flink5 - window_flink5秒内最小温度-优快云博客

该博客展示了如何使用Apache Flink处理来自多个传感器的实时温度数据。通过创建一个简单的流处理应用程序，它演示了如何将输入数据转换为SensorReading案例类，然后应用时间窗口进行15秒的温度统计，找出每个传感器的最低温度。整个过程涉及到数据的接收、转换、分组、窗口操作和结果输出。

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D:\develop_software\netcat-win32-1.12> nc -l -p 7777
sensor_1,1547718199,35.8
sensor_6,1547718201,15.4
sensor_7,1547718202,6.7
sensor_10,1547718205,38.1
sensor_1,1547718129,29.8
sensor_1,1547718158,5.8
sensor_1,1547718140,40.8

package com.sinktest
//定义样例类，温度传感器
case class SensorReading4(id:String,timestamp:Long,temperature:Double)
import org.apache.flink.api.common.functions.ReduceFunction
import org.apache.flink.streaming.api.scala._
import org.apache.flink.streaming.api.windowing.time.Time
//定义样例类，温度传感器
case class SensorReading5(id:String,timestamp:Long,temperature:Double)
object WindowTest {
  def main(args: Array[String]): Unit = {
    val env=StreamExecutionEnvironment.getExecutionEnvironment

    val inputStream=env.socketTextStream("localhost",7777)
    //1.先转换成样例类类型
    val dataStream= inputStream.map(data=>{
      val arr = data.split(",")
      SensorReading5(arr(0),arr(1).toLong,arr(2).toDouble)
    })
    //每15秒统计一次，窗口内各传感器所有温度的最小值,最小的温度值
    val resultStream= dataStream
      .keyBy("id")//按照二元组的第一个元素分组(id)
      //.window(TumblingEventTimeWindows.of(Time.seconds(15))) //滚动窗口
      //.window(SlidingEventTimeWindows.of(Time.seconds(15),Time.seconds(3))) //滑动窗口
      //.window(EventTimeSessionWindows.withGap(Time.seconds(10))) //会话窗口
      //.countWindow(10) //滚动窗口
      .timeWindow(Time.seconds(15)) //简写 滚动窗口
      .reduce(new MyReducer)

      resultStream.print()

      env.execute()
  }
}

class MyReducer extends ReduceFunction[SensorReading5]{
  override def reduce(t1: SensorReading5, t2: SensorReading5): SensorReading5 = {
    SensorReading5(t1.id,t2.timestamp,t1.temperature.min(t2.temperature))
  }
}