Hi Jark, let me answer your questions:
Q1: Yes, that's what I am currently thinking about. Q2: You can interpret a session id as a partitioning attribute. If you have OVER (PARTITION BY a, SessionWithGap(rowtime)), "a" would be a regular partitioning attribute and "SessionWithGap(rowtime)" would logically be the ID of the session a record belongs to. Within a partition you can still use ORDER BY, PRECEDING and FOLLOWING to define the records over which the aggregate of each row should be computed. Q3: My proposal focused on OVER windows for streaming tables. For batch tables, I would suggest to start as well from the SQL side and add the Table API as a second step. Of course, the batch side does not need to have as many restriction as streaming (although we can also start with many restrictions and extend features later). Q4: Yes, I think so. ProcessFunction might be the way to go (unless somebody has a better idea). This might be a bit of effort to implement but gives us a lot of flexibility when adding features such as retraction and configurable update rates. We have to think about the performance implication though. Better runtime abstractions for sorted state might be helpful. Best, Fabian 2017-01-24 6:53 GMT+01:00 Jark Wu <wuchong...@alibaba-inc.com>: > Hi Fabian, > > Thanks for bringing up this discussion and the nice approach to avoid > overlapping contributions. > > All of these make sense to me. But I have some questions. > > Q1: If I understand correctly, we will not support TumbleRows and > SessionRows at the beginning. But maybe support them as a syntax sugar (in > Table API) when the SlideRows is supported in the future. Right ? > > Q2: How to support SessionRows based on SlideRows ? I don't get how to > partition on "gap-separated". > > Q3: Should we break down the approach into smaller tasks for streaming > tables and batch tables ? > > Q4: The implementaion of SlideRows still need a custom operator that > collects records in a priority queue ordered by the "rowtime", which is > similar to the design we discussed in FLINK-4697, right? > > +1 not support for OVER ROW for event time at this point. > > Regards, Jark > > > > 在 2017年1月24日，上午10:28，Hongyuhong <hongyuh...@huawei.com> 写道： > > > > Hi, > > We are also interested in streaming sql and very willing to participate > and contribute. > > > > We are now in progress and we will also contribute to calcite to push > forward the window and stream-join support. > > > > > > > > -------------- > > Sender: Fabian Hueske [mailto:fhue...@gmail.com] > > Send Time: 2017年1月24日 5:55 > > Receiver: dev@flink.apache.org > > Theme: Re: [DISCUSS] Development of SQL OVER / Table API Row Windows for > streaming tables > > > > Hi Haohui, > > > > our plan was in fact to piggy-back on Calcite and use the TUMBLE > function [1] once is it is available (CALCITE-1345 [2]). > > Unfortunately, this issue does not seem to be very active, so I don't > know what the progress is. > > > > I would suggest to move the discussion about group windows to a separate > thread and keep this one focused on the organization of the SQL OVER > windows. > > > > Best, > > Fabian > > > > [1] http://calcite.apache.org/docs/stream.html) > > [2] https://issues.apache.org/jira/browse/CALCITE-1345 > > > > 2017-01-23 22:42 GMT+01:00 Haohui Mai <ricet...@gmail.com>: > > > >> Hi Fabian, > >> > >> FLINK-4692 has added the support for tumbling window and we are > >> excited to try it out and expose it as a SQL construct. > >> > >> Just curious -- what's your thought on the SQL syntax on tumbling > window? > >> > >> Implementation wise it might make sense to think tumbling window as a > >> special case of the sliding window. > >> > >> The problem I see is that the OVER construct might be insufficient to > >> support all the use cases of tumbling windows. For example, it fails > >> to express tumbling windows that have fractional time units (as > >> pointed out in http://calcite.apache.org/docs/stream.html). > >> > >> It looks to me that the Calcite / Azure Stream Analytics have > >> introduced a new construct (TUMBLE / TUMBLINGWINDOW) to address this > issue. > >> > >> Do you think it is a good idea to follow the same conventions? Your > >> ideas are appreciated. > >> > >> Regards, > >> Haohui > >> > >> > >> On Mon, Jan 23, 2017 at 1:02 PM Haohui Mai <ricet...