我尝试在windowedstream上实现reduce，如下所示：

.keyBy(t -> t.key)
            .timeWindow(Time.of(15, MINUTES), Time.of(1, MINUTES))
            .reduce(new ReduceFunction<TwitterSentiments>() {
                @Override
                public TwitterSentiments reduce(TwitterSentiments t2, TwitterSentiments t1) throws Exception {
                    t2.positive += t1.positive;
                    t2.neutral += t1.neutral;
                    t2.negative += t1.negative;

                    return t2;
                }
            });

我遇到的问题是，当我调用stream.print（）时，我会得到许多值（看起来像每个twitter对象一个值，而不是一个聚合对象）。
我也尝试过使用这样的aggregationfunction，但有同样的问题：

.aggregate(new AggregateFunction<TwitterSentiments, Tuple3<Long, Long, Long>, Tuple3<Long, Long, Long>>() {
                @Override
                public Tuple3<Long, Long, Long> createAccumulator() {
                    return new Tuple3<Long, Long, Long>(0L,0L,0L);
                }

                @Override
                public Tuple3<Long, Long, Long> add(TwitterSentiments ts, Tuple3<Long, Long, Long> accumulator) {
                    return new Tuple3<Long, Long, Long>(
                            accumulator.f0 + ts.positive.longValue(),
                            accumulator.f1 + ts.neutral.longValue(),
                            accumulator.f2 + ts.negative.longValue()
                    );
                }

                @Override
                public Tuple3<Long, Long, Long> getResult(Tuple3<Long, Long, Long> accumulator) {
                    return accumulator;
                }

                @Override
                public Tuple3<Long, Long, Long> merge(Tuple3<Long, Long, Long> accumulator1, Tuple3<Long, Long, Long> accumulator2) {
                    return new Tuple3<Long, Long, Long>(
                            accumulator1.f0 + accumulator2.f0,
                            accumulator1.f1 + accumulator2.f1,
                            accumulator1.f2 + accumulator2.f1);
                }
            });

为什么stream.print（）在这些聚合之后仍然输出许多记录？