How about using a source and broadcast variable?

You could write the model to the storage (DFS), the read it with a source
and use a broadcast variable to send it to all tasks.
A single record can be very large, so it should work even if your model is
quite big.

Does that sound feasible?

In future versions of flink, you may be able to skip the "write to DFS"
step and simply have the model in a collection source (when large RPC
messages are supported).

Best,
Stephan



On Fri, Sep 2, 2016 at 11:20 AM, Bauss, Julian <julian.ba...@bonprix.net>
wrote:

> Hello Everybody,
>
>
>
> I’m currently refactoring some code and am looking for a better
> alternative to handle
>
> JPMML-Models in data streams. At the moment the flink job I’m working on
> references a model-object
>
> as a Singleton which I want to change because static references tend to
> cause problems in distributed systems.
>
>
>
> I thought about handing the model-object to the function that uses it as a
> variable closure. The object
>
> can be between 16MB and 250MB in size (depending on the depth of the
> decision tree).
>
>
>
> According to https://cwiki.apache.org/confluence/display/FLINK/
> Variables+Closures+vs.+Broadcast+Variables that’s way too large though.
>
> Are there any viable alternatives or would this be the „right way“ to
> handle this situation?
>
>
>
> Best Regards,
>
>
>
> Julian
>
>
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