spark-2.2.0-bin-hadoop2.6和spark-1.6.1-bin-hadoop2.6发行包自带案例全面详解（java、python、r和scala）之Basic包下的JavaTC.java（图文详解）

 

 

 

 

不多说，直接上干货！

 

 

spark-1.6.1-bin-hadoop2.6里Basic包下的JavaTC.java

 

 

/*
 * 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,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

//package org.apache.spark.examples;
package zhouls.bigdata.Basic;

import java.util.ArrayList;
import java.util.HashSet;
import java.util.List;
import java.util.Random;
import java.util.Set;

import scala.Tuple2;

import org.apache.spark.SparkConf;
import org.apache.spark.api.java.JavaPairRDD;
import org.apache.spark.api.java.JavaSparkContext;
import org.apache.spark.api.java.function.PairFunction;

/**
 * Transitive closure on a graph, implemented in Java.
 * Usage: JavaTC [slices]
 */
public final class JavaTC {

  private static final int numEdges = 200;
  private static final int numVertices = 100;
  private static final Random rand = new Random(42);

  static List<Tuple2<Integer, Integer>> generateGraph() {
    Set<Tuple2<Integer, Integer>> edges = new HashSet<Tuple2<Integer, Integer>>(numEdges);
    while (edges.size() < numEdges) {
      int from = rand.nextInt(numVertices);
      int to = rand.nextInt(numVertices);
      Tuple2<Integer, Integer> e = new Tuple2<Integer, Integer>(from, to);
      if (from != to) {
        edges.add(e);
      }
    }
    return new ArrayList<Tuple2<Integer, Integer>>(edges);
  }

  static class ProjectFn implements PairFunction<Tuple2<Integer, Tuple2<Integer, Integer>>,
      Integer, Integer> {
    static final ProjectFn INSTANCE = new ProjectFn();

    @Override
    public Tuple2<Integer, Integer> call(Tuple2<Integer, Tuple2<Integer, Integer>> triple) {
      return new Tuple2<Integer, Integer>(triple._2()._2(), triple._2()._1());
    }
  }

  public static void main(String[] args) {
    SparkConf sparkConf = new SparkConf().setAppName("JavaHdfsLR").setMaster("local"); 
    JavaSparkContext sc = new JavaSparkContext(sparkConf);
    Integer slices = (args.length > 0) ? Integer.parseInt(args[0]): 2;
    JavaPairRDD<Integer, Integer> tc = sc.parallelizePairs(generateGraph(), slices).cache();

    // Linear transitive closure: each round grows paths by one edge,
    // by joining the graph's edges with the already-discovered paths.
    // e.g. join the path (y, z) from the TC with the edge (x, y) from
    // the graph to obtain the path (x, z).

    // Because join() joins on keys, the edges are stored in reversed order.
    JavaPairRDD<Integer, Integer> edges = tc.mapToPair(
      new PairFunction<Tuple2<Integer, Integer>, Integer, Integer>() {
        @Override
        public Tuple2<Integer, Integer> call(Tuple2<Integer, Integer> e) {
          return new Tuple2<Integer, Integer>(e._2(), e._1());
        }
    });

    long oldCount;
    long nextCount = tc.count();
    do {
      oldCount = nextCount;
      // Perform the join, obtaining an RDD of (y, (z, x)) pairs,
      // then project the result to obtain the new (x, z) paths.
      tc = tc.union(tc.join(edges).mapToPair(ProjectFn.INSTANCE)).distinct().cache();
      nextCount = tc.count();
    } while (nextCount != oldCount);

    System.out.println("TC has " + tc.count() + " edges.");
    sc.stop();
  }
}

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

spark-2.2.0-bin-hadoop2.6里Basic包下的JavaTC.java

 

 

 

/*
 * 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,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

//package org.apache.spark.examples;
package zhouls.bigdata.Basic;

import java.util.ArrayList;
import java.util.HashSet;
import java.util.List;
import java.util.Random;
import java.util.Set;

import scala.Tuple2;

import org.apache.spark.api.java.JavaPairRDD;
import org.apache.spark.api.java.JavaSparkContext;
import org.apache.spark.api.java.function.PairFunction;
import org.apache.spark.sql.SparkSession;

/**
 * Transitive closure on a graph, implemented in Java.
 * Usage: JavaTC [partitions]
 */
public final class JavaTC {

  private static final int numEdges = 200;
  private static final int numVertices = 100;
  private static final Random rand = new Random(42);

  static List<Tuple2<Integer, Integer>> generateGraph() {
    Set<Tuple2<Integer, Integer>> edges = new HashSet<>(numEdges);
    while (edges.size() < numEdges) {
      int from = rand.nextInt(numVertices);
      int to = rand.nextInt(numVertices);
      Tuple2<Integer, Integer> e = new Tuple2<>(from, to);
      if (from != to) {
        edges.add(e);
      }
    }
    return new ArrayList<>(edges);
  }

  static class ProjectFn implements PairFunction<Tuple2<Integer, Tuple2<Integer, Integer>>,
      Integer, Integer> {
    static final ProjectFn INSTANCE = new ProjectFn();

    @Override
    public Tuple2<Integer, Integer> call(Tuple2<Integer, Tuple2<Integer, Integer>> triple) {
      return new Tuple2<>(triple._2()._2(), triple._2()._1());
    }
  }

  public static void main(String[] args) {
    SparkSession spark = SparkSession
      .builder()
      .master("local")  
      .appName("JavaTC")
      .getOrCreate();

    JavaSparkContext jsc = new JavaSparkContext(spark.sparkContext());

    Integer slices = (args.length > 0) ? Integer.parseInt(args[0]): 2;
    JavaPairRDD<Integer, Integer> tc = jsc.parallelizePairs(generateGraph(), slices).cache();

    // Linear transitive closure: each round grows paths by one edge,
    // by joining the graph's edges with the already-discovered paths.
    // e.g. join the path (y, z) from the TC with the edge (x, y) from
    // the graph to obtain the path (x, z).

    // Because join() joins on keys, the edges are stored in reversed order.
    JavaPairRDD<Integer, Integer> edges = tc.mapToPair(e -> new Tuple2<>(e._2(), e._1()));

    long oldCount;
    long nextCount = tc.count();
    do {
      oldCount = nextCount;
      // Perform the join, obtaining an RDD of (y, (z, x)) pairs,
      // then project the result to obtain the new (x, z) paths.
      tc = tc.union(tc.join(edges).mapToPair(ProjectFn.INSTANCE)).distinct().cache();
      nextCount = tc.count();
    } while (nextCount != oldCount);

    System.out.println("TC has " + tc.count() + " edges.");
    spark.stop();
  }
}