java - 使用 Flink DataStream 计算窗口持续时间的平均值

Question

我在有机架可用的地方使用 Flink DataStream API，我想通过机架 ID 计算温度组的“平均值”。我的窗口持续时间是 40 秒，我的窗口每 10 秒滑动一次......下面是我的代码，我每 10 秒为每个 rackID 计算温度的 sum，但现在我想计算 < strong>平均温度::

static Properties properties=new Properties();
    public static Properties getProperties()
    {
        properties.setProperty("bootstrap.servers", "54.164.200.104:9092");
        properties.setProperty("zookeeper.connect", "54.164.200.104:2181");
        //properties.setProperty("deserializer.class", "kafka.serializer.StringEncoder");
        //properties.setProperty("group.id", "akshay");
        properties.setProperty("auto.offset.reset", "earliest");
        return properties;
    }

 @SuppressWarnings("rawtypes")
public static void main(String[] args) throws Exception 
{
    StreamExecutionEnvironment env=StreamExecutionEnvironment.getExecutionEnvironment();
    env.setStreamTimeCharacteristic(TimeCharacteristic.EventTime);
    Properties props=Program.getProperties();
    DataStream<TemperatureEvent> dstream=env.addSource(new FlinkKafkaConsumer09<TemperatureEvent>("TemperatureEvent", new TemperatureEventSchema(), props)).assignTimestampsAndWatermarks(new IngestionTimeExtractor<>());
    DataStream<TemperatureEvent> ds1=dstream.keyBy("rackId").timeWindow(Time.seconds(40), Time.seconds(10)).sum("temperature");
    env.execute("Temperature Consumer");
}

如何计算上述示例的平均温度？？

Answer 1

据我所知，您需要自己编写平均函数。你可以在这里找到一个例子:

https://github.com/apache/flink/blob/master/flink-examples/flink-examples-streaming/src/main/java/org/apache/flink/streaming/examples/windowing/GroupedProcessingTimeWindowExample.java

在你的情况下，你可能会更换.sum("温度");

类似的东西.apply(new Avg());并实现 Avg 类:

public class Avg implements WindowFunction<TemperatureEvent,  TemperatureEvent, Long, org.apache.flink.streaming.api.windowing.windows.Window> {

  @Override
  public void apply(Long key, Window window, Iterable<TemperatureEvent> values, Collector<TemperatureEvent> out) {
    long sum = 0L;
    int count = 0;
    for (TemperatureEvent value : values) {
        sum += value.getTemperature();
        count ++;
    }

    TemperatureEvent result = values.iterator().next();
    result.setTemperature(sum / count);
    out.collect(result);
  }
}

注意:如果您的函数有可能在空窗口中被调用(例如，通过使用自定义触发器)，您需要在访问 elements.head 之前进行检查