How to run concurrent jobs(actions) in Apache Spark using single spark context

Question

It says in Apache Spark documentation "within each Spark application, multiple “jobs” (Spark actions) may be running concurrently if they were submitted by different threads". Can someone explain how to achieve this concurrency for the following sample code?

    SparkConf conf = new SparkConf().setAppName("Simple_App");
    JavaSparkContext sc = new JavaSparkContext(conf);

    JavaRDD<String> file1 = sc.textFile("/path/to/test_doc1");
    JavaRDD<String> file2 = sc.textFile("/path/to/test_doc2");

    System.out.println(file1.count());
    System.out.println(file2.count());

These two jobs are independent and must run concurrently.
Thank You.

Answer 1

Try something like this:

    final JavaSparkContext sc = new JavaSparkContext("local[2]","Simple_App");
    ExecutorService executorService = Executors.newFixedThreadPool(2);
    // Start thread 1
    Future<Long> future1 = executorService.submit(new Callable<Long>() {
        @Override
        public Long call() throws Exception {
            JavaRDD<String> file1 = sc.textFile("/path/to/test_doc1");
            return file1.count();
        }
    });
    // Start thread 2
    Future<Long> future2 = executorService.submit(new Callable<Long>() {
        @Override
        public Long call() throws Exception {
            JavaRDD<String> file2 = sc.textFile("/path/to/test_doc2");
            return file2.count();
        }
    });
    // Wait thread 1
    System.out.println("File1:"+future1.get());
    // Wait thread 2
    System.out.println("File2:"+future2.get());