>>> Can someone please help me debug this.
>>>>
>>>> Thanks,
>>>> Sourabh
>>>>
>>>
>>>
>>
>
