I'm aware of IterativeStream but I don't think it's useful in this case.
As shown in the example above, my use case is "cyclic" in that the same
object goes from *Input* to *predictionStream* (flatMap1), then to
*statsStream* (flatMap2, where it's updated with an object from *Input2*)
and finally
Hi,
which Flink version are you using?
This issue occurred quite freqently in the 1.2.0 RC0 and should be fixed in
later RCs.
On Fri, Jan 27, 2017 at 4:13 PM, Malte Schwarzer wrote:
> Hi all,
>
> when running a Flink batch job, from time to time a TaskManager dies
> randomly, which makes the fu
Hello,
Cyclic dataflows can be built using iterations:
https://ci.apache.org/projects/flink/flink-docs-release-1.2/dev/datastream_api.html#iterations
Best,
Gábor
2017-01-28 18:39 GMT+01:00 Matt :
> I have a ConnectedStream (A) that depends on another ConnectedStream (B),
> which depends on th
I have a ConnectedStream (A) that depends on another ConnectedStream (B),
which depends on the first one (A).
Simplified code:
*predictionStream = **input*
.connect(*statsStream*)
.keyBy(...)
.flatMap(CoFlatMapFunction {
flatMap1(obj, output) {
p = prediction(obj)
* ou
I'll create a new thread with my last message since it's not completely
related with the original question here.
On Sat, Jan 28, 2017 at 11:55 AM, Matt wrote:
> Aha, ok, got it!
>
> I just realized that this ConnectedStream I was talking about (A) depends
> on another ConnectedStream (B), which
env.setParallelism(5).addSource(???) will set the default parallelism for
this Job to 5 and then add the source.
--
View this message in context:
http://apache-flink-user-mailing-list-archive.2336050.n4.nabble.com/setParallelism-for-addSource-in-streaming-tp11343p11356.html
Sent from the Apache
Aha, ok, got it!
I just realized that this ConnectedStream I was talking about (A) depends
on another ConnectedStream (B), which depends on the first one (A). So it's
even trickier than I first thought.
For instance (simplified):
*predictionStream = **input*
.connect(*statsStream*)
.keyBy(..
