java和scala分别实现WordCount

 WordCount作为大数据领域的经典范例，如同HelloWorld在程序设计中的地位一样，是一个入门程序。在此使用并行化处理介绍WordCount程序过程。

1. 实例描述

输入（txt）：
Hello World Bye World
Hello Hadoop Bye Hadoop
Bye Hadoop Hello Hadoop

输出：
<Hello, 3>
<World, 2>
<Bye, 3>
<Hadoop, 4>

2. 设计思路
在map阶段会将数据映射为：
<Hello, 1>
<World, 1>
<Bye, 1>
<World, 1>
<Hello, 1>
<Hadoop, 1>
<Bye, 1>
<Hadoop, 1>
<Bye, 1>
<Hadoop, 1>
<Hello, 1>
<Hadoop, 1>

在reduce阶段会将相同key的数据合并，并将合并结果相加：
<Hello, 1, 1, 1>
<World, 1, 1>
<Bye, 1, 1, 1>
<Hadoop, 1, 1, 1, 1>

3. 代码示例

WordCount用java实现代码示例如下：

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 scala.Tuple2;

import java.util.Arrays;
import java.util.regex.Pattern;

/**
* Created by yhao on 2015/3/16.
*/
public class WordCount {
private static final Pattern SPACE = Pattern.compile(" ");

public static void main(String[] args) {
String srcPath = null;
String desPath = null;
SparkConf sparkConf = new SparkConf().setAppName("wordcount");

if (args.length != 2) {
System.out.println("Parameter error!");
System.exit(-1);
}else {
srcPath = args[0];
desPath = args[1];
}

JavaSparkContext jsc = new JavaSparkContext();
final JavaRDD<String> lines = jsc.textFile(srcPath);
JavaRDD<String> words = lines.flatMap(new FlatMapFunction<String, String>() {
@Override
public Iterable<String> call(String s) throws Exception {
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) throws Exception {
return new Tuple2<String, Integer>(s, 1);
}
});

JavaPairRDD<String, Integer> counts = ones.reduceByKey(new Function2<Integer, Integer, Integer>() {
@Override
public Integer call(Integer integer, Integer integer2) throws Exception {
return integer + integer2;
}
});

counts.saveAsTextFile(desPath);
jsc.stop();
}
}

WordCount用scala实现代码如下：

import org.apache.spark.{SparkContext, SparkConf}
import org.apache.spark.SparkContext._

/**
* Created by yhao on 2015/3/17.
*/
class WordCount {

}

object WordCount {
def main(args: Array[String]) {
if(args.length != 2) {
System.out.println("Usage: <src> <des>")
System.exit(2)
}

val sparkConf = new SparkConf().setAppName("WordCount")
val sparkContext = new SparkContext(sparkConf)
val lines = sparkContext.textFile(args(0))
val words = lines.flatMap(_.split(" ")).map(a => (a, 1))
val counts = words.reduceByKey((a, b) => a+b)

counts.saveAsTextFile(args(1))
sparkContext.stop()
}
}

4. 应用场景
WordCount模型可应用于很多场景中，如统计博客各日志浏览量，文本搜索词频等等。