流处理，这里用netcat来完成

package com.smalltiger.flinkWCimport org.apache.flink.api.java.utils.ParameterTool
import org.apache.flink.streaming.api.scala._/*** Created by smalltiger on 2019/11/6.* flink基于流处理的一个WordCount统计*/
object StreamWC {def main(args: Array[String]): Unit = {//从外部命令中获取参数var params: ParameterTool = ParameterTool.fromArgs(args)var host: String = params.get("host")var port: Int = params.getInt("port")//1.获取当前执行环境var env: StreamExecutionEnvironment = StreamExecutionEnvironment.getExecutionEnvironment//接受socket文本流val textDstrem:DataStream[String] = env.socketTextStream(host,port)//flatMap和Map需要引入引入隐式转换import org.apache.flink.api.scala._val dataStream:DataStream[(String,Int)] = textDstrem.flatMap(_.split(" ")).filter(_.nonEmpty).map((_,1)).keyBy(0).sum(1)dataStream.print().setParallelism(1)//启动executor，执行任务env.execute("启动任务")}
}

批处理，直接处理文件内容

package com.smalltiger.flinkWC
import org.apache.flink.api.scala._/*** Created by smalltiger on 2019/11/6.* flink基于批处理统计wordcount*/
object WordCount {def main(args: Array[String]): Unit = {//创建执行环境val env = ExecutionEnvironment.getExecutionEnvironment//从文件中读取数据val inpath = "D:\\WorkSpace\\flinkWC\\src\\main\\resources\\abc.txt";var inputDS: DataSet[String] = env.readTextFile(inpath)//按照空格进行一个分词，对单词进行groupby分组，然后用sum进行一个聚合var wordCounts: AggregateDataSet[(String, Int)] = inputDS.flatMap(_.split(" ")).map((_, 1)).groupBy(0).sum(1)wordCounts.print()}
}