Flink Scala API-应用新的窗口函数与应用功能



我修改了Flink的基本WordCount示例,并使用窗口函数播放。

WindowedStream的应用方法被超载,并且接受一个函数:

def apply[R: TypeInformation](
    function: (K, W, Iterable[T], Collector[R]) => Unit): DataStream[R] = { ... }

以及窗口功能:

def apply[R: TypeInformation](
    function: WindowFunction[T, R, K, W]): DataStream[R] = { ... }

在WindowedStream上赋予应用程序的函数时,我会得到编译,但是我的代码不会使用我的窗口函数编译(我不知道为什么..)。

这是基本流:

val windowCounts: WindowedStream[WordWithCount, String, TimeWindow] = text
    .flatMap { w => w.split("\s") }
    .map { w => WordWithCount(w, 1) }
    .keyBy(t => "all")
    .window(SlidingProcessingTimeWindows.of(Time.seconds(30), Time.seconds(10)))

这是我对窗口函数的含义。这个对我有用:

def distinctCount(
    s: String, tw: TimeWindow, input: Iterable[WordWithCount],
    out: Collector[String]): Unit = {
  val discount = input.map(t => t.word).toSet.size
  out.collect(s"Distinct elements: $discount")
}
// compiles
val distinctCountStream = windowCounts.apply { distinctCount _ }

这个不编译:

class DiscountWindowFunction extends WindowFunction[WordWithCount, String, String, TimeWindow] {
  override def apply(key: String, window: TimeWindow, input: lang.Iterable[WordWithCount], out: Collector[String]): Unit = {
    val discount = input.map(t => t.word).toSet.size
    out.collect(s"Distinct elements: $discount")
  }
  def apply(key: String, window: TimeWindow, input: Iterable[(String, Int)], out: Collector[String]): Unit = {
    apply(key, window, input.asJava, out)
  }
}
// does not compile
val distinctCount = windowCounts.apply(new DiscountWindowFunction())  

我正在使用Flink 1.3.2,这是我的进口:

import java.lang
import org.apache.flink.streaming.api.functions.windowing.WindowFunction
import org.apache.flink.streaming.api.scala._
import org.apache.flink.streaming.api.windowing.assigners.SlidingProcessingTimeWindows
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 scala.collection.JavaConversions._
import scala.collection.JavaConverters._

您已导入Java DataStream API中使用的WindowFunction

替换时,您的代码应编译

import org.apache.flink.streaming.api.functions.windowing.WindowFunction

import org.apache.flink.streaming.api.scala.function.WindowFunction

顺便说一句。感谢您提供的完整信息: - )

相关内容

  • 没有找到相关文章

最新更新