public static void main(String[] args) throws Exception {
       // 1、创建执行环境
       ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
       // 2、读取文件数据
       String inputPath = "/Users/gaolei/Documents/DemoProjects/flink-start/src/main/resources/hello.txt";
       DataSource<String> dataSource = env.readTextFile(inputPath);
       // 对数据集进行处理 按照空格分词展开 转换成（word，1）二元组
       AggregateOperator<Tuple2<String, Integer>> result = dataSource.flatMap(new MyFlatMapper())
               // 按照第一个位置 -> word 分组
               .groupBy(0)
               .sum(1);
       result.print();
   }

   public static class MyFlatMapper implements FlatMapFunction<String, Tuple2<String, Integer>> {
       public void flatMap(String s, Collector<Tuple2<String, Integer>> collector) {
           // 首先按照空格分词
           String[] words = s.split(" ");
           // 遍历所有的word 包装成二元组输出
           for (String word : words) {
               collector.collect(new Tuple2<String, Integer>(word, 1));
           }
       }
   }

public class StreamWordCount {
    public static void main(String[] args) throws Exception {

        // 创建流处理执行环境
        StreamExecutionEnvironment env = StreamContextEnvironment.getExecutionEnvironment();

        // 设置并行度，默认值 = 当前计算机的CPU逻辑核数（设置成1即单线程处理）
        // env.setMaxParallelism(32);

        // 从文件中读取数据
//        String inputPath = "/tmp/Flink_Tutorial/src/main/resources/hello.txt";
//        DataStream<String> inputDataStream = env.readTextFile(inputPath);

        // 从socket文本流读取数据
        DataStream<String> inputDataStream = env.socketTextStream("localhost", 7777);

        // 基于数据流进行转换计算
        DataStream<Tuple2<String,Integer>> resultStream = inputDataStream.flatMap(new WordCount.MyFlatMapper())
                .keyBy(0)
                .sum(1);

        resultStream.print();

        // 执行任务
        env.execute();
    }
}