CC00031.flink——|Hadoop&Flink.V15|——|Flink.v15|Flink Windows窗口机制|

一、Flink window窗口机制：滑动时间窗口(Sliding Window)

### --- Flink window窗口机制：滑动时间窗口(Sliding Window)

~~~     滑动时间窗口Sliding Window
           

### --- 滑动时间窗口说明

~~~     滑动窗口是固定窗口的更广义的一种形式，滑动窗口由固定的窗口长度和滑动间隔组成
~~~     特点：窗口长度固定，可以有重叠
           

### --- 基于时间的滑动窗口

~~~     场景: 我们可以每30秒计算一次最近一分钟用户购买的商品总数
           

### --- 基于事件的滑动窗口

~~~     场景: 每10个 “相同”元素计算一次最近100个元素的总和
           

二、编程代码实现

### --- 编程代码实现

package com.yanqi.window;

import org.apache.flink.api.common.functions.MapFunction;
import org.apache.flink.api.java.tuple.Tuple3;
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.functions.source.SourceFunction;
import org.apache.flink.streaming.api.functions.windowing.WindowFunction;
import org.apache.flink.streaming.api.windowing.time.Time;
import org.apache.flink.streaming.api.windowing.windows.GlobalWindow;
import org.apache.flink.streaming.api.windowing.windows.TimeWindow;
import org.apache.flink.util.Collector;

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

public class WindowDemo {

    public static void main(String[] args) throws Exception {
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        //1、获取流数据源
        DataStreamSource<String> data = env.socketTextStream("hadoop01", 7777);
        DataStreamSource<String> data1 = env.addSource(new SourceFunction<String>() {
            int count = 0;

            @Override
            public void run(SourceContext<String> ctx) throws Exception {
                while (true) {
                    ctx.collect(count + "号数据源");
                    count++;
                    Thread.sleep(1000);
                }
            }

            @Override
            public void cancel() {

            }
        });
        SimpleDateFormat sdf = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss.SSS");
        //2、获取窗口
        SingleOutputStreamOperator<Tuple3<String, String, String>> maped = data.map(new MapFunction<String, Tuple3<String, String, String>>() {
            @Override
            public Tuple3<String, String, String> map(String value) throws Exception {

                long l = System.currentTimeMillis();
                String dataTime = sdf.format(l);
                Random random = new Random();
                int randomNum = random.nextInt(5);
                return new Tuple3<>(value, dataTime, String.valueOf(randomNum));
            }
        });
        KeyedStream<Tuple3<String, String, String>, String> keybyed = maped.keyBy(value -> value.f0);


        WindowedStream<Tuple3<String, String, String>, String, TimeWindow> timeWindow = keybyed.timeWindow(Time.seconds(5));

       //3、操作窗口数据
        SingleOutputStreamOperator<String> applyed = timeWindow.apply(new WindowFunction<Tuple3<String, String, String>, String, String, TimeWindow>() {
            @Override
            public void apply(String s, TimeWindow window, Iterable<Tuple3<String, String, String>> input, Collector<String> out) throws Exception {
                Iterator<Tuple3<String, String, String>> iterator = input.iterator();
                StringBuilder sb = new StringBuilder();
                System.out.println("...............");
                while (iterator.hasNext()) {
                    Tuple3<String, String, String> next = iterator.next();
                    sb.append(next.f0 + "..." + next.f1 + "..." + next.f2);

                }
                String s1 = s + "..." + sdf.format(window.getStart()) + "..." + sdf.format(window.getEnd())+ "..." + sb;
                out.collect(s1);

            }
        });
        //4、输出窗口数据
        applyed.print();
        env.execute();


    }
}
           

### --- 编译打印

~~~     # 启动nc
[[email protected] ~]# nc -lp 7777
 ~~~ 写入数据流
0号数据源
1号数据源
2号数据源
0号数据源 0号数据源 0号数据源
1号数据源 1号数据源 1号数据源
2号数据源 2号数据源 2号数据源
           

### --- 编译打印

D:\JAVA\jdk1.8.0_231\bin\java.exe "-javaagent:D:\IntelliJIDEA\IntelliJ IDEA 2019.3.3\lib\idea_rt.jar=51475:D:\IntelliJIDEA\IntelliJ IDEA 2019.3.3\bin" -Dfile.encoding=UTF-8 -classpath 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com.yanqi.window.WindowDemo

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2> 2号数据源...2021-10-30 00:08:55.000...2021-10-30 00:09:00.000...2号数据源...2021-10-30 00:08:57.401...0
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3> 1号数据源...2021-10-30 00:08:55.000...2021-10-30 00:09:00.000...1号数据源...2021-10-30 00:08:57.401...4
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3> 0号数据源...2021-10-30 00:08:55.000...2021-10-30 00:09:00.000...0号数据源...2021-10-30 00:08:57.401...4
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3> 0号数据源 0号数据源 0号数据源...2021-10-30 00:09:10.000...2021-10-30 00:09:15.000...0号数据源 0号数据源 0号数据源...2021-10-30 00:09:09.968...4
1> 1号数据源 1号数据源 1号数据源...2021-10-30 00:09:10.000...2021-10-30 00:09:15.000...1号数据源 1号数据源 1号数据源...2021-10-30 00:09:09.968...2
4> 2号数据源 2号数据源 2号数据源...2021-10-30 00:09:10.000...2021-10-30 00:09:15.000...2号数据源 2号数据源 2号数据源...2021-10-30 00:09:10.472...0