flink的入门案例之wordcount

这是依赖

<dependency>

  <groupId>org.apache.flink</groupId>

  <artifactId>flink-java</artifactId>

  <version>1.5.0</version>

</dependency>

<dependency>

  <groupId>org.apache.flink</groupId>

  <artifactId>flink-streaming-java_2.11</artifactId>

  <version>1.5.0</version>

</dependency>

<dependency>

  <groupId>org.apache.flink</groupId>

  <artifactId>flink-clients_2.11</artifactId>

  <version>1.5.0</version>

</dependency>

 这个是1.5版本的依赖..

然后是我们的代码

public class FlinkWordCount {

         publicstatic void main(String[] args) throws Exception {

       final ExecutionEnvironment env =ExecutionEnvironment.getExecutionEnvironment();

       DataSet<String> text = env.fromElements(

           "hadoop hive?",

           "think hadoop hive sqoop hbase spark flink?");

        DataSet<Tuple2<String,Integer>> wordCounts = text

           .flatMap(new LineSplitter())

           .groupBy(0)

           .sum(1);

       wordCounts.print();

    }

   public static class LineSplitter implements FlatMapFunction<String,Tuple2<String, Integer>> {

       @Override

       public void flatMap(String line, Collector<Tuple2<String,Integer>> out) {

           for (String word : line.split("\\W+")) {

                out.collect(newTuple2<String, Integer>(word, 1));

           }

       }

}

 

 

执行结果,,可以在节点根据命令提交,

也可以在UI界面提交jar.的包,,在submit的需要指定程序的主类