如何在Java中的Apache Spark Streaming中为文件名模式定义文件过滤器？

Question

I'm using Apache Spark Streaming 1.2.0 and trying to define a file filter for file names when creating an InputDStream by invoking the fileStream method. My code is working perfectly fine when I don't use a file filter, eg by invoking the other fileStream method (described here ).

According to the documentation of fileStream method, I can pass it

scala.Function1<org.apache.hadoop.fs.Path,Object> filter

But so far, I could not create a fileFilter . My initial attempts have been

1- Tried to implement it as:

Function1<Path, Object> fileFilter = new Function1<Path, Object>() {
    @Override
    public Object apply(Path v1) {
      return true;
    }

    @Override
    public <A> Function1<A, Object> compose(Function1<A, Path> g) {
      return Function1$class.compose(this, g);
    }

    @Override
    public <A> Function1<Path, A> andThen(Function1<Object, A> g) {
      return Function1$class.andThen(this, g);
    }
  };

But apparently my implementation of andThen is wrong, and I couldn't understand how I should implement it. It complains that the anonymous function

is not abstract and does not override abstract method <A>andThen$mcVJ$sp(scala.Function1<scala.runtime.BoxedUnit,A>) in scala.Function1

2- Tried to implement it as:

Function1<Path, Object> fileFilter = new AbstractFunction1<Path, Object>() {
    @Override
    public Object apply(Path v1) {
      return true;
    }
  };

This one compiles but then when I run it I get an exception:

2015-02-02 13:42:50 ERROR OneForOneStrategy:66 - myModule$1
java.io.NotSerializableException: myModule$1
    at java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1184)
    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.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.streaming.DStreamGraph$$anonfun$writeObject$1.apply$mcV$sp(DStreamGraph.scala:169)
    at org.apache.spark.util.Utils$.tryOrIOException(Utils.scala:985)
    at org.apache.spark.streaming.DStreamGraph.writeObject(DStreamGraph.scala:164)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:483)
    at java.io.ObjectStreamClass.invokeWriteObject(ObjectStreamClass.java:988)
    at java.io.ObjectOutputStream.writeSerialData(ObjectOutputStream.java:1496)
    at java.io.ObjectOutputStream.writeOrdinaryObject(ObjectOutputStream.java:1432)
    at java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1178)
    at java.io.ObjectOutputStream.defaultWriteFields(ObjectOutputStream.java:1548)
    at java.io.ObjectOutputStream.writeSerialData(ObjectOutputStream.java:1509)
    at java.io.ObjectOutputStream.writeOrdinaryObject(ObjectOutputStream.java:1432)
    at java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1178)
    at java.io.ObjectOutputStream.writeObject(ObjectOutputStream.java:348)
    at org.apache.spark.streaming.CheckpointWriter.write(Checkpoint.scala:184)
    at org.apache.spark.streaming.scheduler.JobGenerator.doCheckpoint(JobGenerator.scala:263)
    at org.apache.spark.streaming.scheduler.JobGenerator.org$apache$spark$streaming$scheduler$JobGenerator$$processEvent(JobGenerator.scala:167)
    at org.apache.spark.streaming.scheduler.JobGenerator$$anonfun$start$1$$anon$1$$anonfun$receive$1.applyOrElse(JobGenerator.scala:76)
    at akka.actor.Actor$class.aroundReceive(Actor.scala:465)
    at org.apache.spark.streaming.scheduler.JobGenerator$$anonfun$start$1$$anon$1.aroundReceive(JobGenerator.scala:74)
    at akka.actor.ActorCell.receiveMessage(ActorCell.scala:516)
    at akka.actor.ActorCell.invoke(ActorCell.scala:487)
    at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:238)
    at akka.dispatch.Mailbox.run(Mailbox.scala:220)
    at akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:393)
    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)

Any ideas how I can implement a fileFilter so that I can pass it fileStream method, so that I can make Spark Streaming process only the file name patterns I want?

Answer 1

I had to create another file named FileFilter.java:

import org.apache.hadoop.fs.Path;
import scala.runtime.AbstractFunction1;
import java.io.Serializable;

public class FileFilter extends AbstractFunction1<Path, Object> implements Serializable {

  @Override
  public Object apply(Path v1) {
    if ( v1.toString().endsWith((".json")) ) {
      return Boolean.TRUE;
    } else {
      return Boolean.FALSE;
    }
  }
}

And then pass it to the fileStream method as in:

fileStream(inDirectory, new FileFilter(), false, ...)

And it worked without any problems.