Seems like we have two separate components. One is to allow interpreters to update interpreter results. The other is interpreters that do that.
> On Aug 28, 2015, at 11:02 AM, IT CTO <[email protected]> wrote: > > +1 for streaming support. > > בתאריך יום ו׳, 28 באוג׳ 2015, 17:53 מאת Christian Tzolov <[email protected] >> : > >> I've been exploring lately how would a streaming platforms fit into >> Zeppelin. >> >> The streaming processes are continuous as opposed to the usual Paragraph's >> batch like jobs. >> >> For example you start the twitter search stream in a paragraph (by clicking >> the Run button) the underlying streaming platform will open a stream and >> will return and the Paragraph will show a 'FINISHED' state while the real >> state in this case is 'STARTED' (or alike)? >> >> Currently Zeppelin doesn't seem to provide abstractions to track and stop >> such long-living tasks? >> >> I've checked the Spark Streaming tutorial but couldn't find an explanation >> of how to track and stop running streams? >> >> Do you think this is a valid use case for Zeppelin? Perhaps Spark Streaming >> and Flink have already solved this somehow? >> >> If you think this is valid use case i will open a JIRA ticket so we can >> start looking for solutions. >> >> Cheers, >> Christian >> >> -- >> Christian Tzolov <http://www.linkedin.com/in/tzolov> | Solution Architect, >> EMEA Practice Team | Pivotal <http://pivotal.io/> >> [email protected]|+31610285517 >>
