Scala，Java，Python 3种语言编写Spark WordCount示例

首先，我先定义一个文件，hello.txt，里面的内容如下：

hello spark
hello hadoop
hello flink
hello storm

Scala方式

scala版本是2.11.8。

配置maven文件，三个依赖：

<dependency>
  <groupId>org.apache.hadoop</groupId>
  <artifactId>hadoop-client</artifactId>
  <version>2.6.0-cdh5.7.0</version>
</dependency>

<dependency>
  <groupId>org.scala-lang</groupId>
  <artifactId>scala-library</artifactId>
  <version>2.11.8</version>
</dependency>

<dependency>
  <groupId>org.apache.spark</groupId>
  <artifactId>spark-core_2.11</artifactId>
  <version>2.2.0</version>
</dependency>

package com.darrenchan.spark

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

object SparkCoreApp2 {
  def main(args: Array[String]): Unit = {
    val sparkConf = new SparkConf().setMaster("local[2]").setAppName("WordCountApp")
    val sc = new SparkContext(sparkConf)

    //业务逻辑
    val counts = sc.textFile("D:\\hello.txt").
      flatMap(_.split(" ")).
      map((_, 1)).
      reduceByKey(_+_)

    println(counts.collect().mkString("\n"))

    sc.stop()
  }
}

运行结果：

Java方式

Java8，用lamda表达式。

package com.darrenchan.spark.javaapi;

import org.apache.spark.SparkConf;
import org.apache.spark.SparkContext;
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.sql.SparkSession;
import scala.Tuple2;

import java.util.Arrays;

public class WordCountApp2 {
    public static void main(String[] args) {
        SparkConf sparkConf = new SparkConf().setMaster("local[2]").setAppName("WordCountApp");
        JavaSparkContext sc = new JavaSparkContext(sparkConf);

        //业务逻辑
        JavaPairRDD<String, Integer> counts =
                sc.textFile("D:\\hello.txt").
                        flatMap(line -> Arrays.asList(line.split(" ")).iterator()).
                        mapToPair(word -> new Tuple2<>(word, 1)).
                        reduceByKey((a, b) -> a + b);

        System.out.println(counts.collect());

        sc.stop();
    }
}

运行结果：

Python方式

Python 3.6.5。

from pyspark import SparkConf, SparkContext

def main():
    # 创建SparkConf，设置Spark相关的参数信息
    conf = SparkConf().setMaster("local[2]").setAppName("spark_app")
    # 创建SparkContext
    sc = SparkContext(conf=conf)

    # 业务逻辑开发
    counts = sc.textFile("D:\\hello.txt").\
        flatMap(lambda line: line.split(" ")).\
        map(lambda word: (word, 1)).\
        reduceByKey(lambda a, b: a + b)

    print(counts.collect())

    sc.stop()


if __name__ == '__main__':
    main()

运行结果：

使用Python在Windows下运行Spark有很多坑，详见如下链接：

http://note.youdao.com/noteshare?id=aad06f5810f9463a94a2d42144279ea4