Hi
In the following example given in flink:
object ExampleCountWindowAverage extends App {
val env = StreamExecutionEnvironment.getExecutionEnvironment
env.fromCollection(List(
(1L, 3L),
(1L, 5L),
(1L, 7L),
(1L, 4L),
(1L, 2L)
)).keyBy(_._1)
.flatMap(new CountWindowAve
Hi
In the streaming pipe line of Scala we want to use intermediary Machine
Learning module written in python, Is it possible to use it ? Or entire pipe
line should be either Python or Scala, we can't mix?
Regards
Bhaskar
On 2018/09/13 03:30:28, Ken Krugler wrote:
> Hi Bhaskar,
>
> > On 2018/09/12 20:42:22, Ken Krugler wrote:
> >> Hi Bhaskar,
> >>
> >> I assume you don’t have 1000 streams, but rather one (keyed) stream with
> >> 1000 different key values, yes?
> >>
> >> If so, then this one stream is phys
On 2018/09/12 20:42:22, Ken Krugler wrote:
> Hi Bhaskar,
>
> I assume you don’t have 1000 streams, but rather one (keyed) stream with 1000
> different key values, yes?
>
> If so, then this one stream is physically partitioned based on the
> parallelism of the operator following the keyBy()
On 2018/09/12 16:55:09, bhaskar.eba...@gmail.com
wrote:
> Hi
>
> I have created a KeyedStream with state as explained below
> For example i have created 1000 streams, out of which 50% of streams data is
> going to come once in 8 hours. Will the resources of these under utilized
> streams
Hi
I have created a KeyedStream with state as explained below
For example i have created 1000 streams, out of which 50% of streams data is
going to come once in 8 hours. Will the resources of these under utilized
streams are idle for that duration? Or Flink internal task manager is having
some
