Is accumulator logic heavy in flink?

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I am trying to check the flink performance using kafka source. My process logic contains the aggregating the values. When I see the metrics, .aggregate after .keyBy and .window (TumblingWindow for 60sec) caused the backpressured and it eventually affects the kafka source throughput.

I think that aggregting is just count the value using incoming data but my experiment showed me that it cause the upstream performance.

Is this real in flink?

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