We do not have in-memory window stores implemented yet: https://issues.apache.org/jira/browse/KAFKA-4730
On Wed, Jul 4, 2018 at 12:05 PM, Gleb Stsenov <gleb.stse...@gmail.com> wrote: > Hello Guozhang, > Thank you! > One thing to clarify: so, only persistent store can be windowed, right? > Demo default in-memory key-value store won't work? > /G. > > On Wed, Jul 4, 2018 at 9:45 PM, Guozhang Wang <wangg...@gmail.com> wrote: > > > Hello Gleb, > > > > For the first question, you should use a windowed store in your topology > > builder. > > > > And for the first / second question, I think using interactive query > should > > be fine, i.e. you can create different windows for different length, and > > use interactive queries to get the count on different window spans. > > > > > > Guozhang > > > > > > > > On Wed, Jul 4, 2018 at 8:34 AM, Gleb Stsenov <gleb.stse...@gmail.com> > > wrote: > > > > > Hello, > > > Just started with Kafka, took 2.0 because it has better unit test > > support. > > > Built custom processor, which is basically same as > WordCountProcessorDemo > > > example (github https://goo.gl/XSh7iW ) and can be treated as equal to > > > that. > > > > > > Built topology by adding source topic, processor, state store, and sink > > (to > > > topic). > > > Played with KafkaTool and console consumers, can see my wordcounts > since > > > beginning of publisher life. > > > > > > *Question*: > > > what would be the correct way to get wordcounts for last 24h? > > > > > > On topology creation, on processor init, or somehow related to > > "interactive > > > queries" feature? > > > First goal is answering to "what are the most common words during last > > 24h > > > (having word count > configured_X)". > > > Second goal is custom time window. Kinda if word "user" is the most > > common > > > in 24h, I want to know its word count for last 36h, or so. Sounds like > > > "interactive query" for me, but not sure. > > > > > > Read description of window types in doc, but can't get the idea of > > applying > > > them to processor API. > > > > > > Thank you. > > > BR, > > > Gleb. > > > > > > > > > > > -- > > -- Guozhang > > > -- -- Guozhang
