Flink-09 Flink Java 3分钟上手会话窗口 SessionWindow TimeWindow CountWindow GlobalWindow 原创

代码仓库

会同步代码到 GitHub
https://github.com/turbo-duck/flink-demo

在这里插入图片描述

上节进度

上节完成了 SlideWindow 时间窗口中的 时间驱动 和 事件驱动

核心代码

/ 时间驱动
 WindowedStream<Tuple2<String, Integer>, Tuple, TimeWindow> timeWindow = keyedStream.timeWindow(Time.seconds(10), Time.seconds(5));
         timeWindow.sum(1).print();
         timeWindow.apply(new MyTimeWindowFunction()).print();
// 事件驱动
WindowedStream<Tuple2<String, Integer>, String, GlobalWindow> countWindow = keyedStream
                .countWindow(3, 2);
        countWindow.sum(1).print();
        countWindow.apply(new MyCountWindowFunction()).print();
        env.execute();

会话窗口

请添加图片描述
Flink 会话窗口（Session Window）是一种基于会话活动来划分窗口的机制。与固定时间窗口（Tumbling Window）和滑动窗口（Sliding Window）不同，会话窗口不依赖固定的时间间隔，而是根据数据的活跃度来动态地划分窗口。具体来说，当数据流中存在一定时间的间隔（即没有数据到达），会话窗口会根据这个间隔结束一个窗口，并在新的数据到来时开始一个新的窗口。

会话窗口场景

用户行为分析：如电商网站用户会话，分析用户的购物行为。
IoT 数据处理：物联网设备的活动周期，如传感器的间歇性数据上传。
网络流量分析：根据流量数据的间隔时间来分析网络活动会话。

时间驱动

package icu.wzk.demo07;


import org.apache.flink.api.common.functions.MapFunction;
import org.apache.flink.api.java.functions.KeySelector;
import org.apache.flink.api.java.tuple.Tuple2;
import icu.wzk.demo06.MyTimeWindowFunction;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.datastream.KeyedStream;
import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator;
import org.apache.flink.streaming.api.datastream.WindowedStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.windowing.assigners.ProcessingTimeSessionWindows;
import org.apache.flink.streaming.api.windowing.time.Time;
import org.apache.flink.streaming.api.windowing.windows.TimeWindow;

import java.text.SimpleDateFormat;
import java.util.Random;


/**
 * 会话窗口
 * @author wzk
 * @date 14:10 2024/6/24
**/
public class SessionWindow {

    private static final Random RANDOM = new Random();

    public static void main(String[] args) throws Exception {
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        env.setParallelism(1);
        DataStreamSource<String> dataStreamSource = env.socketTextStream("0.0.0.0", 9999);
        SingleOutputStreamOperator<Tuple2<String, Integer>> mapStream = dataStreamSource.map(new MapFunction<String, Tuple2<String, Integer>>() {
            @Override
            public Tuple2<String, Integer> map(String value) throws Exception {
                SimpleDateFormat format = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss.SSS");
                long timeMillis = System.currentTimeMillis();
                int random = RANDOM.nextInt(10);
                System.err.println("value : " + value + " random : " + random + " timestamp : " + timeMillis + "|" + format.format(timeMillis));
                return new Tuple2<>(value, random);
            }
        });
        KeyedStream<Tuple2<String, Integer>, String> keyedStream = mapStream
                .keyBy(new KeySelector<Tuple2<String, Integer>, String>() {
                    @Override
                    public String getKey(Tuple2<String, Integer> value) throws Exception {
                        return value.f0;
                    }
                });

        // 如果连续10s内，没有数据进来，则会话窗口断开。
        WindowedStream<Tuple2<String, Integer>, String, TimeWindow> window = keyedStream
                .window(ProcessingTimeSessionWindows.withGap(Time.seconds(10)));
        window.sum(1).print();
        window.apply(new MyTimeWindowFunction()).print();
        env.execute();
    }
}

