Hi All, I have looked into Windowing concepts from Apache Beam and the PR #319 by David. Looks like there are a lot of advanced concepts which could be used by operators using event time windowing. Additionally I also looked at the Managed State implementation.
One of the things I noticed is that there is an overlap of functionality between Managed State and Windowing Support in terms of the following: - *Discarding / Dropping of tuples* from the system - Managed State uses the concept of expiry while a Windowed operator uses the concepts of Watermarks and allowed lateness. If I try to reconcile the above two, it seems like Managed State (through TimeBucketAssigner) is trying to implement some sort of implicit heuristic Watermarks based on either the user supplied time or the event time. - *Global Window* support - Once we have an option to disable purging in Managed State, it will have similar semantics to the Global Window option in Windowing support. If I understand correctly, is the suggestion to implement the Dedup operator as a Windowed operator and to use managed state only as a storage medium (through WindowedStorage) ? What could be a better way of going about this? Thanks. ~ Bhupesh On Wed, Jun 29, 2016 at 10:35 PM, Bhupesh Chawda <bhup...@apache.org> wrote: > Hi Thomas, > > I agree that the case of processing bounded data is a special case of > unbounded data. > Th difference I was pointing out was in terms of expiry. This is not > applicable in case of bounded data sets, while unbounded data sets will > inherently use expiry for limiting the amount of data to be stored. > > For idempotency when applying expiry on the streaming data, I need to > explore more on the using the window timestamp that you proposed as opposed > to the system time which I was planning to use. > > Thanks. > ~ Bhupesh > > On Wed, Jun 29, 2016 at 8:39 PM, Thomas Weise <tho...@datatorrent.com> > wrote: > >> Bhupesh, >> >> Why is there a distinction between bounded and unbounded data? I see the >> former as a special case of the latter? >> >> When rewinding the stream or reprocessing the stream in another run the >> operator should produce the same result. >> >> This operator should be idempotent also. That implies that code does not >> rely on current system time but the window timestamp instead. >> >> All of this should be accomplished by using the windowing support: >> https://github.com/apache/apex-malhar/pull/319 >> >> Thanks, >> Thomas >> >> >> >> >> >> >> On Wed, Jun 29, 2016 at 4:32 AM, Bhupesh Chawda <bhup...@datatorrent.com> >> wrote: >> >> > Hi All, >> > >> > I want to validate the use cases for de-duplication that will be going >> as >> > part of this implementation. >> > >> > - *Bounded data set* >> > - This is de-duplication for bounded data. For example, data sets >> > which are old or fixed or which may not have a time field at >> > all. Example: >> > Last year's transaction records or Customer data etc. >> > - Concept of expiry is not needed as this is bounded data set. >> > - *Unbounded data set* >> > - This is de-duplication of online streaming data >> > - Expiry is needed because here incoming tuples may arrive later >> than >> > what they are expected. Expiry is always computed by taking the >> > difference >> > in System time and the Event time. >> > >> > Any feedback is appreciated. >> > >> > Thanks. >> > >> > ~ Bhupesh >> > >> > On Mon, Jun 27, 2016 at 11:34 AM, Bhupesh Chawda < >> bhup...@datatorrent.com> >> > wrote: >> > >> > > Hi All, >> > > >> > > I am working on adding a De-duplication operator in Malhar library >> based >> > > on managed state APIs. I will be working off the already created JIRA >> - >> > > https://issues.apache.org/jira/browse/APEXMALHAR-1701 and the initial >> > > pull request for an AbstractDeduper here: >> > > https://github.com/apache/apex-malhar/pull/260/files >> > > >> > > I am planning to include the following features in the first version: >> > > 1. Time based de-duplication. Assumption: Tuple_Key -> Tuple_Time >> > > correlation holds. >> > > 2. Option to maintain order of incoming tuples. >> > > 3. Duplicate and Expired ports to emit duplicate and expired tuples >> > > respectively. >> > > >> > > Thanks. >> > > >> > > ~ Bhupesh >> > > >> > >> > >
