package com.test.topN;

import bean.ApacheLog;
import bean.UrlCount;
import org.apache.commons.compress.utils.Lists;
import org.apache.flink.api.common.eventtime.SerializableTimestampAssigner;
import org.apache.flink.api.common.eventtime.WatermarkStrategy;
import org.apache.flink.api.common.functions.AggregateFunction;
import org.apache.flink.api.common.functions.MapFunction;
import org.apache.flink.api.common.state.MapState;
import org.apache.flink.api.common.state.MapStateDescriptor;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.configuration.Configuration;
import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.functions.KeyedProcessFunction;
import org.apache.flink.streaming.api.functions.windowing.WindowFunction;
import org.apache.flink.streaming.api.windowing.assigners.SlidingEventTimeWindows;
import org.apache.flink.streaming.api.windowing.time.Time;
import org.apache.flink.streaming.api.windowing.windows.TimeWindow;
import org.apache.flink.util.Collector;
import java.sql.Timestamp;
import java.text.SimpleDateFormat;
import java.time.Duration;
import java.util.ArrayList;
import java.util.Iterator;
import java.util.Map;
/**
 * @author: Rango
 * @create: 2021-05-26 10:16
 * @description: 每隔5秒，输出最近10分钟内访问量最多的前N个URL
 **/
public class URLTopN3 {
    public static void main(String[] args) throws Exception {

        //1.建立环境
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment().setParallelism(1);

        //2.读取端口数据并映射到JavaBean，并定义watermark时间语义
        WatermarkStrategy<ApacheLog> wms = WatermarkStrategy
                .<ApacheLog>forBoundedOutOfOrderness(Duration.ofSeconds(1))
                .withTimestampAssigner(new SerializableTimestampAssigner<ApacheLog>() {
                    @Override
                    public long extractTimestamp(ApacheLog element, long recordTimestamp) {
                        return element.getTs();
                    }});

        SingleOutputStreamOperator<ApacheLog> apacheLogDS = env.socketTextStream("hadoop102", 9999)
                .map(new MapFunction<String, ApacheLog>() {
                    @Override
                    public ApacheLog map(String value) throws Exception {
                        SimpleDateFormat sdf = new SimpleDateFormat("dd/MM/yy:HH:mm:ss");
                        String[] split = value.split(" ");
                        return new ApacheLog(split[0],
                                split[2],
                                sdf.parse(split[3]).getTime(),
                                split[5],
                                split[6]);
                    }})
                .assignTimestampsAndWatermarks(wms);

        //3.第一次聚合，按url转为tuple2分组，开窗，增量聚合
        SingleOutputStreamOperator<UrlCount> aggregateDS = apacheLogDS
                .map(new MapFunction<ApacheLog, Tuple2<String, Integer>>() {
            @Override
            public Tuple2<String, Integer> map(ApacheLog value) throws Exception {
                return new Tuple2<>(value.getUrl(), 1);
            }}).keyBy(data -> data.f0)
                .window(SlidingEventTimeWindows.of(Time.minutes(10),Time.seconds(5)))
                .allowedLateness(Time.minutes(1))
                .aggregate(new HotUrlAggFunc(), new HotUrlWindowFunc());

        //4.第二次聚合，对第一次聚合输出按窗口分组，再全窗口聚合，建立定时器你，每5秒钟触发一次
        SingleOutputStreamOperator<String> processDS = aggregateDS
                .keyBy(data -> data.getWindowEnd())
                .process(new HotUrlProcessFunc(5));

        processDS.print();
        env.execute();
    }
    //实现AggregateFunction类中的方法
    public static class HotUrlAggFunc implements AggregateFunction<Tuple2<String, Integer>,Integer,Integer>{
        @Override
        public Integer createAccumulator() {return 0;}
        @Override
        public Integer add(Tuple2<String, Integer> value, Integer accumulator) { return accumulator+1;}
        @Override
        public Integer getResult(Integer accumulator) {return accumulator;}
        @Override
        public Integer merge(Integer a, Integer b) {return a+b; }
    }
    //实现窗口函数的apply方法，把累加函数输出的整数结果，转换为javabean类urlcount来做输出，方便后续按窗口聚合
    public static class HotUrlWindowFunc implements WindowFunction<Integer, UrlCount,String, TimeWindow> {
        @Override
        public void apply(String urls, TimeWindow window, Iterable<Integer> input, Collector<UrlCount> out) throws Exception {
            //获取按key相加后的次数并新建javabean（urlcount）作为返回
            Integer count = input.iterator().next();
            out.collect(new UrlCount(urls,window.getEnd(),count));
        }
    }
    //继承KeyedProcessFunction方法，重写processElemnt方法
    public static class HotUrlProcessFunc extends KeyedProcessFunction<Long,UrlCount,String>{
        //定义TopN为入参
        private Integer TopN;
        public HotUrlProcessFunc(Integer topN) {
            TopN = topN;
        }
        //定义状态
        private MapState <String,UrlCount>mapState;
        //open方法中初始化状态
        @Override
        public void open(Configuration parameters) throws Exception {
            mapState = getRuntimeContext()
                    .getMapState(new MapStateDescriptor<String, UrlCount>("map-state",String.class,UrlCount.class));
        }
        @Override
        public void processElement(UrlCount value, Context ctx, Collector<String> out) throws Exception {
            //状态装入数据
            mapState.put(value.getUrl(), value);
            //定时器,窗口一秒后触发
            ctx.timerService().registerEventTimeTimer(value.getWindowEnd()+1L);
            //再加一个定时器来清除状态用，在窗口关闭后再清除状态，这样延迟数据到达后窗口还能做排序
            ctx.timerService().registerEventTimeTimer(value.getWindowEnd()+61001L);
        }
        //定时器内容
        @Override
        public void onTimer(long timestamp, OnTimerContext ctx, Collector<String> out) throws Exception {
            if (timestamp == ctx.getCurrentKey()+61001L){
                mapState.clear();
                return;}

            //取出状态数据
            Iterator<Map.Entry<String, UrlCount>> iterator = mapState.iterator();
            ArrayList<Map.Entry<String, UrlCount>> entries = Lists.newArrayList(iterator);

            //排序
            entries.sort(((o1, o2) -> o2.getValue().getCount()-o1.getValue().getCount()));

            //排序后装入StringBulider作为输出TopN
            StringBuilder sb = new StringBuilder();
            sb.append("==============")
                    .append(new Timestamp(timestamp - 1L))
                    .append("==============")
                    .append("\n");
            for (int i = 0; i < Math.min(TopN,entries.size()); i++) {
                UrlCount urlCount = entries.get(i).getValue();
                sb.append("Top").append(i+1);
                sb.append(" Url:").append(urlCount.getUrl());
                sb.append(" Counts:").append(urlCount.getCount());
                sb.append("\n");
            }
            sb.append("==============")
                    .append(new Timestamp(timestamp - 1L))
                    .append("==============")
                    .append("\n")
                    .append("\n");

            out.collect(sb.toString());
            Thread.sleep(200);
            }}}
           

映射数据源的JavaBean

package bean;

import lombok.AllArgsConstructor;
import lombok.Data;
import lombok.NoArgsConstructor;

@Data
@NoArgsConstructor
@AllArgsConstructor
public class ApacheLog {
    private String ip;
    private String userId;
    private Long ts;
    private String method;
    private String url;
}

package bean;

import lombok.AllArgsConstructor;
import lombok.Data;
import lombok.NoArgsConstructor;

@Data
@NoArgsConstructor
@AllArgsConstructor
public class UrlCount {
    private String url;
    private Long windowEnd;
    private Integer count;
}