Re: Batch Processing as Streaming
Thanks Stephan, That's clear ! Cheers On Thu, Jul 2, 2015 at 6:13 PM, Stephan Ewen wrote: > Hi! > > I am actually working to get some more docs out there, there is a lack > right now, agreed. > > Concerning your questions: > > (1) Batch programs basically recover from the data sources right now. > Checkpointing as in the streaming case does not happen for batch programs. > We have branches that materialize the intermediate streams and apply > backtracking logic for batch programs, but they are not merged into the > master at this point. > > (2) Streaming operators and user functions are long lived. They are > started once and live to the end of the stream, or the machine failure. > > Greetings, > Stephan > > > On Thu, Jul 2, 2015 at 11:48 AM, tambunanw wrote: > >> Hi All, >> >> I see that the way batch processing works in Flink is quite different with >> Spark. It's all about using streaming engine in Flink. >> >> I have a couple of question >> >> 1. Is there any support on Checkpointing on batch processing also ? Or >> that's only for streaming >> >> 2. I want to ask about operator lifecyle ? is that short live or long >> live ? >> Any docs where i can read about this more ? >> >> >> Cheers >> >> >> >> -- >> View this message in context: >> http://apache-flink-user-mailing-list-archive.2336050.n4.nabble.com/Batch-Processing-as-Streaming-tp1909.html >> Sent from the Apache Flink User Mailing List archive. mailing list >> archive at Nabble.com. >> > > -- Welly Tambunan Triplelands http://weltam.wordpress.com http://www.triplelands.com <http://www.triplelands.com/blog/>
Re: Batch Processing as Streaming
Hi! I am actually working to get some more docs out there, there is a lack right now, agreed. Concerning your questions: (1) Batch programs basically recover from the data sources right now. Checkpointing as in the streaming case does not happen for batch programs. We have branches that materialize the intermediate streams and apply backtracking logic for batch programs, but they are not merged into the master at this point. (2) Streaming operators and user functions are long lived. They are started once and live to the end of the stream, or the machine failure. Greetings, Stephan On Thu, Jul 2, 2015 at 11:48 AM, tambunanw wrote: > Hi All, > > I see that the way batch processing works in Flink is quite different with > Spark. It's all about using streaming engine in Flink. > > I have a couple of question > > 1. Is there any support on Checkpointing on batch processing also ? Or > that's only for streaming > > 2. I want to ask about operator lifecyle ? is that short live or long live > ? > Any docs where i can read about this more ? > > > Cheers > > > > -- > View this message in context: > http://apache-flink-user-mailing-list-archive.2336050.n4.nabble.com/Batch-Processing-as-Streaming-tp1909.html > Sent from the Apache Flink User Mailing List archive. mailing list archive > at Nabble.com. >
Batch Processing as Streaming
Hi All, I see that the way batch processing works in Flink is quite different with Spark. It's all about using streaming engine in Flink. I have a couple of question 1. Is there any support on Checkpointing on batch processing also ? Or that's only for streaming 2. I want to ask about operator lifecyle ? is that short live or long live ? Any docs where i can read about this more ? Cheers -- View this message in context: http://apache-flink-user-mailing-list-archive.2336050.n4.nabble.com/Batch-Processing-as-Streaming-tp1909.html Sent from the Apache Flink User Mailing List archive. mailing list archive at Nabble.com.
