Hi Juho,
Yes, FLINK-4557 is an umbrella issue for windowed aggregations (both for
stream and batch) for the Table API (not including SQL).
The features are described in FLIP-11 [1]. Note, there is currently a
discussion about certain aspects of the proposed syntax [2].
There is a pull request for
Hi Fabian!
Is this the feature that will also add windowed aggregates to streaming SQL:
https://issues.apache.org/jira/browse/FLINK-4557 (Table API Stream
Aggregations)?
You wrote:
> However for the 1.2 release, it we plan to focus on the streaming
> Table API and Stream SQL to add support for w
If we want to have it in Stream SQL yes. Although we can also think about
extending the Calcite parser ourselves.
IMO, it makes sense to talk to them first, also to get more feedback on the
feature.
2016-06-17 13:18 GMT+02:00 Jark Wu :
> Hi Fabian,
>
> Yea, we can immediately start to work on no
Hi Fabian,
Yea, we can immediately start to work on non-windowed aggregates. But it seems
that Calcite’s StreamSQL doesn’t support non-windowed aggregates (also not
included in roadmap). So we may need to propose this function back to Calcite
community?
- Jark Wu
> 在 2016年6月17日，下午5:41，Fabi
Hi Jark Wu,
I agree about the non-windowed aggregates. If there are actual use cases
for this operator, we should definitely support it.
Since it does not depend on windows or time, we can immediately start to
work on it. In principle, it should be rather easy to implement.
However, we have to che
Hi Fabian,
There are a lot of our business are using non-windowed aggregations. And there
is a little difference between non-windowed aggregate and Row window operator,
as the later is bound to a certain window and emit the result of the N rows
preceding for every incoming row. However the form
Hi Jark,
thanks for sharing Blink's Streaming Table API. It seems to be close to the
DataStream API, while the Table API draft I shared is more similar to
Calcite's proposal.
You are right, the current draft does not include running (non-windowed)
aggregates. We were not sure how useful these are
Hi Fabian,
It’s great to hear that we are going to start it!
I’m glad to share our current Streaming Table API [1]. I find that that all
aggregation functions are scoped to the defined window in Flink Stream Table
API design [2] and Calcite StreamSQL desgin [3]. I’m thinking that do we need
Hi Jark,
wow, that's good news!
You are right, the streaming Table API is currently very limited. In the
last month's we changed the internal architecture and put everything on top
of Apache Calcite.
For the upcoming 1.1 release, we won't add new features to the Table API /
SQL. However for the 1.
Hi,
We have a great interest in the new Table API & SQL. In Alibaba, we have added
a lot of features (groupBy, agg, window, join, UDF …) to Streaming Table API
(base on Flink 1.0). Now, many jobs run on Table API in production environment.
But we want to keep pace with the community, and we hav
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