Bhupesh, When using "Windows Operator", if you were using sliding time windows like you were originally thinking then you would have the correct dedup behavior with the example case you mentioned with the tuples isn't it? Can the sliding windows share state with each other?
Thanks On Thu, Jul 14, 2016 at 10:55 AM, Bhupesh Chawda <bhup...@apache.org> wrote: > Hi All, > > I also implemented a De-duplication operator using Windowed Operator. Now > we have two implementations, one with Managed state and another using > Windowed operator. Here are their details: > > 1. *With Managed State - * > - The operator is implemented using managed state as the storage for > buckets into which the tuples will be stored. > - *TimeBucketAssigner* is used to assign an incoming tuple to > different buckets based on the event time. It is also used to > identify > whether a particular tuple is expired and should be sent to the > expired > port / dropped. > - For managed state, the *ManagedTimeUnifiedStateImpl* implementation > is used which just requires the user to specify the event time > and a bucket > is automatically assigned based on that. The structure of the bucket > data > on storage is as follows: /operator_id /time_bucket > - An advantage of using Managed State approach is that we don't have > to assume the correlation of event time to the de-duplication key of > the > tuple. For example, if we get two tuples like: (K1, T1), and (K1, > T2), we > can still use ManagedStateImpl and conclude that these tuples are > duplicates based on the Key K1. > 2. *With Windowed Operator - * > - The operator uses the WindowedOperatorImpl as the base operator. > - Accumulation, for the deduper, basically amounts to storing a list > of tuples in the data storage. Every time we get a unique tuple, we > *accumulate* it in the list. > - Event windows are modeled using the *TimeWindow* option. Although > SlidingTimeWIndows seems to be intuitive for data buckets, it seems > to be > the costly option as the accumulation in this case is not just > an aggregate > value but a list of values in that bucket. > - Watermarks are not assumed to be sent from an input operator > (although it is okay if an upstream operator sends them). The > *fixedWatermark* feature is used to assume watermarks which are > relative to the window time. > - One of the issues I found with using WindowedOperator for Dedup is > that event time is tightly coupled with the de-duplication key. In > the > above example, (K1, T1), and (K1, T2) *might* be concluded as two > unique tuples since T1 and T2 may fall into two different time > buckets. > > Here are the PRs for both of them. > > - Using Managed State: https://github.com/apache/apex-malhar/pull/335 > - Using Windowed Operator: > https://github.com/apache/apex-malhar/pull/343 > > Please review them and suggest on the correct approach for the final > implementation which should be used to add other features like fault > tolerance, scalability, optimizations etc. > Thanks. > > ~ Bhupesh > > On Fri, Jul 8, 2016 at 11:30 PM, David Yan <da...@datatorrent.com> wrote: > > > No problem. > > > > By the way, I changed the method name to setFixedWatermark. And also, if > > you want to drop any tuples that are considered late, you need to set the > > allowed lateness to be 0. > > > > David > > > > On Fri, Jul 8, 2016 at 4:55 AM, Bhupesh Chawda <bhup...@apache.org> > wrote: > > > > > Thanks David. > > > I'll try to create an implementation for Deduper which uses > > > WindowedOperator. Will open a PR soon for review. > > > > > > ~ Bhupesh > > > > > > On Fri, Jul 8, 2016 at 2:23 AM, David Yan <da...@datatorrent.com> > wrote: > > > > > > > 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 > > > > >> > > >> > > > > > > >> > > >> > > > > > >> > > >> > > > > >> > > > > > > > >> > > > > > > > >> > > > > > > >> > > > > > >> > > > > > > > > > > > > > > > > > > > >
