Hi Danny,

thanks for the quick reply.
Cost calculation we can of course provide (but it could be a bit different as 
we have not only CPU and Memory but also Network or something).

And also something like the RelNodes could be provided. In our case this would 
be "Requests" which are at first "Logical" and are then transformed to 
"Physical" Requests. For example the API allows you to request many fields per 
single request but some PLCs only allow one field per request. So this would be 
one task of this layer.

Julian

Am 19.08.19, 14:44 schrieb "Danny Chan" <[email protected]>:

    Cool idea ! Julian Feinauer ~
    
    I think the volcano model can be used the base of the cost algorithm. As 
long as you define all the metadata that you care about. Another thing is that 
you should have a struct like RelNode and a method like #computeSelfCost.
    
    Best,
    Danny Chan
    在 2019年8月19日 +0800 PM5:20,Julian Feinauer <[email protected]>,写道:
    > Hi folks,
    >
    > I’m here again with another PLC4X related question 
(https://plc4x.apache.org).
    > As we have more and more usecases we encounter situations where we send 
LOTS of replies to PLCs which one could sometimes optimize.
    > This has multiple reasons upstream (like multiple different Services 
sending, or you want two logically different addresses which could be 
physically equal).
    >
    > So, we consider to add some kind of optimizer which takes a Batch of 
requests and tries to arrange them in an “optimal” way with regard to som cost 
function.
    > The cost functions would of course be given by each Driver but the 
optimizer could / should be rather general (possibly with pluggable rules).
    >
    > As Calcites Planner already includes all of that I ask myself if it could 
be possible (and make sense) to use that in PLC4X.
    > Generally speaking, this raises the question if the Volcano approach can 
be suitable for such problems.
    > The other alternative would be to start with some kind of heuristic based 
planning or with other optimization algorithms (genetic algs, cross entropy,…).
    >
    > Any thoughs or feedbacks are welcome!
    >
    > Julian
    

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