Hi,
Watermarks are not holding back records. Instead they define the event-time
at an operator (as Vino said) and can trigger the processing of data if the
logic of an operator is based on time.
For example, a window operator can emit complete results for a window once
the time passed the
Hi Soheil,
I feel that some of your understanding is a bit problematic.
*"After that according to the current watermark, data with the timestamp
between the last watermark and current watermark will be released and go to
the next steps"*
The main role of Watermark here is to define the progress
Suppose we have a time window of 10 milliseconds and we use EventTime.
First, we determine how Flink can get time and watermark from
incoming messages, after that, we set a key for the stream and set a time
window.
aggregatedTuple
.assignTimestampsAndWatermarks(new
