Spark平台上的JavaWordCount示例

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WorldCount目录结构如下：

[root@master WordCount]# find .../src./src/main./src/main/java./src/main/java/JavaWordCount.java./pom.xml

其中./pom.xml内容如下：
（注意对应以后生成的jar包，本例中最后生成word-count-1.0.jar）

<project>  <groupId>edu.berkeley</groupId>  <artifactId>word-count</artifactId>  <modelVersion>4.0.0</modelVersion>  <name>JavaWordCount</name>  <packaging>jar</packaging>  <version>1.0</version>  <dependencies>    <dependency> <!-- Spark dependency -->      <groupId>org.apache.spark</groupId>      <artifactId>spark-core_2.10</artifactId>      <version>1.2.0</version>    </dependency>    <dependency> <!-- Hadoop dependency -->      <groupId>org.apache.hadoop</groupId>      <artifactId>hadoop-client</artifactId>      <version>2.6.0</version>    </dependency>  </dependencies></project>

./src/main/java/JavaWordCount.java内容如下：

import scala.Tuple2;import org.apache.spark.SparkConf;import org.apache.spark.api.java.JavaPairRDD;import org.apache.spark.api.java.JavaRDD;import org.apache.spark.api.java.JavaSparkContext;import org.apache.spark.api.java.function.FlatMapFunction;import org.apache.spark.api.java.function.Function2;import org.apache.spark.api.java.function.PairFunction;import java.util.Arrays;import java.util.List;import java.util.regex.Pattern;public final class JavaWordCount {  private static final Pattern SPACE = Pattern.compile(" ");  public static void main(String[] args) throws Exception {    if (args.length < 1) {      System.err.println("Usage: JavaWordCount <file>");      System.exit(1);    }    SparkConf sparkConf = new SparkConf().setAppName("JavaWordCount");    JavaSparkContext ctx = new JavaSparkContext(sparkConf);    JavaRDD<String> lines = ctx.textFile(args[0], 1);    JavaRDD<String> words = lines.flatMap(new FlatMapFunction<String, String>() {      @Override      public Iterable<String> call(String s) {        return Arrays.asList(SPACE.split(s));      }    });    JavaPairRDD<String, Integer> ones = words.mapToPair(new PairFunction<String, String, Integer>() {      @Override      public Tuple2<String, Integer> call(String s) {        return new Tuple2<String, Integer>(s, 1);      }    });    JavaPairRDD<String, Integer> counts = ones.reduceByKey(new Function2<Integer, Integer, Integer>() {      @Override      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());    }    ctx.stop();  }}

进入WorldCount目录，并编译程序并打包：

[root@master WordCount]# mvn package

然后往集群上发布：

[root@master WordCount]#spark-submit \  --class JavaWordCount \  --master yarn-cluster \  --num-executors 2 \  --executor-memory 6g \  --executor-cores 4  \  target/word-count-1.0.jar \  /user/root/random0.data

若–master 后用的是yarn-cluster，则在log日志中（从WebUI进入）查看结果

package: 1For: 2processing.: 1Programs: 1Because: 1The: 1cluster.: 1its: 1……

若–master 后用的是yarn-client，则在控制台查看结果

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