I am not sure if I can follow. However, in Kafka Streams using window aggregation, the windowed KTable uses a key-value store internally -- it's only called windowed store because it encodes the key for the store as pair of <record-key:windowId> and also applies a couple of other mechanism with regard to retention time to delete old windows.
Does this answer your question? -Matthias On 12/14/16 6:46 AM, Mikael Högqvist wrote: > Hi, > > I'm wondering about the tradeoffs when implementing a tumbling window with > a long retention, e.g. 1 year. Is it better to use a normal key value store > and aggregate the time bucket using a group by instead of a window store? > > Best, > Mikael >
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