为什么我在 Flink 中的 MapState 变量不保留以前的值?

Why my MapState variable in Flink is not persisting previous values?

我正在 Java 中实现 Flink 程序以使用 MapStateDescriptor 处理状态。我的实现基于此 source。出于某种原因,MapState 保留了以前的值,我无法计算出我想要的平均值。当我调试时 averageTemp 总是空的,我从来没有在里面找到任何钥匙。我在实施过程中遗漏了什么?

import java.util.Map;

import org.apache.flink.api.common.functions.RichMapFunction;
import org.apache.flink.api.common.state.MapState;
import org.apache.flink.api.common.state.MapStateDescriptor;
import org.apache.flink.api.java.functions.KeySelector;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.configuration.Configuration;
import org.apache.flink.streaming.api.TimeCharacteristic;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.sense.flink.mqtt.MqttTemperature;
import org.sense.flink.mqtt.TemperatureMqttConsumer;

public class SensorsMultipleReadingMqttEdgentQEP {

    public SensorsMultipleReadingMqttEdgentQEP() throws Exception {
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        env.setStreamTimeCharacteristic(TimeCharacteristic.IngestionTime);

        DataStream<MqttTemperature> temperatureStream01 = env.addSource(new TemperatureMqttConsumer("topic-edgent-01"));
        DataStream<MqttTemperature> temperatureStream02 = env.addSource(new TemperatureMqttConsumer("topic-edgent-02"));
        DataStream<MqttTemperature> temperatureStream03 = env.addSource(new TemperatureMqttConsumer("topic-edgent-03"));
        DataStream<MqttTemperature> temperatureStreams = temperatureStream01.union(temperatureStream02)
                .union(temperatureStream03);

        DataStream<Tuple2<String, Double>> average = temperatureStreams.keyBy(new TemperatureKeySelector())
                .map(new AverageTempMapper());
        average.print();

        env.execute("SensorsMultipleReadingMqttEdgentQEP");
    }

    public static class TemperatureKeySelector implements KeySelector<MqttTemperature, Integer> {

        private static final long serialVersionUID = 5905504239899133953L;

        @Override
        public Integer getKey(MqttTemperature value) throws Exception {
            return value.getId();
        }
    }

    public static class AverageTempMapper extends RichMapFunction<MqttTemperature, Tuple2<String, Double>> {

        private static final long serialVersionUID = -5489672634096634902L;
        private MapState<String, Double> averageTemp;

        @Override
        public void open(Configuration parameters) throws Exception {
            averageTemp = getRuntimeContext()
                    .getMapState(new MapStateDescriptor<>("average-temperature", String.class, Double.class));
        }

        @Override
        public Tuple2<String, Double> map(MqttTemperature value) throws Exception {
            String key = "no-room";
            Double temp = value.getTemp();

            if (value.getId().equals(1) || value.getId().equals(2) || value.getId().equals(3)) {
                key = "room-A";
            } else if (value.getId().equals(4) || value.getId().equals(5) || value.getId().equals(6)) {
                key = "room-B";
            } else if (value.getId().equals(7) || value.getId().equals(8) || value.getId().equals(9)) {
                key = "room-C";
            }
            // NEVER ITERATES ON THE averageTemp
            for (Map.Entry<String, Double> entry: averageTemp.entries()) {
                System.out.println(entry.getKey() + " - " + entry.getValue());
            }

            System.out.println("value: " + value);
            if (averageTemp.contains(key)) { // NEVER CONTAINS A KEY
                System.out.println("yes: " + key);
                temp = (averageTemp.get(key) + value.getTemp()) / 2;
            } else {
                averageTemp.put(key, temp);
            }
            return Tuple2.of(key, temp);
        }
    }
}

**编辑:**好的。我误解了这个问题。代码将以前的状态保存在 MapState 上。我错了,因为我正在调试代码。但实际上我遇到的问题是它启动了 1 个以上的线程,并且在开始计算平均值之前至少覆盖了我的地图值 3 次。

您的地图函数中的状态基于每个键。因此,当调用 map 函数并获得 map 状态时,它将针对正在处理的 MqttTemperature 记录中的任何 id。

鉴于您需要每个房间的平均温度,我将按如下方式处理:

  1. 根据 id 字段将 TemperatureKeySelector 更改为 return room-Aroom-Broom-C
  2. AverageTempMapper 中,有两个 ValueState 变量 - 一个是温度总和 (Double),另一个是计数。当你的map()方法被调用时,如果这两个ValueState变量中有一个为null,则将其初始化为0,然后sum/increment.