我无法在RDD [ConsumerRecord]上进行转换 [英] I can't do transformation on a RDD[ConsumerRecord]
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问题描述
我在从DStream的kafka主题中恢复ConsumerRecord时遇到序列化问题.为了说明我的问题，我创建了以下示例.我创建一个带有json值的ConsumerRecord，然后将其放入rdd中.我进行收集以打印结果.我收到序列化错误.这是示例:
I have a serialization problem with a ConsumerRecord recover from a kafka topic in a DStream. To illustrate my problem, I create the following exemple. I create a ConsumerRecord with a json value, I put it inside a rdd. I do a collect in order to print result. I get a serialization error. here is the Exemple:
import org.apache.kafka.clients.consumer.ConsumerRecord
import org.apache.log4j.{Level, Logger}
import org.apache.spark.{SparkConf, SparkContext}
object Exemple {
def main(args: Array[String]): Unit = {
Logger.getLogger("org").setLevel(Level.ERROR)
Logger.getLogger("akka").setLevel(Level.ERROR)
val conf = new SparkConf().setMaster("local[*]").setAppName("Exemple")
val sc = new SparkContext(conf)
val consumerRecord: ConsumerRecord[String, String] = new ConsumerRecord("",1,2l,"myTopic","""{"id":1}""")
val rdd = sc.parallelize(List(consumerRecord))
val valueRDD = rdd.map(cr => cr.value)
valueRDD.collect.foreach(println) // this line throws error
}
}
我收到以下错误:
Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[Stage 0:> (0 + 0) / 4]18/03/02 00:58:55 ERROR Utils: Exception encountered
java.io.NotSerializableException: org.apache.kafka.clients.consumer.ConsumerRecord
at java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1184)
at java.io.ObjectOutputStream.writeArray(ObjectOutputStream.java:1378)
at java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1174)
at java.io.ObjectOutputStream.defaultWriteFields(ObjectOutputStream.java:1548)
at java.io.ObjectOutputStream.writeSerialData(ObjectOutputStream.java:1509)
at java.io.ObjectOutputStream.writeOrdinaryObject(ObjectOutputStream.java:1432)
at java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1178)
at java.io.ObjectOutputStream.defaultWriteFields(ObjectOutputStream.java:1548)
at java.io.ObjectOutputStream.defaultWriteObject(ObjectOutputStream.java:441)
at org.apache.spark.rdd.ParallelCollectionPartition$$anonfun$writeObject$1.apply$mcV$sp(ParallelCollectionRDD.scala:59)
at org.apache.spark.rdd.ParallelCollectionPartition$$anonfun$writeObject$1.apply(ParallelCollectionRDD.scala:51)
at org.apache.spark.rdd.ParallelCollectionPartition$$anonfun$writeObject$1.apply(ParallelCollectionRDD.scala:51)
at org.apache.spark.util.Utils$.tryOrIOException(Utils.scala:1303)
at org.apache.spark.rdd.ParallelCollectionPartition.writeObject(ParallelCollectionRDD.scala:51)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at java.io.ObjectStreamClass.invokeWriteObject(ObjectStreamClass.java:1028)
at java.io.ObjectOutputStream.writeSerialData(ObjectOutputStream.java:1496)
at java.io.ObjectOutputStream.writeOrdinaryObject(ObjectOutputStream.java:1432)
at java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1178)
at java.io.ObjectOutputStream.defaultWriteFields(ObjectOutputStream.java:1548)
at java.io.ObjectOutputStream.writeSerialData(ObjectOutputStream.java:1509)
at java.io.ObjectOutputStream.writeOrdinaryObject(ObjectOutputStream.java:1432)
at java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1178)
at java.io.ObjectOutputStream.writeObject(ObjectOutputStream.java:348)
