EXTEND_MODEL_CASES flag in PredictTimeSeries - is it actual training on the new "extended" data ?

Question

Hi to all, I have Enterprise SQL OLAP Server.

I want to extend AND TRAIN my existing mining model with new data, all manuals including MSDN, assert it is possible with EXTEND_MODEL_CASES in PREDICTION JOIN queries.

I build the query as described, and i receive some results indeed.

But, when i test the mining model, to check the new cases actually added to existing cases, with this simple test query:

select top 10 * FROM MINING STRUCTURE MineStruct1.CASES order by time desc

i see that, there is no single new case added, all the existing cases are old, that populated with "insert into .." initial process.

So, it looks like, the added cases is not any training, just temporary substitution, and being such, does not affects prediction algorithm noway.

But now i see no value in such technique, for what thing it may be good ?

Is it the only way to get use of updated data - is to reprocess the existing mining model totally, even when added only several new records ?

I very appreciate any explanations, help, or just notes

(Tags: DMX, processing, model, cases, on the fly, train, time series, prediction)