Flink Scala - Extending WindowFunction

Question

I am trying to figure out how to write my own WindowFunction but having issues, and I can not figure out why. The issue I am having is with the apply function, as it does not recognize MyWindowFunction as a valid input, so I can not compile. The data I am streaming contains (timestamp,x,y) where x and y are 0 and 1 for testing. extractTupleWithoutTs simply returns a tuple (x,y) . I have been running the code with simple sum and reduce functions with success. Grateful for any help :) Using Flink 1.3

Imports:

import org.apache.flink.streaming.api.TimeCharacteristic
import org.apache.flink.streaming.api.functions.AssignerWithPeriodicWatermarks
import org.apache.flink.streaming.api.scala.function.WindowFunction
import org.apache.flink.streaming.api.watermark.Watermark
import org.apache.flink.streaming.api.windowing.windows.TimeWindow
import org.apache.flink.util.Collector

Rest of the code:

val env = StreamExecutionEnvironment.getExecutionEnvironment
env.setStreamTimeCharacteristic(TimeCharacteristic.EventTime)
val text = env.socketTextStream("localhost", 9999).assignTimestampsAndWatermarks(new TsExtractor)
val tuple = text.map( str => extractTupleWithoutTs(str))
val counts = tuple.keyBy(0).timeWindow(Time.seconds(5)).apply(new MyWindowFunction())
counts.print()
env.execute("Window Stream")

MyWindow function which is basically copy paste from example with changes of the types.

class MyWindowFunction extends WindowFunction[(Int, Int), Int, Int, TimeWindow] {
  def apply(key: Int, window: TimeWindow, input: Iterable[(Int, Int)], out: Collector[Int]): () = {
    var count = 0
    for (in <- input) {
      count = count + 1
    }
    out.collect(count)
  }
}

Answer 1

The problem is the third type parameter of the WindowFunction , ie, the type of the key. The key is declared with an index in the keyBy method ( keyBy(0) ). Therefore, the type of the key cannot be determined at compile time. The same problem arises, if you declare the key as a string, ie, keyBy("f0") .

There are two options to resolve this:

1. Use a KeySelector function in keyBy to extract the key (something like keyBy(_._1) ). The return type of the KeySelector function is known at compile time such that you can use a correctly typed WindowFunction with an Int key.
2. Change the type of the third type parameter of the WindowFunction to org.apache.flink.api.java.tuple.Tuple , ie, WindowFunction[(Int, Int), Int, org.apache.flink.api.java.tuple.Tuple, TimeWindow] . Tuple is a generic holder for the keys extracted by keyBy . In your case it will be a org.apache.flink.api.java.tuple.Tuple1 . In WindowFunction.apply() you can cast Tuple to Tuple1 and access the key field by Tuple1.f0 .