Hi Eleanore,
A dynamic filter like the one you need, is essentially a join operation.
There is two ways to do this:
* partitioning the key set and the message on the attribute. This would be
done with a KeyedCoProcessFunction.
* broadcasting the key set and just locally forwarding the messages. This
would be done with a KeyedBroadcastProcessFunction.
The challenge in your application is that the key set entries have
different types which is something that Flink does not very well support.
There is two ways to go about this:
1) route all data through the same operators that can handle all types. You
can model this with an n-ary Either type. Flink only has a binary Either
type, so you would need to implement the TypeInformation, serializer, and
comparator yourself. The Either classes should give you good guidance for
that.
2) have different operators and flows for each basic data type. This will
fan out your job, but should be the easier approach.
Best, Fabian
Am Do., 16. Jan. 2020 um 07:48 Uhr schrieb Jin Yi <eleanore....@gmail.com>:
> Hi there,
>
> I have the following usecase:
> a key set say [A,B,C,....] with around 10M entries, the type of the
> entries can be one of the types in BasicTypeInfo, e.g. String, Long,
> Integer etc...
>
> and each message looks like below:
> message: {
> header: A
> body: {}
> }
>
> I would like to use Flink to filter each message' header field, to see if
> the value present in the key set.
>
> *The key set needs to be dynamic, meaning at any time, we can perform
> add/read/delete operations on the key set. *
>
> Any suggestions are very welcome!
>
> Thanks a lot!
> Eleanore
>
