Hello.
My app needs Map[K, V] as simple cache for business data, which needs to be
invalidated periodically, lets say once per day.
Right now I'm using rather naive approach which is
trait Dictionary[K, V] extends Serializable {
@volatile private var cache: Map[K, V] = Map()
def lookup(id: K):
Hello Stefano
I have tried to implement what I understood from your mail earlier in the
day, but it doesn't seem to produce the result I expect. Here's the code
snippet:
-
val env = StreamExecutionEnvironment.createLocal
Hello again Nirmalaya,
in this case you are keying by timestamp; think of keying as grouping: this
means that windows are brought together according to their timestamp. I
misread your original post but now that I see the code I understand your
problem.
I've put some code here:
https://github.com/
Hi all,
I have two streams in which I need to keep counts of different metrics that
will have to be shared by both of the streams. So they will be sharing some
state once they have finished processing the stream. My question is if I
should do this as a sink aggregating what I need at the end or by
Hi Renato,
First of all to do anything together on the two streams you probably want
to union them. This means that you need to have a common type. If this is
the case you are lucky and you don't need anything else. Otherwise I
suggest using the Either type provided by Flink as a simple wrapper.
