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rankingapache-flinkflink-streamingtop-nwindowing

Last tuple of time window


I have the following situation

stream<Tuple2<String, Integer>
   .keyBy(0)
   .timeWindow(Time.of(10, TimeUnit.SECONDS))
   .sum(1)
   .flatMap(..)
   .sink()

What I am trying to do is calculate a top N for my time window. The top N for each window is stored by the sink.

I can calculate the top N in the flatmap, but I do not know when to send it to the sink for storage. As far as I can see there is no way to know when the window has ended from within the flatmap function.

I know there are alternatives such as an apply function which does both or creating markers in the stream to indicate the end, but I am wondering if there is a more elegant solution.


Solution

  • If you want to calculate the top N for each window over all keys, then you should apply a time window all with the same length in whose apply method you calculate the top N. You could do something like:

    final int n = 10;
    stream
        .keyBy(0)
        .timeWindow(Time.of(10L, TimeUnit.SECONDS))
        .sum(1)
        .timeWindowAll(Time.of(10L, TimeUnit.SECONDS))
        .apply(new AllWindowFunction<Tuple2<String,Integer>, Tuple2<String, Integer>, TimeWindow>() {
            @Override
            public void apply(TimeWindow window, Iterable<Tuple2<String, Integer>> values, Collector<Tuple2<String, Integer>> out) throws Exception {
                PriorityQueue<Tuple2<String, Integer>> priorityQueue = new PriorityQueue<>(n, new Comparator<Tuple2<String, Integer>>() {
                    @Override
                    public int compare(Tuple2<String, Integer> o1, Tuple2<String, Integer> o2) {
                        return o1.f1 - o2.f1;
                    }
                });
    
                for (Tuple2<String, Integer> value : values) {
                    priorityQueue.offer(value);
    
                    while (priorityQueue.size() > n) {
                        priorityQueue.poll();
                    }
                }
    
                for (Tuple2<String, Integer> stringIntegerTuple2 : priorityQueue) {
                    out.collect(stringIntegerTuple2);
                }
            }
        })
        .print();