Flink之函数使用

最新推荐文章于 2025-07-10 14:27:53 发布

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#flink #大数据

1. WindowFunction

在滚动窗口中使用 WindowFunction 函数来实现对数据的统计。

样例数据：

9,3
9,2
9,7
4,9
2,6

import org.apache.flink.api.common.functions.MapFunction;
import org.apache.flink.api.common.functions.ReduceFunction;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.functions.windowing.WindowFunction;
import org.apache.flink.streaming.api.windowing.assigners.ProcessingTimeSessionWindows;
import org.apache.flink.streaming.api.windowing.assigners.TumblingProcessingTimeWindows;
import org.apache.flink.streaming.api.windowing.time.Time;
import org.apache.flink.streaming.api.windowing.windows.TimeWindow;
import org.apache.flink.util.Collector;

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

        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        DataStreamSource<String> source = env.socketTextStream("192.168.88.161", 9999);
        source.setParallelism(1);
        SingleOutputStreamOperator<Tuple2<Integer, Integer>> mapData = source.map(new MapFunction<String, Tuple2<Integer, Integer>>() {
            @Override
            public Tuple2<Integer, Integer> map(String value) throws Exception {
                String[] arr = value.split(",");
                return Tuple2.of(Integer.valueOf(arr[0]), Integer.valueOf(arr[1]));
            }
        });
        mapData.keyBy(line->line.f0)
//                todo 滚动窗口 每三秒一计算
                .window(TumblingProcessingTimeWindows.of(Time.seconds(3)))
                .apply(new WindowFunction<Tuple2<Integer, Integer>, Tuple2<Integer, Integer>, Integer, TimeWindow>() {
                    @Override
                    public void apply(Integer integer, TimeWindow window, Iterable<Tuple2<Integer, Integer>> input, Collector<Tuple2<Integer, Integer>> out) throws Exception {
                        Integer key = 0;
                        Integer count = 0;
                        for (Tuple2<Integer, Integer> line : input){
//                          key 获取的是 参数
                            key = line.f0;
//                          count 获取的是对指定参数进行累加操作
                            count += line.f1;
                        }
                        out.collect(Tuple2.of(key,count));
                    }
                })
                .print();
        env.execute();
    }
}

给程序开一个单独的端口：nc -lk 9999

当程序运行后，在开的端口处发送数据并在控制台打印输出结果：

2. ReduceFunction

在滑动窗口之使用 ReduceFunction 实现对数据的统计并输出。

样例数据：

9,3
9,2
9,7
4,9
2,6
1,5
2,3
5,7
5,4

import org.apache.flink.api.common.functions.MapFunction;
import org.apache.flink.api.common.functions.ReduceFunction;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.functions.windowing.WindowFunction;
import org.apache.flink.streaming.api.windowing.assigners.ProcessingTimeSessionWindows;
import org.apache.flink.streaming.api.windowing.assigners.SlidingProcessingTimeWindows;
import org.apache.flink.streaming.api.windowing.assigners.TumblingProcessingTimeWindows;
import org.apache.flink.streaming.api.windowing.time.Time;
import org.apache.flink.streaming.api.windowing.windows.TimeWindow;
import org.apache.flink.util.Collector;

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

        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        DataStreamSource<String> source = env.socketTextStream("192.168.88.161", 9999);
        source.setParallelism(1);
        SingleOutputStreamOperator<Tuple2<Integer, Integer>> mapData = source.map(new MapFunction<String, Tuple2<Integer, Integer>>() {
            @Override
            public Tuple2<Integer, Integer> map(String value) throws Exception {
                String[] arr = value.split(",");
                return Tuple2.of(Integer.valueOf(arr[0]), Integer.valueOf(arr[1]));
            }
        });
        mapData.keyBy(line->line.f0)

//  todo 滑动窗口 每三秒计算一次前六秒的数据量
                .window(SlidingProcessingTimeWindows.of(Time.seconds(6),Time.seconds(3)))
                .reduce(new ReduceFunction<Tuple2<Integer, Integer>>() {
                    @Override
                    public Tuple2<Integer, Integer> reduce(Tuple2<Integer, Integer> value1, Tuple2<Integer, Integer> value2) throws Exception {
                        return Tuple2.of(value1.f0,value1.f1 + value2.f1);
                    }
                })

                .print();
        env.execute();
    }
}

给程序开一个单独的端口：nc -lk 9999

当程序运行后，在开的端口处发送数据并在控制台打印输出结果：