at org.apache.spark.serializer.JavaSerializationStream.writeObject(JavaSerializer.scala:43)
at org.apache.spark.serializer.JavaSerializerInstance.serialize(JavaSerializer.scala:100)
at org.apache.spark.scheduler.TaskSetManager$$anonfun$resourceOffer$1.apply(TaskSetManager.scala:472)
at org.apache.spark.scheduler.TaskSetManager$$anonfun$resourceOffer$1.apply(TaskSetManager.scala:453)
at scala.Option.map(Option.scala:146)
at org.apache.spark.scheduler.TaskSetManager.resourceOffer(TaskSetManager.scala:453)
at org.apache.spark.scheduler.TaskSchedulerImpl$$anonfun$org$apache$spark$scheduler$TaskSchedulerImpl$$resourceOfferSingleTaskSet$1.apply$mcVI$sp(TaskSchedulerImpl.scala:295)
at scala.collection.immutable.Range.foreach$mVc$sp(Range.scala:160)
at org.apache.spark.scheduler.TaskSchedulerImpl.org$apache$spark$scheduler$TaskSchedulerImpl$$resourceOfferSingleTaskSet(TaskSchedulerImpl.scala:290)
at org.apache.spark.scheduler.TaskSchedulerImpl$$anonfun$resourceOffers$4$$anonfun$apply$9.apply(TaskSchedulerImpl.scala:375)
at org.apache.spark.scheduler.TaskSchedulerImpl$$anonfun$resourceOffers$4$$anonfun$apply$9.apply(TaskSchedulerImpl.scala:373)
at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:186)
at org.apache.spark.scheduler.TaskSchedulerImpl$$anonfun$resourceOffers$4.apply(TaskSchedulerImpl.scala:373)
at org.apache.spark.scheduler.TaskSchedulerImpl$$anonfun$resourceOffers$4.apply(TaskSchedulerImpl.scala:370)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.TaskSchedulerImpl.resourceOffers(TaskSchedulerImpl.scala:370)
at org.apache.spark.scheduler.local.LocalEndpoint.reviveOffers(LocalSchedulerBackend.scala:85)
at org.apache.spark.scheduler.local.LocalEndpoint$$anonfun$receive$1.applyOrElse(LocalSchedulerBackend.scala:64)
at org.apache.spark.rpc.netty.Inbox$$anonfun$process$1.apply$mcV$sp(Inbox.scala:117)
at org.apache.spark.rpc.netty.Inbox.safelyCall(Inbox.scala:205)
at org.apache.spark.rpc.netty.Inbox.process(Inbox.scala:101)
at org.apache.spark.rpc.netty.Dispatcher$MessageLoop.run(Dispatcher.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)
18/03/02 00:58:55 ERROR Utils: Exception encountered
java.io.NotSerializableException: org.apache.kafka.clients.consumer.ConsumerRecord
at java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1184)
at java.io.ObjectOutputStream.writeArray(ObjectOutputStream.java:1378)
at java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1174)
at java.io.ObjectOutputStream.defaultWriteFields(ObjectOutputStream.java:1548)
at java.io.ObjectOutputStream.writeSerialData(ObjectOutputStream.java:1509)
at java.io.ObjectOutputStream.writeOrdinaryObject(ObjectOutputStream.java:1432)
at java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1178)
at java.io.ObjectOutputStream.defaultWriteFields(ObjectOutputStream.java:1548)
at java.io.ObjectOutputStream.defaultWriteObject(ObjectOutputStream.java:441)
at org.apache.spark.rdd.ParallelCollectionPartition$$anonfun$writeObject$1.apply$mcV$sp(ParallelCollectionRDD.scala:59)
at org.apache.spark.rdd.ParallelCollectionPartition$$anonfun$writeObject$1.apply(ParallelCollectionRDD.scala:51)
at org.apache.spark.rdd.ParallelCollectionPartition$$anonfun$writeObject$1.apply(ParallelCollectionRDD.scala:51)
at org.apache.spark.util.Utils$.tryOrIOException(Utils.scala:1303)
at org.apache.spark.rdd.ParallelCollectionPartition.writeObject(ParallelCollectionRDD.scala:51)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at java.io.ObjectStreamClass.invokeWriteObject(ObjectStreamClass.java:1028)
