java - How to implement custom job listener/tracker in Spark?

Question

I have a class like below, and when i run this through command line i want to see progress status. some thing like,

10% completed... 
30% completed... 
100% completed...Job done!

I am using spark 1.0 on yarn and using Java API.

public class MyJavaWordCount {
    public static void main(String[] args) throws Exception {
        if (args.length < 2) {
            System.err.println("Usage: MyJavaWordCount <master> <file>");
            System.exit(1);
        }
        System.out.println("args[0]: <master>="+args[0]);
        System.out.println("args[1]: <file>="+args[1]);

        JavaSparkContext ctx = new JavaSparkContext(
                args[0],
                "MyJavaWordCount",
                System.getenv("SPARK_HOME"),
                System.getenv("SPARK_EXAMPLES_JAR"));
        JavaRDD<String> lines = ctx.textFile(args[1], 1);

//      output                                            input   output         
        JavaRDD<String> words = lines.flatMap(new FlatMapFunction<String, String>() {
            //              output       input 
            public Iterable<String> call(String s) {
                return Arrays.asList(s.split(" "));
            }
        });

//          K       V                                                input   K       V 
        JavaPairRDD<String, Integer> ones = words.mapToPair(new PairFunction<String, String, Integer>() {
            //            K       V             input 
            public Tuple2<String, Integer> call(String s) {
                //                K       V 
                return new Tuple2<String, Integer>(s, 1);
            }
        });

        JavaPairRDD<String, Integer> counts = ones.reduceByKey(new Function2<Integer, Integer, Integer>() {
            public Integer call(Integer i1, Integer i2) {
                return i1 + i2;
            }
        });

        List<Tuple2<String, Integer>> output = counts.collect();
        for (Tuple2 tuple : output) {
            System.out.println(tuple._1 + ": " + tuple._2);
        }
        System.exit(0);
    }
}

Answer 1

If you are using scala-spark this code will help you to adding spark listener.

Create your SparkContext

val sc=new SparkContext(sparkConf) 

Now you can add your spark listener in spark context

sc.addSparkListener(new SparkListener() {
  override def onApplicationStart(applicationStart: SparkListenerApplicationStart) {
    println("Spark ApplicationStart: " + applicationStart.appName);
  }

  override def onApplicationEnd(applicationEnd: SparkListenerApplicationEnd) {
    println("Spark ApplicationEnd: " + applicationEnd.time);
  }

});

Here is the list of Interface for listening to events from the Spark schedule.