事件驱动

package icu.wzk.demo07;


import org.apache.flink.api.common.functions.MapFunction;
import org.apache.flink.api.java.functions.KeySelector;
import org.apache.flink.api.java.tuple.Tuple2;
import icu.wzk.demo06.MyTimeWindowFunction;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.datastream.KeyedStream;
import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator;
import org.apache.flink.streaming.api.datastream.WindowedStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.windowing.assigners.ProcessingTimeSessionWindows;
import org.apache.flink.streaming.api.windowing.time.Time;
import org.apache.flink.streaming.api.windowing.windows.TimeWindow;

import java.text.SimpleDateFormat;
import java.util.Random;


/**
 * 会话窗口
 * @author wzk
 * @date 14:10 2024/6/24
**/
public class SessionWindow {

    private static final Random RANDOM = new Random();

    public static void main(String[] args) throws Exception {
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        env.setParallelism(1);
        DataStreamSource<String> dataStreamSource = env.socketTextStream("0.0.0.0", 9999);
        SingleOutputStreamOperator<Tuple2<String, Integer>> mapStream = dataStreamSource.map(new MapFunction<String, Tuple2<String, Integer>>() {
            @Override
            public Tuple2<String, Integer> map(String value) throws Exception {
                SimpleDateFormat format = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss.SSS");
                long timeMillis = System.currentTimeMillis();
                int random = RANDOM.nextInt(10);
                System.err.println("value : " + value + " random : " + random + " timestamp : " + timeMillis + "|" + format.format(timeMillis));
                return new Tuple2<>(value, random);
            }
        });
        KeyedStream<Tuple2<String, Integer>, String> keyedStream = mapStream
                .keyBy(new KeySelector<Tuple2<String, Integer>, String>() {
                    @Override
                    public String getKey(Tuple2<String, Integer> value) throws Exception {
                        return value.f0;
                    }
                });

        // 如果连续10s内，没有数据进来，则会话窗口断开。
        WindowedStream<Tuple2<String, Integer>, String, TimeWindow> window = keyedStream
                .window(ProcessingTimeSessionWindows.withGap(Time.seconds(10)));
        window.sum(1).print();
        window.apply(new MyCountWindowFunction()).print();
        env.execute();
    }
}

MyTimeWindowFunction

package icu.wzk.demo06;

import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.streaming.api.functions.windowing.WindowFunction;
import org.apache.flink.streaming.api.windowing.windows.TimeWindow;
import org.apache.flink.util.Collector;

import java.text.SimpleDateFormat;


/**
 * 基于时间驱动 TimeWindow
 * @author wzk
 * @date 10:26 2024/6/22
**/
public class MyTimeWindowFunction implements WindowFunction<Tuple2<String,Integer>, String, String, TimeWindow> {

    @Override
    public void apply(String s, TimeWindow window, Iterable<Tuple2<String, Integer>> input, Collector<String> out) throws Exception {
        SimpleDateFormat format = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss.SSS");

        int sum = 0;

        for(Tuple2<String,Integer> tuple2 : input){
            sum +=tuple2.f1;
        }

        long start = window.getStart();
        long end = window.getEnd();

        out.collect("key:" + s + " value: " + sum + "| window_start :"
                + format.format(start) + "  window_end :" + format.format(end)
        );
    }
}

MyCountWindow

package icu.wzk.demo06;


import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.streaming.api.functions.windowing.WindowFunction;
import org.apache.flink.streaming.api.windowing.windows.GlobalWindow;
import org.apache.flink.util.Collector;

import java.text.SimpleDateFormat;


/**
 * 基于事件驱动 GlobalWindow
 * @author wzk
 * @date 10:27 2024/6/22
**/
public class MyCountWindowFunction implements WindowFunction<Tuple2<String, Integer>, String, String, GlobalWindow> {

    @Override
    public void apply(String s, GlobalWindow window, Iterable<Tuple2<String, Integer>> input, Collector<String> out) throws Exception {
        SimpleDateFormat format = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss.SSS");
        int sum = 0;
        for (Tuple2<String, Integer> tuple2 : input){
            sum += tuple2.f1;
        }
        // 无用的时间戳，默认值为： Long.MAX_VALUE,因为基于事件计数的情况下，不关心时间。
        long maxTimestamp = window.maxTimestamp();
        out.collect("key:" + s + " value: " + sum + "| maxTimeStamp :"
                + maxTimestamp + "," + format.format(maxTimestamp)
        );
    }
}