at java.io.ObjectOutputStream.writeSerialData(ObjectOutputStream.java:1496)
at java.io.ObjectOutputStream.writeOrdinaryObject(ObjectOutputStream.java:1432)
at java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1178)
at java.io.ObjectOutputStream.writeObject(ObjectOutputStream.java:348)
at org.apache.spark.serializer.SerializationDebugger$SerializationDebugger.visitSerializableWithWriteObjectMethod(SerializationDebugger.scala:230)
at org.apache.spark.serializer.SerializationDebugger$SerializationDebugger.visitSerializable(SerializationDebugger.scala:189)
at org.apache.spark.serializer.SerializationDebugger$SerializationDebugger.visit(SerializationDebugger.scala:108)
at org.apache.spark.serializer.SerializationDebugger$SerializationDebugger.visitSerializable(SerializationDebugger.scala:206)
at org.apache.spark.serializer.SerializationDebugger$SerializationDebugger.visit(SerializationDebugger.scala:108)
at org.apache.spark.serializer.SerializationDebugger$.find(SerializationDebugger.scala:67)
at org.apache.spark.serializer.SerializationDebugger$.improveException(SerializationDebugger.scala:41)
at org.apache.spark.serializer.JavaSerializationStream.writeObject(JavaSerializer.scala:46)
at org.apache.spark.serializer.JavaSerializerInstance.serialize(JavaSerializer.scala:100)
at org.apache.spark.scheduler.TaskSetManager$$anonfun$resourceOffer$1.apply(TaskSetManager.scala:472)
at org.apache.spark.scheduler.TaskSetManager$$anonfun$resourceOffer$1.apply(TaskSetManager.scala:453)
at scala.Option.map(Option.scala:146)
at org.apache.spark.scheduler.TaskSetManager.resourceOffer(TaskSetManager.scala:453)
at org.apache.spark.scheduler.TaskSchedulerImpl$$anonfun$org$apache$spark$scheduler$TaskSchedulerImpl$$resourceOfferSingleTaskSet$1.apply$mcVI$sp(TaskSchedulerImpl.scala:295)
at scala.collection.immutable.Range.foreach$mVc$sp(Range.scala:160)
at org.apache.spark.scheduler.TaskSchedulerImpl.org$apache$spark$scheduler$TaskSchedulerImpl$$resourceOfferSingleTaskSet(TaskSchedulerImpl.scala:290)
at org.apache.spark.scheduler.TaskSchedulerImpl$$anonfun$resourceOffers$4$$anonfun$apply$9.apply(TaskSchedulerImpl.scala:375)
at org.apache.spark.scheduler.TaskSchedulerImpl$$anonfun$resourceOffers$4$$anonfun$apply$9.apply(TaskSchedulerImpl.scala:373)
at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:186)
at org.apache.spark.scheduler.TaskSchedulerImpl$$anonfun$resourceOffers$4.apply(TaskSchedulerImpl.scala:373)
at org.apache.spark.scheduler.TaskSchedulerImpl$$anonfun$resourceOffers$4.apply(TaskSchedulerImpl.scala:370)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.TaskSchedulerImpl.resourceOffers(TaskSchedulerImpl.scala:370)
at org.apache.spark.scheduler.local.LocalEndpoint.reviveOffers(LocalSchedulerBackend.scala:85)
at org.apache.spark.scheduler.local.LocalEndpoint$$anonfun$receive$1.applyOrElse(LocalSchedulerBackend.scala:64)
at org.apache.spark.rpc.netty.Inbox$$anonfun$process$1.apply$mcV$sp(Inbox.scala:117)
at org.apache.spark.rpc.netty.Inbox.safelyCall(Inbox.scala:205)
at org.apache.spark.rpc.netty.Inbox.process(Inbox.scala:101)
at org.apache.spark.rpc.netty.Dispatcher$MessageLoop.run(Dispatcher.scala:213)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
18/03/02 00:58:55 ERROR TaskSetManager: Failed to serialize task 3, not attempting to retry it.
