I have a question related to KeyedStream, asking it here instead of starting a new thread.
If I assign timestamps on a keyed stream, the resulting stream is not keyed. So essentially I would need to apply the key by operator again after the assign timestamps operator. Why should assigning timestamps to events change the stream from Keyed to Non-Keyed? Thanks, Shailesh On Fri, Apr 6, 2018 at 4:31 PM, Michael Latta <mla...@technomage.com> wrote: > Yes. It took a bit of digging in the website to find RichFlatMapFunction > to get managed state. > > Michael > > Sent from my iPad > > On Apr 6, 2018, at 3:29 AM, Fabian Hueske <fhue...@gmail.com> wrote: > > Hi, > > I think Flink is exactly doing what you are looking for. > If you use keyed state , Flink will put the state always in the context > of the key of the currently processed record. > So if you have a MapFunction with keyed state, and the map() method is > called with a record that has a key A, the state will be the state for key > A. If the next record has a key B, the state will be for key B. > > Best, > Fabian > >  https://ci.apache.org/projects/flink/flink-docs- > release-1.4/dev/stream/state/state.html#keyed-state > > 2018-04-05 14:08 GMT+02:00 Michael Latta <mla...@technomage.com>: > >> Thanks for the clarification. I was just trying to understand the >> intended behavior. It would have been nice if Flink tracked state for >> downstream operators by key, but I can do that with a map in the downstream >> functions. >> >> Michael >> >> Sent from my iPad >> >> On Apr 5, 2018, at 2:30 AM, Fabian Hueske <fhue...@gmail.com> wrote: >> >> Amit is correct. keyBy() ensures that all records with the same key are >> processed by the same paralllel instance of a function. >> This is different from "a parallel instance only sees records of one key". >> >> I had a look at the docs . >> I agree that "Logically partitions a stream into disjoint partitions, >> each partition containing elements of the same key." can be easily >> interpreted as you did. >> I've pushed a commit to clarify the description. The docs should be >> updated soon. >> >> Best, Fabian >> >>  https://ci.apache.org/projects/flink/flink-docs-release-1.4/ >> dev/stream/operators/#datastream-transformations >> >> 2018-04-05 6:21 GMT+02:00 Amit Jain <aj201...@gmail.com>: >> >>> Hi, >>> >>> KeyBy operation partition the data on given key and make sure same slot >>> will >>> get all future data belonging to same key. In default implementation, it >>> can >>> also map subset of keys in your DataStream to same slot. >>> >>> Assuming you have number of keys equal to number running slot then you >>> may >>> specify your custom keyBy operation to the achieve the same. >>> >>> >>> Could you specify your case. >>> >>> -- >>> Thanks >>> Amit >>> >>> >>> >>> -- >>> Sent from: http://apache-flink-user-mailing-list-archive.2336050.n4.nab >>> ble.com/ >>> >> >> >