第 2 节 batch批处理（java实现）

上篇：第 1 节 滑动窗口单词计数（Scala实现）

---

准备文件：
自己在d盘下D:\input\file文件下创建a.txt文本

其中a.txt文本下编辑的的内容为：

hadoop
flume
spark
hive
flink

具体代码实现：

package xuwei.tech;

import org.apache.flink.api.common.functions.FlatMapFunction;
import org.apache.flink.api.java.ExecutionEnvironment;
import org.apache.flink.api.java.operators.AggregateOperator;
import org.apache.flink.api.java.operators.DataSource;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.util.Collector;


/**
 * 用java实现批处理
 *
 */
public class BatchWordCountJava {
    public static void main(String[] args)throws Exception {
        //获取flink的运行环境
        ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
        //获取文件的内容
        String inputpath="D:\\input\\file";
        String outPut="D:\\input\\result";
        //获取文件的内容
       DataSource<String> text = env.readTextFile(inputpath);
       AggregateOperator<Tuple2<String, Integer>> counts = text.flatMap(new Tockenizer()).groupBy(0).sum(1);
       counts.writeAsCsv(outPut,"\n"," ");
       env.execute("batch word count");
    }
    public static class Tockenizer implements FlatMapFunction<String, Tuple2<String,Integer>>{

        @Override
        public void flatMap(String value, Collector<Tuple2<String, Integer>> out) throws Exception {
             String[] tokens = value.toLowerCase().split("\\W+");
             for (String token:tokens){
                 if(token.length()>0){
                  out.collect(new Tuple2<String, Integer>(token,1));
                 }
             }

        }
    }
}

运行程序，控制台打印信息：

生成文件数据

发现，数据还做了一个排序