java.io.NotSerializableException: org.apache.kafka.clients.consumer.ConsumerRecord
Serialization stack:
- object not serializable (class: org.apache.kafka.clients.consumer.ConsumerRecord, value: ConsumerRecord(topic = , partition = 1, offset = 2, NoTimestampType = -1, checksum = -1, serialized key size = -1, serialized value size = -1, key = myTopic, value = {"id":1}))
- element of array (index: 0)
- array (class [Lorg.apache.kafka.clients.consumer.ConsumerRecord;, size 1)
- field (class: scala.collection.mutable.WrappedArray$ofRef, name: array, type: class [Ljava.lang.Object;)
- object (class scala.collection.mutable.WrappedArray$ofRef, WrappedArray(ConsumerRecord(topic = , partition = 1, offset = 2, NoTimestampType = -1, checksum = -1, serialized key size = -1, serialized value size = -1, key = myTopic, value = {"id":1})))
- writeObject data (class: org.apache.spark.rdd.ParallelCollectionPartition)
- object (class org.apache.spark.rdd.ParallelCollectionPartition, org.apache.spark.rdd.ParallelCollectionPartition@694)
- field (class: org.apache.spark.scheduler.ResultTask, name: partition, type: interface org.apache.spark.Partition)
- object (class org.apache.spark.scheduler.ResultTask, ResultTask(0, 3))
at org.apache.spark.serializer.SerializationDebugger$.improveException(SerializationDebugger.scala:40)
at org.apache.spark.serializer.JavaSerializationStream.writeObject(JavaSerializer.scala:46)
at org.apache.spark.serializer.JavaSerializerInstance.serialize(JavaSerializer.scala:100)
at org.apache.spark.scheduler.TaskSetManager$$anonfun$resourceOffer$1.apply(TaskSetManager.scala:472)
at org.apache.spark.scheduler.TaskSetManager$$anonfun$resourceOffer$1.apply(TaskSetManager.scala:453)
at scala.Option.map(Option.scala:146)
at org.apache.spark.scheduler.TaskSetManager.resourceOffer(TaskSetManager.scala:453)
at org.apache.spark.scheduler.TaskSchedulerImpl$$anonfun$org$apache$spark$scheduler$TaskSchedulerImpl$$resourceOfferSingleTaskSet$1.apply$mcVI$sp(TaskSchedulerImpl.scala:295)
at scala.collection.immutable.Range.foreach$mVc$sp(Range.scala:160)
at org.apache.spark.scheduler.TaskSchedulerImpl.org$apache$spark$scheduler$TaskSchedulerImpl$$resourceOfferSingleTaskSet(TaskSchedulerImpl.scala:290)
at org.apache.spark.scheduler.TaskSchedulerImpl$$anonfun$resourceOffers$4$$anonfun$apply$9.apply(TaskSchedulerImpl.scala:375)
at org.apache.spark.scheduler.TaskSchedulerImpl$$anonfun$resourceOffers$4$$anonfun$apply$9.apply(TaskSchedulerImpl.scala:373)
at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:186)
at org.apache.spark.scheduler.TaskSchedulerImpl$$anonfun$resourceOffers$4.apply(TaskSchedulerImpl.scala:373)
at org.apache.spark.scheduler.TaskSchedulerImpl$$anonfun$resourceOffers$4.apply(TaskSchedulerImpl.scala:370)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.TaskSchedulerImpl.resourceOffers(TaskSchedulerImpl.scala:370)
at org.apache.spark.scheduler.local.LocalEndpoint.reviveOffers(LocalSchedulerBackend.scala:85)
at org.apache.spark.scheduler.local.LocalEndpoint$$anonfun$receive$1.applyOrElse(LocalSchedulerBackend.scala:64)
at org.apache.spark.rpc.netty.Inbox$$anonfun$process$1.apply$mcV$sp(Inbox.scala:117)
at org.apache.spark.rpc.netty.Inbox.safelyCall(Inbox.scala:205)
at org.apache.spark.rpc.netty.Inbox.process(Inbox.scala:101)
at org.apache.spark.rpc.netty.Dispatcher$MessageLoop.run(Dispatcher.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)
18/03/02 00:58:55 ERROR TaskSchedulerImpl: Resource offer failed, task set TaskSet_0.0 was not serializable
Exception in thread "main" org.apache.spark.SparkException: Job aborted due to stage failure: Failed to serialize task 3, not attempting to retry it. Exception during serialization: java.io.NotSerializableException: org.apache.kafka.clients.consumer.ConsumerRecord
