Hi Gyula,
Thanks a lot. That's really help a lot !
Have a great vacation
Cheers
On Fri, Aug 21, 2015 at 7:47 PM, Gyula Fóra wrote:
> Hi
>
> You are right, if all operators need continuous updates than the most
> straightforward way is to push all the updates to the operators like you
> descri
Hi
You are right, if all operators need continuous updates than the most
straightforward way is to push all the updates to the operators like you
described.
If the cached data is the same for all operators and is small enough you
can centralize the updates in a dedicated operator and push the upd
Hi Gyula,
I have a couple of operator on the pipeline. Filter, mapper, flatMap, and
each of these operator contains some cache data.
So i think that means for every other operator on the pipeline, i will need
to add a new stream to update each cache data.
Cheers
On Thu, Aug 20, 2015 at 5:33 PM
Hi,
I don't think I fully understand your question, could you please try to be
a little more specific?
I assume by caching you mean that you keep the current model as an operator
state. Why would you need to add new streams in this case?
I might be slow to answer as I am currently on vacation wi
Hi Gyula,
I have another question. So if i cache something on the operator, to keep
it up to date, i will always need to add and connect another stream of
changes to the operator ?
Is this right for every case ?
Cheers
On Wed, Aug 19, 2015 at 3:21 PM, Welly Tambunan wrote:
> Hi Gyula,
>
> Th
Hi Gyula,
That's really helpful. The docs is improving so much since the last time
(0.9).
Thanks a lot !
Cheers
On Wed, Aug 19, 2015 at 3:07 PM, Gyula Fóra wrote:
> Hey,
>
> If it is always better to check the events against a more up-to-date model
> (even if the events we are checking arrive
Hey,
If it is always better to check the events against a more up-to-date model
(even if the events we are checking arrived before the update) then it is
fine to keep the model outside of the system.
In this case we need to make sure that we can push the updates to the
external system consistentl
Thanks Gyula,
Another question i have..
> ... while external model updates would be *tricky *to keep consistent.
Is that still the case if the Operator treat the external model as
read-only ? We create another stream that will update the external model
separately.
Could you please elaborate more
In that case I would apply a map to wrap in some common type, like a n
Either before the union.
And then in the coflatmap you can unwrap it.
On Wed, Aug 19, 2015 at 9:50 AM Welly Tambunan wrote:
> Hi Gyula,
>
> Thanks.
>
> However update1 and update2 have a different type. Based on my
> understa
Hi Gyula,
Thanks.
However update1 and update2 have a different type. Based on my
understanding, i don't think we can use union. How can we handle this one ?
We like to create our event strongly type to get the domain language
captured.
Cheers
On Wed, Aug 19, 2015 at 2:37 PM, Gyula Fóra wrote
Hey,
One input of your co-flatmap would be model updates and the other input
would be events to check against the model if I understand correctly.
This means that if your model updates come from more than one stream you
need to union them into a single stream before connecting them with the
event
Hi Gyula,
Thanks for your response.
However the model can received multiple event for update. How can we do
that with co-flatmap as i can see the connect API only received single
datastream ?
> ... while external model updates would be tricky to keep consistent.
Is that still the case if the Op
Hey!
I think it is safe to say that the best approach in this case is creating a
co-flatmap that will receive updates on one input. The events should
probably be broadcasted in this case so you can check in parallel.
This approach can be used effectively with Flink's checkpoint mechanism,
while e
Hi All,
We have a streaming computation that required to validate the data stream
against the model provided by the user.
Right now what I have done is to load the model into flink operator and
then validate against it. However the model can be updated and changed
frequently. Fortunately we alway
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