I know that this haven't been accepted yet but any news on it ? How can we
cache the product and user factor ?
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tFeatures().cache();
> Also I was trying to repartition those rdds and create new model from
> repartitioned versions but that also didn't help.
>
>
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Hi all!
I have MatrixFactorizationModel object. If I'm trying to recommend products to
single user right after constructing model through ALS.train(...) then it takes
300ms (for my data and hardware). But if I save model to disk and load it back
then recommendation takes almost 2000ms. Also Spar
