Great, thanks for the explanation. I noticed now indeed that the examples are for the table API. I believe over window is sufficient for the purpose right now, was just curious.
Best, Stefano From: Fabian Hueske [mailto:fhue...@gmail.com] Sent: Tuesday, October 17, 2017 9:24 PM To: Stefano Bortoli <stefano.bort...@huawei.com> Cc: user@flink.apache.org Subject: Re: GROUP BY TUMBLE on ROW range Hi Stefano, this is not supported in Flink's SQL and we would need new Group Window functions (like TUMBLE) for this. A TUMBLE_COUNT function would be somewhat similar to SESSION, which also requires checks on the sorted neighboring rows to identify the window of a row. Such a function would first need to be added to Calcite and then integrated with Flink. A tumble count could also be expressed in plain SQL but wouldn't be very intuitive. You would have to - define an over window (maybe partitioned on some key) sorted on time with a ROW_NUMBER function that assigns increasing numbers to rows. - do a group by on the row number modulo the window size. Btw. count windows are supported by the Table API. Best, Fabian 2017-10-17 17:16 GMT+02:00 Stefano Bortoli <stefano.bort...@huawei.com<mailto:stefano.bort...@huawei.com>>: Hi all, Is there a way to use a tumble window group by with row range in streamSQL? I mean, something like this: // "SELECT COUNT(*) " + // "FROM T1 " + // "GROUP BY TUMBLE(rowtime, INTERVAL '2' ROWS PRECEDING )" However, even looking at tests and looking at the “row interval expression generation” I could not find any examples in SQL. I know it is supported by the stream APIs, and countWindow is the chosen abstraction. table .window(Tumble over 2.rows on 'long as 'w) .groupBy('w) .select('int.count) .toDataSet[Row] I fear I am missing something simple. Thanks a lot for the support guys! Best, Stefano
