Hi Titus,
have you looked into ProcessFunction? ProcessFunction[1] gives you
access to the two important streaming primitives "time" and "state".
So in your case you can decide flexibly what you want to put into state
and when you want to set and fire a timer (for clean-up) per key.
Regards,
Timo
[1]
https://ci.apache.org/projects/flink/flink-docs-release-1.5/dev/stream/operators/process_function.html
Am 17.07.18 um 11:39 schrieb Titus Rakkesh:
Friends, any assistance regarding this?
On Mon, Jul 16, 2018 at 3:44 PM, Titus Rakkesh <titus.rakk...@gmail.com>
wrote:
Dear All,
We have 2 independent streams which will receive elements in different
frequency,
DataStream<Tuple3<String, Integer, Double>> splittedActivationTuple;
DataStream<Tuple2<String, Double>> unionReloadsStream;
We have a requirement to keep "splittedActivationTuple" stream elements in
a Window of eviction time period of 24 hours. So I created a
"WindowedStream" like below,
WindowedStream<Tuple3<String, Integer, Double>, Tuple, GlobalWindow>
keyedWindowedActStream = splittedActivationTuple
.assignTimestampsAndWatermarks(new
IngestionTimeExtractor()).keyBy(0).window(GlobalWindows.create())
.evictor(TimeEvictor.of(Time.of(24, TimeUnit.HOURS)));
Our requirements are following,
1.
When "unionReloadsStream" receives data, we need to check whether the
corresponding "String" field matches with the "String" field in the
WindowedStream and accumulate "WindowedStream's" Double with
"unionReloadsStream" Double.Will this possible with Flink? I checked
CoGroup and CoMap. But I couldn't figure out how to do since I am new.
2.
CEP functionality to create a new Stream of from WindowedStream if the
Double value > 100? I went through several flink's CEP tutorials. But
couldn't able to figure out how to do with "WindowedStream"?
I am very new to flink. Any assistance would be highly appreciated.
Thanks,
Titus
