Check out this blog post that explain how the different joins work: https://www.confluent.io/blog/crossing-streams-joins-apache-kafka/
It's hard to give a general answer -- it depends on the context of your application. Are keys unique? Do you want to get exactly one result or should a single stock join with multiple dividends? Do you want Stock and Dividend join depending the their timestamps? -Matthias On 4/8/18 1:34 PM, adrien ruffie wrote: > Hello all, > > I have 2 topics streamed by KStream<String, Stock> and one KStream<String, > Dividend> > > I want to merge both object's informations (Stock & Dividend) and send to > another topic > > with for example <String, DividendStockJoin> > > > The <String> key of 2 two topic is the same. I need to use, leftJoin, merge, > KTable, ... > > what is the best solution ? What do you think ? > > > Moreover, how can I make sure the timestamp are pretty much the same? (for > merging same key at the same time produced) Example: > > KStream<String, Stock> --> key: "YHOO", and one timestamp of record > 2018-04-08 19:56:30 > KStream<String, Dividend> --> key: "YHOO", and one timestamp of record > 2018-04-08 19:55:27 > > > I need a Windowing ? > > > Great thank & best regards, > > > Adrien >
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