使用Spark函数实现的java序列化问题
我在理解Java中的Spark函数实现时遇到困难The documentation给出了使用map
和reduce
中函数的三种方法:
- 兰姆达大道
- 通过内联类实现
Function
和Function2
- 通过内部类实现
Function
和Function2
问题是我无法使2.
和3.
工作。
例如,此代码:
public int countInline(String path) {
String master = "local";
SparkConf conf = new SparkConf().setAppName("charCounterInLine")
.setMaster(master);
JavaSparkContext sc = new JavaSparkContext(conf);
JavaRDD<String> lines = sc.textFile(path);
JavaRDD<Integer> lineLengths = lines
.map(new Function<String, Integer>() {
public Integer call(String s) {
return s.length();
}
});
return lineLengths.reduce(new Function2<Integer, Integer, Integer>() {
public Integer call(Integer a, Integer b) {
return a + b;
}
}); // the line causing the error
}
给我这个错误:
14/07/09 11:23:20 INFO DAGScheduler: Failed to run reduce at CharCounter.java:42
[WARNING]
java.lang.reflect.InvocationTargetException
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:483)
at org.codehaus.mojo.exec.ExecJavaMojo$1.run(ExecJavaMojo.java:297)
at java.lang.Thread.run(Thread.java:745)
Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Task not serializable: java.io.NotSerializableException: Hadoop.Spark.basique.CharCounter
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1033)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1017)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1015)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1015)
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$submitMissingTasks(DAGScheduler.scala:770)
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$submitStage(DAGScheduler.scala:713)
at org.apache.spark.scheduler.DAGScheduler.handleJobSubmitted(DAGScheduler.scala:697)
at org.apache.spark.scheduler.DAGSchedulerEventProcessActor$$anonfun$receive$2.applyOrElse(DAGScheduler.scala:1176)
at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498)
at akka.actor.ActorCell.invoke(ActorCell.scala:456)
at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237)
at akka.dispatch.Mailbox.run(Mailbox.scala:219)
at akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:386)
at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
at scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
at scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
现在,我可以通过在公共外部类中实现Function
和Function2
来避免这个问题。然而,这与其说是一个深思熟虑的决定,不如说是一个幸运的猜测。此外,由于我无法使文档示例正常工作,我想有些事情我不明白
最后,我的问题是:
- 如何使
2.
和3.
工作李> - 为什么只有
lambda
在工作李> - 还有其他方法使用
functions
吗李>
# 1 楼答案
为封闭类添加“implements Serializable”可以解决这个问题。它正在序列化封闭类,因为内部类是该类的成员,但封闭类似乎不可序列化
# 2 楼答案
此stracktrace的相关部分是:
当您将函数定义为内部类时,它们的封闭对象将被拉入函数闭包并序列化。如果这个类是不可序列化的,或者包含一个不可序列化的字段,那么您将遇到这个错误
这里有几个选项:
transient
李>