P-11
> provides
> > a
> > > >> way
> > > >>>> to define such a query as a sliding row window with unbounded
> > > preceding
> > > >>>> rows. With the upcoming SQL proposal, queries that consume
> unbounded
> > > >> mem
gt; would
> > >>>> need to extend the parser quite a bit because windows would need to
> be
> > >>>> defined as Strings and not via objects.
> > >>>>
> > >>>> - RowWindows: The rowWindow() call mimics the standard SQL WINDOW
>
> think we can make the over() call mandatory to have the windowing more
> >>>> explicit. It should also be possible to extend the over clause to
> >> directly
> >>>> accept RowWindows instead of window aliases. I would not make this a
> >>>> prio
stion:
>>>> In FLIP-11, groupBy() is used to define the partitioning of RowWindows.
>>>> I think this should be changed to partitionBy() because groupBy() groups
>>>> data and applies an aggregation to all rows of a group which is not
>>>> happening here. In ori
er() for rowWindow() with a single window definition
> >> - additionally allowing window definitions in over()
> >> - using partitionBy() instead of groupBy() for row windows?
> >>
> >> Best, Fabian
> >>
> >> 2016-10-13 11:10 GMT+02:00 Zhangruc
vironment.getTableEnvironment(env)
>>> val ds: DataStream[(String,Long, Long)] = env.readTextFile("/home/demo")
>>> tblEnv.registerDataStream("Order", ds, 'userID, 'count, 'num)
>>> .map(f=>(f, 1L, 1L))
>>> val sql = tb
num)
>> .map(f=>(f, 1L, 1L))
>> val sql = tblEnv.sql("SELECT Stream * FROM Order WHERE userID='A'")
>>
>> So in my opinion, the grammar which is marked red should be compatible
>> with calcite's StreamSQL grammar.
>>
>> By the w
ue...@gmail.com]
发送时间: 2016年10月13日 18:17
收件人: dev@flink.apache.org
抄送: Sean Wang; Timo Walther
主题: Re: 答复: RE:[DISCUSS] FLIP-11: Table API Stream Aggregations
Hi Zhangrucong,
yes, we want to use Calcite's SQL parser including its window syntax, i.e.,
- the standard SQL OVER windows (i
Wang; Timo Walther
主题: Re: 答复: RE:[DISCUSS] FLIP-11: Table API Stream Aggregations
Hi Zhangrucong,
yes, we want to use Calcite's SQL parser including its window syntax, i.e.,
- the standard SQL OVER windows (in streaming with a few restriction such as no
different partitionings or orders)
quot;)
>>
>> So in my opinion, the grammar which is marked red should be compatible
>> with calcite's StreamSQL grammar.
>>
>> By the way, thanks very much for telling me the modified content in
>> Flink StreamSQL. I will look the new proposal .
>>
>> Thanks!
he grammar which is marked red should be compatible
> with calcite's StreamSQL grammar.
>
> By the way, thanks very much for telling me the modified content in Flink
> StreamSQL. I will look the new proposal .
>
> Thanks!
> 发件人: Sean Wang [mailto:wshaox...@gmail.com]
>
product AS (
ORDER BY rowtime
PARTITION BY productId))
Thanks!
-----邮件原件-----
发件人: 王绍翾(大沙)
[mailto:shaoxuan@alibaba-inc.com<mailto:shaoxuan@alibaba-inc.com>]
发送时间: 2016年10月13日 2:03
收件人: dev@flink.apache.org<mailto:dev@flink.apache.org>
主题: RE:[DISCUSS] FLIP-11: Ta
duct AS (
> ORDER BY rowtime
> PARTITION BY productId))
>
>
>
> Thanks!
>
> -邮件原件-
> 发件人: 王绍翾(大沙) [mailto:shaoxuan@alibaba-inc.com]
> 发送时间: 2016年10月13日 2:03
> 收件人: dev@flink.apache.org
> 主题: RE:[DISCUSS] FLIP-11: Table API Stream Aggregatio
TITION BY productId))
Thanks!
-邮件原件-
发件人: 王绍翾(大沙) [mailto:shaoxuan....@alibaba-inc.com]
发送时间: 2016年10月13日 2:03
收件人: dev@flink.apache.org
主题: RE:[DISCUSS] FLIP-11: Table API Stream Aggregations
Hi Fabian, Timo, and Jark.Thanks for kicking off this FLIP. This is a really
great and promising pr
-发件人:Fabian
Hueske 发送时间:2016年9月26日(星期一) 21:13收件人:dev@flink.apache.org
主 题:Re: [DISCUSS] FLIP-11: Table API Stream Aggregations
Hi everybody,
Timo proposed our FLIP-11 a bit more than three weeks ago.
I will update the status of the FLIP to accepted.
Thanks,
Fabian
2016-09-19 9:16 GMT
Hi everybody,
Timo proposed our FLIP-11 a bit more than three weeks ago.
I will update the status of the FLIP to accepted.
Thanks,
Fabian
2016-09-19 9:16 GMT+02:00 Timo Walther :
> Hi Jark,
>
> yes I think enough time has passed. We can start implementing the changes.
> What do you think Fabian
Hi Jark,
yes I think enough time has passed. We can start implementing the
changes. What do you think Fabian?
If there are no objections, I will create the subtasks in Jira today.
For FLIP-11/1 I already have implemented a prototype, I just have to do
some refactoring/documentation before op
Hi all,
It seems that there’s no objections to the window design. So could we open
subtasks to start working on it now ?
- Jark Wu
> 在 2016年9月7日,下午4:29,Jark Wu 写道:
>
> Hi Fabian,
>
> Thanks for sharing your ideas.
>
> They all make sense to me. Regarding to reassigning timestamp, I do no
Hi Fabian,
Thanks for sharing your ideas.
They all make sense to me. Regarding to reassigning timestamp, I do not have an
use case. I come up with this because DataStream has a TimestampAssigner :)
+1 for this FLIP.
- Jark Wu
> 在 2016年9月7日,下午2:59,Fabian Hueske 写道:
>
> Hi,
>
> thanks fo
Hi,
thanks for your comments and questions!
Actually, you are bringing up the points that Timo and I discussed the most
when designing the FLIP ;-)
- We also thought about the syntactic shortcut for running aggregates like
you proposed (table.groupBy(‘a).select(…)). Our motivation to not allow
th
Hi all,
I'm on vacation for about five days , sorry to have missed this great FLIP.
Yes, the non-windowed aggregates is a special case of row-window. And the
proposal looks really good. Can we have a simplified form for the special
case? Such as :
table.groupBy(‘a).rowWindow(SlideRows.unbound
Hi all,
I thought about the API of the FLIP again. If we allow the "systemtime"
attribute, we cannot implement a nice method chaining where the user can
define a "allowLateness" only on event time. So even if the user
expressed that "systemtime" is used we have to offer a "allowLateness"
meth
Hi Jark,
you had asked for non-windowed aggregates in the Table API a few times.
FLIP-11 proposes row-window aggregates which are a generalization of
running aggregates (SlideRow unboundedPreceding).
Can you have a look at the FLIP and give feedback whether this is what you
are looking for?
Impro
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