Hi Amol,
> In above code also it will sort the records in specific time window only.
All windows will be emitted as watermark passes the end of the window. The
watermark only increases. So the non-overlapping windows should be also sorted
by time and as a consequence the records across windows
Hi,
Good point, sorry for confusion, BoundedOutOfOrdernessTimestampExtractor of
course does not buffer records, you need to apply windowing (e.g.
TumblingEventTimeWindows) for that and then sort the window output by time and
emit records in sorted order.
You can also use windowAll which alread
Hi,
I think a global ordering is a bit impractical on production, but in theroy,
you still can do that. You need to
- Firstly fix the operate's parallelism to 1(except the source node).
- If you want to sort the records within a bouned time, then you can keyBy() a
constant and window it,
Hi Amol,
I think you could try (based on your stack overflow code)
org.apache.flink.streaming.api.functions.timestamps.BoundedOutOfOrdernessTimestampExtractor
like this:
DataStream streamSource = env
.addSource(kafkaConsumer)
.setParallelism(4)
.assignTimestampsAndWatermarks(
new
