From what you describe I infer (but it might be a wild guess), that you are actually trying to do KTable-KTable join?
It's all about the semantics of your input data... Note, that a Kafka topic does not have semantics per-se; you apply semantics when you read a topic either as stream or table though. -Matthias On 4/9/18 12:16 AM, adrien ruffie wrote: > Hello Matthias, > > thank for your response. I will try to read the blog post today. > > > For the keys, not really, In fact, keys are always the same "symbol" of a > STOCK example "YHOO", "INTC" and they never change. > > Do you with I need to use another key ? Or add a timestamp to the key ? > > For single stock join with multiple dividends, I didn't think about it before > ... is it possible ? > > > For join depending of timestamps why not, is it possible with windowing ? > > > Thank Matthias > > Adrien > > ________________________________ > De : Matthias J. Sax <matth...@confluent.io> > Envoyé : dimanche 8 avril 2018 23:04:24 > À : firstname.lastname@example.org > Objet : Re: join 2 topic streams --> to another topic > > 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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