package examples;
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 org.apache.spark.api.java.function.VoidFunction;
import scala.Tuple2;
import java.util.Arrays;
import java.util.Iterator;
/**
* @Description
* @Copyright credlink
* @Author luzhen
* @Create 2019/6/6 9:08
*/
public class wordCount3 {
public static void main(String args[]) {
countTest();
}
public static void countTest() {
SparkConf conf = new SparkConf().setAppName("wordCount").setMaster("local[1]");
JavaSparkContext jsc = new JavaSparkContext(conf);
JavaRDD<String> lines = jsc.textFile("D:\\LICENSE");
JavaRDD<String> words = lines.flatMap(
new FlatMapFunction<String, String>() {
@Override
public Iterator<String> call(String s) throws Exception {
return Arrays.asList(s.split(" ")).iterator();
}
}
);
JavaPairRDD<String, Integer> counts = words.mapToPair(
new PairFunction<String, String, Integer>() {
@Override
public Tuple2<String, Integer> call(String s) throws Exception {
return new Tuple2<String, Integer>(s, 1);
}
}
);
JavaPairRDD<String, Integer> results = counts.reduceByKey(
new Function2<Integer, Integer, Integer>() {
@Override
public Integer call(Integer xx1, Integer xx2) throws Exception {
return xx1 + xx2;
}
}
);
results.foreach(new VoidFunction<Tuple2<String, Integer>>() {
@Override
public void call(Tuple2<String, Integer> stringIntegerTuple2) throws Exception {
System.out.println(stringIntegerTuple2);
}
});
}
}
输出结果:
(additional,4)
(Unless,3)
(For,3)
(NON-INFRINGEMENT,,1)
(agree,1)
(reproduce,,1)
(offer,1)
(executed,1)
(event,1)
((or,3)
("Contributor",1)
(Grant,2)
(work.,1)
(include,3)
(content,1)
(nothing,1)
(MERCHANTABILITY,,1)
(add,2)
(through,1)
(However,,1)
(perform,,1)
(files;,1)
(result,1)
(been,2)
(goodwill,,1)
(herein,1)
(appropriateness,1)
(direct,,1)
(To,1)
(any,28)
(contract,,1)
(ANY,2)
本文介绍使用Apache Spark实现WordCount的全过程,从配置Spark环境到读取文本文件,再到使用flatMap、mapToPair和reduceByKey等函数进行单词计数,并展示最终的运行结果。

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