/test/java/org/apache/flink/streaming/api/datastream/ReinterpretDataStreamAsKeyedStreamITCase.java#L98
>>
>> On Fri, Mar 29, 2019 at 6:09 AM Adrienne Kole
>> wrote:
>>
>>> Dear community,
>>>
>>> I have a use-case where sources are keyed.
&g
Dear community,
I have a use-case where sources are keyed.
For example, there is a source function with parallelism 10, and each
instance has its own key.
I used reinterpretAsKeyedStream to convert source DataStream to
KeyedStream, however, I get an IllegalArgument exception.
Is
n
>
> > Am 07.05.2017 um 23:23 schrieb Adrienne Kole <adrienneko...@gmail.com>:
> >
> > Hi,
> >
> > I am doing simple aggregation with a keyed and global windows in flink.
> > When I compare the keyed window aggregation with 1 key and global window
> (
Hi,
I am doing simple aggregation with a keyed and global windows in flink.
When I compare the keyed window aggregation with 1 key and global window
(which has parallelism 1) I would expect that both of them would have
similar performance.
However, keyed stream with 1 key performs with 2x more
Hi,
I recognized that, if the number of data input sources are less than or
equal to number of slots in one node, they (input source operators) are all
deployed in the same node. What is the logic behind this? Can't this be a
bottleneck for throughput and distribution of input sources?
Thanks
t;u...@apache.org> wrote:
Hey Adrienne!
On Wed, Oct 12, 2016 at 4:10 PM, Adrienne Kole <adrienneko...@gmail.com>
wrote:
> Hi,
>
> I have 2 streams which are partitioned based on key field. I want to join
> those streams based on key fields on windows. This is an example I sa
Hi,
I have 2 streams which are partitioned based on key field. I want to join
those streams based on key fields on windows. This is an example I saw in
the flink website:
val firstInput: DataStream[MyType] = ...
val secondInput: DataStream[AnotherType] = ...
val firstKeyed =
