FLink17--聚合函数-AggWindowApp

一、依赖

二、代码

package net.xdclass.class11;

import org.apache.flink.api.common.RuntimeExecutionMode;
import org.apache.flink.api.common.functions.AggregateFunction;
import org.apache.flink.api.java.functions.KeySelector;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.datastream.KeyedStream;
import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.windowing.assigners.TumblingProcessingTimeWindows;
import org.apache.flink.streaming.api.windowing.time.Time;

import net.xdclass.model.VideoOrder;
import net.xdclass.source.VideoOrderSourceV2;

/**
 *  增量聚合 aggregate(new AggregateFunction){});
 * @desc Agg增量聚合函数，把窗口数据和存储器数据累加，不能获取全窗口数据
 *    逻辑复杂的话需要用这种方式对数据做加工，简单的话直接用基本算子就可以
 * @menu
 */
public class FLink17AggWindowApp {

    public static void main(String[] args) throws Exception{
        //WebUi方式运行
//        final StreamExecutionEnvironment env =
//                StreamExecutionEnvironment.createLocalEnvironmentWithWebUI(new Configuration());
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        //设置运行模式为流批一体
        env.setRuntimeMode(RuntimeExecutionMode.AUTOMATIC);
        //并行度
        env.setParallelism(1);
        //设置为自定义source
//        DataStream<VideoOrder> ds = env.addSource(new VideoOrderSourceV2());
        DataStream<VideoOrder> ds = env.addSource(new VideoOrderSourceV2());

        KeyedStream<VideoOrder, Object> keyByDs = ds.keyBy(new KeySelector<VideoOrder, Object>() {
            @Override
            public Object getKey(VideoOrder videoOrder) throws Exception {
                return videoOrder.getTitle();
            }
        });

        DataStream<VideoOrder> aggregate = keyByDs.window(
                TumblingProcessingTimeWindows.of(Time.seconds(5)))
                //输入，聚合结果，输出
                .aggregate(new AggregateFunction<VideoOrder, VideoOrder, VideoOrder>() {
                    //初始化累加器，每批都会初始化对象
                    @Override
                    public VideoOrder createAccumulator() {
//                        System.out.println("初始化对象");
                        VideoOrder videoOrder = new VideoOrder();
                        return videoOrder;
                    }

                    //videoOrder存储累加内容，value新数据
                    @Override
                    public VideoOrder add(VideoOrder value, VideoOrder videoOrder) {
                        videoOrder.setMoney(value.getMoney() + videoOrder.getMoney());
                        videoOrder.setTitle(value.getTitle());
                        if (videoOrder.getCreateTime() == null) {
                            videoOrder.setCreateTime(value.getCreateTime());
                        }
                        if (videoOrder.getTitle() == null) {
                            videoOrder.setTitle(value.getTitle());
                        }
                        return videoOrder;
                    }

                    //获取结果
                    @Override
                    public VideoOrder getResult(VideoOrder videoOrder) {
                        return videoOrder;
                    }

                    //合并操作，可以不写
                    @Override
                    public VideoOrder merge(VideoOrder a, VideoOrder b) {
                        VideoOrder videoOrder = new VideoOrder();
                        videoOrder.setMoney(a.getMoney() + b.getMoney());
                        videoOrder.setTitle(a.getTitle());
                        return videoOrder;
                    }
                });
        aggregate.print();
        //DataStream需要调用execute,可以取个名称
        env.execute("Sailing Window job");
    }
}