Thanks Aljoscha Krettek I will try the same. On Thu, Jun 15, 2017 at 3:11 PM, Aljoscha Krettek <aljos...@apache.org> wrote:
> Hi, > > How would you evaluate such a query? I think the answer could be that you > have to keep all that older data around so that you can evaluate when a new > event arrives. In Flink, you could use a ProcessFunction for that and use a > MapState that keeps events bucketed into one-week intervals. This way, can > more efficiently iterate over the buckets that are required when evaluating > a given event and you can also efficiently delete a complete bucket of > older events once you know that they are not required anymore. > > These are the relevant sections of the Flink doc: > - https://ci.apache.org/projects/flink/flink-docs- > release-1.3/dev/stream/state.html > - https://ci.apache.org/projects/flink/flink-docs-release-1.3/dev/stream/ > process_function.html > > Best, > Aljoscha > > On 13. Jun 2017, at 15:27, shashank agarwal <shashank...@gmail.com> wrote: > > Hi, > > I have to process each event with last 1 hour , 1 week and 1 month data. > Like how many times same ip occurred in last 1 month corresponding to that > event. \ > > I think window is for fixed time i can't calculate with last 1 hour > corresponding to current event. > > If you have any clue please guide what should i use Table, ProcessFunction > or global window. Or what approach should i take ? > > -- > Thanks Regards > > SHASHANK AGARWAL > --- Trying to mobilize the things.... > > > -- Thanks Regards SHASHANK AGARWAL --- Trying to mobilize the things....