Serialization stack:
- object not serializable (class: org.apache.kafka.clients.consumer.ConsumerRecord, value: ConsumerRecord(topic = , partition = 1, offset = 2, NoTimestampType = -1, checksum = -1, serialized key size = -1, serialized value size = -1, key = myTopic, value = {"id":1}))
- element of array (index: 0)
- array (class [Lorg.apache.kafka.clients.consumer.ConsumerRecord;, size 1)
- field (class: scala.collection.mutable.WrappedArray$ofRef, name: array, type: class [Ljava.lang.Object;)
- object (class scala.collection.mutable.WrappedArray$ofRef, WrappedArray(ConsumerRecord(topic = , partition = 1, offset = 2, NoTimestampType = -1, checksum = -1, serialized key size = -1, serialized value size = -1, key = myTopic, value = {"id":1})))
- writeObject data (class: org.apache.spark.rdd.ParallelCollectionPartition)
- object (class org.apache.spark.rdd.ParallelCollectionPartition, org.apache.spark.rdd.ParallelCollectionPartition@694)
- field (class: org.apache.spark.scheduler.ResultTask, name: partition, type: interface org.apache.spark.Partition)
- object (class org.apache.spark.scheduler.ResultTask, ResultTask(0, 3))
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1499)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1487)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1486)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1486)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:814)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:814)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:814)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1714)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1669)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1658)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:630)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2022)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2043)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2062)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2087)
at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:936)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:362)
at org.apache.spark.rdd.RDD.collect(RDD.scala:935)
at Exemple$.main(Exemple.scala:20)
at Exemple.main(Exemple.scala)
Process finished with exit code 1
你有什么主意吗?
推荐答案
org.apache.kafka.clients.consumer.ConsumerRecord无法序列化，因此有一些方法可以解决此类问题
org.apache.kafka.clients.consumer.ConsumerRecord is not serializable, So there are some way to solve this kind of problems
- 使用kryo序列化对类进行序列化
- 仅在map中传递的lambda函数中声明实例.
- 将NotSerializable对象设为静态对象，并在每台计算机上创建一次.
-
调用rdd.forEachPartition并在其中创建NotSerializable对象，如下所示:
- Serializable the class using kryo serialization
- Declare the instance only within the lambda function passed in map.
- Make the NotSerializable object as a static and create it once per machine.
Call rdd.forEachPartition and create the NotSerializable object in there like this:
rdd.forEachPartition(iter-> { NotSerializable notSerializable = new NotSerializable();
rdd.forEachPartition(iter -> { NotSerializable notSerializable = new NotSerializable();
//...现在处理迭代 });
// ...Now process iter });
有关更多详细信息，您可以检查此链接 https ://databricks.gitbooks.io/databricks-spark-knowledge-base/content/troubleshooting/javaionotserializableexception.html
For more details you can check this link https://databricks.gitbooks.io/databricks-spark-knowledge-base/content/troubleshooting/javaionotserializableexception.html
这篇关于我无法在RDD [ConsumerRecord]上进行转换的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！
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