using Spark's status APIs - Java Big Data

Java examples for Big Data:apache spark

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Description

using Spark's status APIs

Demo Code

/*// w  ww  .ja  va  2 s  . c om
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You under the Apache License, Version 2.0
 * (the "License"); you may not use this file except in compliance with
 * the License.  You may obtain a copy of the License at
 *
 *    http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
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package org.apache.spark.examples;

import org.apache.spark.SparkConf;
import org.apache.spark.SparkJobInfo;
import org.apache.spark.SparkStageInfo;
import org.apache.spark.api.java.JavaFutureAction;
import org.apache.spark.api.java.JavaRDD;
import org.apache.spark.api.java.JavaSparkContext;
import org.apache.spark.api.java.function.Function;

import java.util.Arrays;
import java.util.List;

/**
 * Example of using Spark's status APIs from Java.
 */
public final class JavaStatusTrackerDemo {

    public static final String APP_NAME = "JavaStatusAPIDemo";

    public static final class IdentityWithDelay<T> implements
            Function<T, T> {
        @Override
        public T call(T x) throws Exception {
            Thread.sleep(2 * 1000); // 2 seconds
            return x;
        }
    }

    public static void main(String[] args) throws Exception {
        SparkConf sparkConf = new SparkConf().setAppName(APP_NAME);
        final JavaSparkContext sc = new JavaSparkContext(sparkConf);

        // Example of implementing a progress reporter for a simple job.
        JavaRDD<Integer> rdd = sc.parallelize(Arrays.asList(1, 2, 3, 4, 5),
                5).map(new IdentityWithDelay<Integer>());
        JavaFutureAction<List<Integer>> jobFuture = rdd.collectAsync();
        while (!jobFuture.isDone()) {
            Thread.sleep(1000); // 1 second
            List<Integer> jobIds = jobFuture.jobIds();
            if (jobIds.isEmpty()) {
                continue;
            }
            int currentJobId = jobIds.get(jobIds.size() - 1);
            SparkJobInfo jobInfo = sc.statusTracker().getJobInfo(
                    currentJobId);
            SparkStageInfo stageInfo = sc.statusTracker().getStageInfo(
                    jobInfo.stageIds()[0]);
            System.out.println(stageInfo.numTasks() + " tasks total: "
                    + stageInfo.numActiveTasks() + " active, "
                    + stageInfo.numCompletedTasks() + " complete");
        }

        System.out.println("Job results are: " + jobFuture.get());
        sc.stop();
    }
}

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