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https://issues.apache.org/jira/browse/SPARK-14105?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15210734#comment-15210734
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Liyin Tang edited comment on SPARK-14105 at 3/24/16 6:35 PM:
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Add the min code example to reproduce this issue in the jira description.
There is another way to work around this issue without changing KafkaRDD code,
which register a customized Kryo serialization implementation for Kafka
Message. In this way, we don't have to deep copy each message.
was (Author: liyin):
Add the min code example to reproduce this issue.
There is another way to work around this issue without changing KafkaRDD code,
which register a customized Kryo serialization implementation for Kafka
Message. In this way, we don't have to deep copy each message.
> Serialization issue for KafkaRDD
> --------------------------------
>
> Key: SPARK-14105
> URL: https://issues.apache.org/jira/browse/SPARK-14105
> Project: Spark
> Issue Type: Bug
> Components: Streaming
> Affects Versions: 1.5.2, 1.6.1
> Reporter: Liyin Tang
> Attachments: Screenshot 2016-03-23 09.04.51.png
>
>
> When using DISK or Memory to persistent KafkaDirectInputStream, it will
> serialize the FetchResponse into blocks. The FetchResponse contains the
> ByteBufferMessageSet where each Kafka Message is just one slice of the
> underlying ByteBuffer.
> When serializing the KafkaRDDIterator, it seems like the entire underlying
> ByteBuffer in ByteBufferMessageSet will be serialized for each and every
> message. This will cause block size easily exceeds 2G, and lead to
> "java.lang.OutOfMemoryError: Requested array size exceeds VM limit" or
> "FileChannelImpl.map -> exceeds Integer.MAX_VALUE:"
> The consumer fetch is the default value (1M). I tried to reduce fetch size,
> but it will cause other errors like errRanOutBeforeEnd.
> Here is the min code to reproduce this issue:
> ```
> // create source stream object
> val ssc = new StreamingContext(sparkConf, Seconds(intervalSeconds))
> // Create topic, kafkaParams, messageHandler and offsetnRanges
> val topicsSet: Set[String] = "flog".split(",").toSet
> val kafkaParams = Map[String, String]("metadata.broker.list" ->
> KafkaCluster.MAIN.getKafkaConnString)
> val messageHandler = (mmd: MessageAndMetadata[String, String]) => mmd
> val topicPartitionOffsetRange = KafkaOffsetsUtil.getKafkaOffsets(
> KafkaCluster.MAIN,
> topicsSet.toList.asJava,
>
> kafka.api.OffsetRequest.LatestTime).toMap.mapValues(Long2long).take(10)
> // Create an DStream
> val inputStream = KafkaUtils.createDirectStream[String, String,
> StringDecoder, StringDecoder, MessageAndMetadata[String, String]](
> ssc,
> kafkaParams,
> topicPartitionOffsetRange,
> messageHandler)
> // Apply window function
> inputStream.window(Seconds(slidingWindowInterval),
> Seconds(intervalSeconds)).foreachRDD(rdd => rdd.count())
> ssc.start()
> ssc.awaitTermination()
> ```
> Here are exceptions I got for both Memory and Disk persistent.
> Memory Persistent:
> 16/03/23 15:34:44 ERROR SparkUncaughtExceptionHandler: Uncaught exception in
> thread Thread[Executor task launch worker-9,5,main]
> java.lang.OutOfMemoryError: Requested array size exceeds VM limit
> at java.util.Arrays.copyOf(Arrays.java:3236)
> at java.io.ByteArrayOutputStream.grow(ByteArrayOutputStream.java:113)
> at
> java.io.ByteArrayOutputStream.ensureCapacity(ByteArrayOutputStream.java:93)
> at java.io.ByteArrayOutputStream.write(ByteArrayOutputStream.java:140)
> at java.io.BufferedOutputStream.flushBuffer(BufferedOutputStream.java:82)
> at java.io.BufferedOutputStream.write(BufferedOutputStream.java:126)
> at com.esotericsoftware.kryo.io.Output.flush(Output.java:155)
> at com.esotericsoftware.kryo.io.Output.require(Output.java:135)
> at com.esotericsoftware.kryo.io.Output.writeBytes(Output.java:220)
> at com.esotericsoftware.kryo.io.Output.writeBytes(Output.java:206)
> at
> com.esotericsoftware.kryo.serializers.DefaultArraySerializers$ByteArraySerializer.write(DefaultArraySerializers.java:29)
> at
> com.esotericsoftware.kryo.serializers.DefaultArraySerializers$ByteArraySerializer.write(DefaultArraySerializers.java:18)
> at com.esotericsoftware.kryo.Kryo.writeObjectOrNull(Kryo.java:549)
> at
> com.esotericsoftware.kryo.serializers.FieldSerializer$ObjectField.write(FieldSerializer.java:570)
> at
> com.esotericsoftware.kryo.serializers.FieldSerializer.write(FieldSerializer.java:213)
> at com.esotericsoftware.kryo.Kryo.writeObject(Kryo.java:501)
> at
> com.esotericsoftware.kryo.serializers.FieldSerializer$ObjectField.write(FieldSerializer.java:564)
> at
> com.esotericsoftware.kryo.serializers.FieldSerializer.write(FieldSerializer.java:213)
> at com.esotericsoftware.kryo.Kryo.writeObject(Kryo.java:501)
> at
> com.esotericsoftware.kryo.serializers.FieldSerializer$ObjectField.write(FieldSerializer.java:564)
> at
> com.esotericsoftware.kryo.serializers.FieldSerializer.write(FieldSerializer.java:213)
> at com.esotericsoftware.kryo.Kryo.writeClassAndObject(Kryo.java:568)
> at
> org.apache.spark.serializer.KryoSerializationStream.writeObject(KryoSerializer.scala:158)
> at
> org.apache.spark.serializer.SerializationStream.writeAll(Serializer.scala:153)
> at
> org.apache.spark.storage.BlockManager.dataSerializeStream(BlockManager.scala:1190)
> at
> org.apache.spark.storage.BlockManager.dataSerialize(BlockManager.scala:1199)
> at org.apache.spark.storage.MemoryStore.putArray(MemoryStore.scala:132)
> at org.apache.spark.storage.BlockManager.doPut(BlockManager.scala:793)
> at org.apache.spark.storage.BlockManager.putArray(BlockManager.scala:669)
> at org.apache.spark.CacheManager.putInBlockManager(CacheManager.scala:175)
> at org.apache.spark.CacheManager.getOrCompute(CacheManager.scala:78)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:262)
> Disk Persistent:
> 16/03/23 17:04:00 INFO TaskSetManager: Lost task 42.1 in stage 2.0 (TID 974)
> on executor i-2878ceb3.inst.aws.airbnb.com: java.lang.RuntimeException
> (java.lang.IllegalArgumentException: Size exceeds Integer.MAX_VALUE
> at sun.nio.ch.FileChannelImpl.map(FileChannelImpl.java:836)
> at
> org.apache.spark.storage.DiskStore$$anonfun$getBytes$2.apply(DiskStore.scala:125)
> at
> org.apache.spark.storage.DiskStore$$anonfun$getBytes$2.apply(DiskStore.scala:113)
> at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1206)
> at org.apache.spark.storage.DiskStore.getBytes(DiskStore.scala:127)
> at org.apache.spark.storage.DiskStore.getBytes(DiskStore.scala:134)
> at
> org.apache.spark.storage.BlockManager.doGetLocal(BlockManager.scala:512)
> at
> org.apache.spark.storage.BlockManager.getBlockData(BlockManager.scala:302)
>
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