@gmail.com> wrote: > >> > >>> +1 > >>> > >>> We are also quite interested in these features and would love to > >>> participate and contribute. > >>> > >>> ~Haohui > >>> > >>> On Mon, Jan 23, 2017 at 7:31 AM Fabian Hueske <fhue...@gmail.com> > wrote: > >>> > >>>> Hi everybody, > >>>> > >>>> it seems that currently several contributors are working on new > >>>> features for the streaming Table API / SQL around row windows (as > >>>> defined in > >>>> FLIP-11 > >>>> [1]) and SQL OVER-style window (FLINK-4678, FLINK-4679, FLINK-4680, > >>>> FLINK-5584). > >>>> Since these efforts overlap quite a bit I spent some time thinking > >>>> about how we can approach these features and how to avoid > >>>> overlapping contributions. > >>>> > >>>> The challenge here is the following. Some of the Table API row > >>>> windows > >> as > >>>> defined by FLIP-11 [1] are basically SQL OVER windows while other > >>>> cannot be easily expressed as such (TumbleRows for row-count > >>>> intervals, SessionRows). > >>>> However, since Calcite already supports SQL OVER windows, we can > >>>> reuse > >> the > >>>> optimization logic for some of the Table API row windows. I also > >>>> thought about the semantics of the TumbleRows and SessionRows > >>>> windows as defined in > >>>> FLIP-11 and came to the conclusion that these are not well defined > >>>> in > >>>> FLIP-11 and should rather be defined as SlideRows windows with a > >>>> special PARTITION BY clause. > >>>> > >>>> I propose to approach SQL OVER windows and Table API row windows as > >>>> follows: > >>>> > >>>> We start with three simple cases for SQL OVER windows (not Table > >>>> API > >> yet): > >>>> > >>>> * OVER RANGE for event time > >>>> * OVER RANGE for processing time > >>>> * OVER ROW for processing time > >>>> > >>>> All cases fulfill the following restrictions: > >>>> - All aggregations in SELECT must refer to the same window. > >>>> - PARTITION BY may not contain the rowtime attribute. > >>>> - ORDER BY must be on rowtime attribute (for event time) or on a > >>>> marker function that indicates processing time. Additional sort > >>>> attributes are not supported initially. > >>>> - only "BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW" and "BETWEEN x > >>>> PRECEDING AND CURRENT ROW" are supported. > >>>> > >>>> OVER ROW for event time cannot be easily supported. With event > >>>> time, we may have late records which need to be injected into the > >>>> order of records. > >>>> When > >>>> a record in injected in to the order where a row-count window has > >> already > >>>> been computed, this and all following windows will change. We could > >> either > >>>> drop the record or sent out many retraction records. I think it is > >>>> best > >> to > >>>> not open this can of worms at this point. > >>>> > >>>> The rational for all of the above restrictions is to have first > >>>> versions of OVER windows soon. > >>>> Once we have the above cases covered we can extend and remove > >> limitations > >>>> as follows: > >>>> > >>>> - Table API SlideRow windows (with the same restrictions as above). > >>>> This will be mostly API work since the execution part has been solved > before. > >>>> - Add support for FOLLOWING (except UNBOUNDED FOLLOWING) > >>>> - Add support for different windows in SELECT. All windows must be > >>>> partitioned and ordered in the same way. > >>>> - Add support for additional ORDER BY attributes (besides time). > >>>> > >>>> As I said before, TumbleRows and SessionRows windows as in FLIP-11 > >>>> are > >> not > >>>> well defined, IMO. > >>>> They can be expressed as SlideRows windows with special > >>>> partitioning (partitioning on fixed, non-overlapping time ranges > >>>> for TumbleRows, and gap-separated, non-overlapping time ranges for > >>>> SessionRows) I would not start to work on those yet. > >>>> > >>>> I would like to close all related JIRA issues (FLINK-4678, > >>>> FLINK-4679, FLINK-4680, FLINK-5584) and restructure the development > >>>> of these > >> features > >>>> as outlined above with corresponding JIRA issues. > >>>> > >>>> What do others think? (I cc'ed the contributors assigned to the > >>>> above > >> JIRA > >>>> issues) > >>>> > >>>> Best, Fabian > >>>> > >>>> [1] > >>>> > >>>> https://cwiki.apache.org/confluence/display/FLINK/FLIP- > >> 11%3A+Table+API+Stream+Aggregations > >>>> > >>> > >> > >
