flink初级编程实践

Flink 是一个分布式流处理和批处理框架，可以用于大规模数据的实时处理和分析。下面是一个简单的 Flink 编程实践示例，用于计算输入流中每个单词的出现次数：

import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.functions.source.SourceFunction;

public class WordCount {

    public static void main(String[] args) throws Exception {
        // 创建执行环境
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

        // 定义输入流
        DataStream<String> input = env.addSource(new SimpleSource());

        // 数据转换和处理
        DataStream<Tuple2<String, Integer>> counts = input
                .flatMap((String value, Collector<Tuple2<String, Integer>> out) -> {
                    // 按空格拆分每行，并输出每个单词的次数
                    for (String word : value.split(" ")) {
                        out.collect(new Tuple2<>(word, 1));
                    }
                })
                .keyBy(0)  // 按单词分组
                .sum(1);   // 求和

        // 输出结果
        counts.print();

        // 执行程序
        env.execute();
    }

    // 自定义数据源，用于提供输入数据
    public static class SimpleSource implements SourceFunction<String> {
        private volatile boolean isRunning = true;

        @Override
        public void run(SourceContext<String> ctx) throws Exception {
            while (isRunning) {
                ctx.collect("hello world");
                Thread.sleep(1000);
            }
        }

        @Override
        public void cancel() {
            isRunning = f