Hi Bhupesh, I just added the method setFixedLateness(long millis) to AbstractWindowedOperator in my PR. This will allow you to specify the lateness with respect to the timestamp from the window ID without watermark tuples from upstream.
David On Thu, Jul 7, 2016 at 11:49 AM, David Yan <da...@datatorrent.com> wrote: > Hi Bhupesh, > > Yes, the windowed operator currently depends on the watermark tuples > upstream for any "lateness" related operation. If there is no watermark, > nothing will be considered late. We can add support for lateness handling > without incoming watermark tuples. Let me add that to the pull request. > > David > > > On Wed, Jul 6, 2016 at 10:48 PM, Bhupesh Chawda <bhup...@apache.org> > wrote: > >> Hi David, >> >> Thanks for your reply. >> >> If I am to use a windowed operator for the Dedup operator, there should be >> some operator (upstream to Deduper) which sends the watermark tuples. >> These >> tuples (along with allowed lateness), will be the ones deciding which >> incoming tuples are too late and will be dropped. I have the following >> questions: >> >> Is a windowed operator (which needs watermarks) dependent upon some other >> operator for these tuples? What happens when there are no watermark tuples >> sent from upstream? >> >> Can a windowed operator "*assume*" the watermark tuples based on some >> notion of time? For example, can the Deduper, use the streaming window >> time >> as the reference to advance the watermark? >> >> Thanks. >> >> ~ Bhupesh >> >> On Thu, Jul 7, 2016 at 4:07 AM, David Yan <da...@datatorrent.com> wrote: >> >> > Hi Bhupesh, >> > >> > FYI, there is a JIRA open for a scalable implementation of >> WindowedStorage >> > and WindowedKeyedStorage: >> > >> > https://issues.apache.org/jira/browse/APEXMALHAR-2130 >> > >> > We expect either to use ManagedState directly, or Spillable structures, >> > which in turn uses ManagedState. >> > >> > I'm not very familiar with the dedup operator. but in order to use the >> > WindowedOperator, it sounds to me that we can use SlidingWindows with an >> > implementation of WindowedKeyedStorage that uses a Bloom filter to cover >> > most of the false cases. >> > >> > David >> > >> > On Mon, Jul 4, 2016 at 4:42 AM, Bhupesh Chawda <bhup...@apache.org> >> wrote: >> > >> > > 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 >> > > >> > > >> > > >> > >> > > >> >> > > > >> > > > >> > > >> > >> > >
