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;
/**
* @Author yqq
* @Date 2021/12/06 23:16
* @Version 1.0
*/
/**
* SparkScala api 与Java api 不同:
* 1).java中需要创建 JavaSparkContext
* 2).scala中是RDD ,java中是JavaRDD
* 3).scala中将RDD转换成K,V格式的数据直接使用 map转出tuple数据即可
* Java中将RDD转换成K,V格式的数据需要使用mapToPair,转出K,V格式的数据
*
* 4).JavaPairRDD 在java中代表的是K,V格式的RDD
*
*/
public class WordCountByJava {
public static void main(String[] args) {
SparkConf conf = new SparkConf();
conf.setMaster("local");
conf.setAppName("word_count_java");
JavaSparkContext context = new JavaSparkContext(conf);
JavaRDD<String> lines = context.textFile("data/words");
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> pairRDD = words.mapToPair(new PairFunction<String, String, Integer>() {
@Override
public Tuple2<String, Integer> call(String s) throws Exception {
return new Tuple2<>(s, 1);
}
});
JavaPairRDD<String, Integer> result = pairRDD.reduceByKey(new Function2<Integer, Integer, Integer>() {
@Override
public Integer call(Integer integer, Integer integer2) throws Exception {
return integer + integer2;
}
});
result.foreach(new VoidFunction<Tuple2<String, Integer>>() {
@Override
public void call(Tuple2<String, Integer> tuple2) throws Exception {
System.out.println(tuple2);
}
});
}
}
。。。。。很明显Java写的很复杂。。。。。。还是Scala真香