Hi Timo,
I have some questions regarding your implementation:
" The timestamp (not an indicator anymore) becomes part of the physical row.
E.g.
long.cast(STRING) would require a materialization "
=> If we have this how are we going to make a difference between rowtime and
processtime? For supporting some queries/operators you only need to use these
time indications as markers to have something like below. If you do not get
access to any sort of unique markers to indicate these than we will have hard
time to support many implementations. What would be the option to support this
condition in your implementation
if(rowtime)
...
else if(proctime)
...some other implemenetation
"- Windows are only valid if they work on time indicators."
=> Does this mean we can no longer work with count windows? There are a lot of
queries where windows would be defined based on cardinality of elements.
-----Original Message-----
From: Timo Walther [mailto:twal...@apache.org]
Sent: Monday, March 20, 2017 10:08 AM
To: dev@flink.apache.org
Subject: Re: [DISCUSS] Table API / SQL indicators for event and processing time
Hi everyone,
for the last two weeks I worked on a solution for the time indicator issue. I
have implemented a prototype[1] which shows how we can express, track, and
access time in a consistent way for batch and stream tables.
Main changes of my current solution:
- Processing and rowtime time indicators can be named arbitrarily
- They can be defined as follows: stream.toTable(tEnv, 'long, 'int, 'string,
'proctime.proctime) or stream.toTable(tEnv, 'long.rowtime, 'int, 'string)
- In a streaming environment: if the "long" field is already defined in the
record, it will not be read by the runtime. "long" always represents the
timestamp of the row.
- In batch environment: "long" must be present in the record and will be read
by the runtime.
- The table definition looks equivalent in both batch and streaming (better
unification than current state)
- Internally row types are split up in a logical and a physical row type.
- The logical row type contains time indicators, the physical rowtime never
contains time indicators (the pure "long" will never be in a record)
- After validation and query decorrelation, a special time indicator converter
traverses the RelNodes and analyzes if the a time indicator is accessed or only
forwarded.
- An access to a time indicator means that we need to materialize the rowtime
using a ProcessFunction (not yet implemented). The timestamp (not an indicator
anymore) becomes part of the physical row. E.g.
long.cast(STRING) would require a materialization
- Forwarding of time indicators does not materialize the rowtime. It remains a
logical attribute. E.g. .select('long)
- Windows are only valid if they work on time indicators.
There are still a lot of open question that we can discuss and/or fix in future
PRs. For now it would be great if you could give some feedback about the
current implementation. With some exceptions my branch can be built
successfully.
Regards,
Timo
[1] https://github.com/twalthr/flink/tree/FLINK-5884
Am 02/03/17 um 07:22 schrieb jincheng sun:
> Hi,
> @Timo, thanks for your replay, and congratulations on your job.
> @Fibian, No matter what way to achieve, as long as when the table is
> generated or created, identity the field attributes, that is what we want.
> I think at this point we are on the same page. We can go ahead.
> And very glad to hear That: `the 'rowtime keyword would be removed`,
> which is a very important step for keeping Stream and Batch consistent.
>
> Best,
> SunJincheng
>
>
> 2017-03-01 17:24 GMT+08:00 Fabian Hueske <fhue...@gmail.com>:
>
>> Hi,
>>
>> @Xingcan
>> Yes that is right. It is not (easily) possible to change the
>> watermarks of a stream. All attributes which are used as event-time
>> timestamps must be aligned with these watermarks. This are only
>> attributes which are derived from the original rowtime attribute,
>> i.e., the one that was specified when the Table was created.
>>
>> @SunJincheng
>> Regarding your points:
>>
>> 1. Watermarks can only be generated for (almost) sorted attributes.
>> Since a stream has only one sort order and cannot be sorted before it
>> is converted into Table, there will be hardly a case where n > 1 is
>> possible. The only possibility I see are two attributes which are in
>> almost the same order but with a certain distance (think of orderDate
>> and shipDate, but values would always be 1 day apart). However, this
>> requirement is very limiting and to be honest, I don't see how
>> assigning different watermarks for different attributes would work reliably
>> in practice.
>> The ORDER BY clause in an OVER window can only be used because the
>> stream is already sorted on that attribute (that's also why it is
>> restricted to rowtime and proctime in streaming)
>>
>> 2. Since a stream can only have one sort order, we so far assumed
>> that streams would already have watermarks and timestamps assigned. I
>> think this is a fair assumption, because a stream can only have one
>> order and hence only one timestamped & watermarked attribute (except
>> for the corner case I discussed above). As Timo said, .rowtime would
>> only add an attribute which refers to the already assigned timestamp of a
>> row.
>>
>> 3. I completely agree that the difference between batch and streaming
>> should be overcome. This is actually the goal of Timo's work. So yes,
>> the 'rowtime keyword would be removed because any attribute can be
>> marked as event-time attribute (by calling 't.rowtime).
>>
>> Btw. A table source could still make the watermark configurable by
>> offering a respective interface. However, I'm not yet convinced that
>> this needs to be part of the Table API.
>>
>> What do you think?
>>
>> Best, Fabian
>>
>> 2017-03-01 7:55 GMT+01:00 jincheng sun <sunjincheng...@gmail.com>:
>>
>>> Hi,Fabian,
>>>
>>> Thanks for your attention to this discussion. Let me share some
>>> ideas about this. :)
>>>
>>> 1. Yes, the solution I have proposed can indeed be extended to
>>> support multi-watermarks. A single watermark is a special case of
>>> multiple watermarks (n = 1). I agree that for the realization of the
>>> simple, that
>> we
>>> currently only support single watermark. Our idea is consistent.
>>>
>>> BTW. I think even if we only use one attribute to generate
>>> watermark we also need to sort, because in OVER window(Event-time)
>>> we must know the exact data order, is that right?
>>>
>>> 2. I think our difference is how to register the watermark?
>>> Now we see two ways:
>>> A. t.rowtime;
>>> If I understand correctly, in the current design when we use
>>> the expression 'rowtime, The system defaults based on user data to
>>> export timestamps;
>>> B. registeredWatermarks ('t, waterMarkFunction1):
>>> We are explicitly registered to generate watermarks and
>>> extract timestamps in user-defined ways;
>>>
>>> These two ways are characterized by:
>>> Approach A: The system defaults to export the value of the t
>>> field as
>> a
>>> timestamp, which is simple for the system.
>>> Approach B: the user can develop the logic of the export
>>> timestamp,
>> for
>>> the user has been very flexible. For example: the field `t` is a
>>> complex field (value is:` xxx # 20170302111129 # yyy`), the user can
>>> press a certain logic export timestamp (20170302111129).
>>>
>>> So i tend to approach B. What do you think?
>>>
>>> 3. We are very concerned about the unity of Stream and Batch, such
>>> as
>> the
>>> current TableAPI:
>>> Batch:
>>> Table
>>> .window (Tumble over 2.rows on 'long as' w) //' long is the
>>> normal field
>>> .groupBy ('w)
>>> .select ('int.count)
>>>
>>> Stream:
>>> Table
>>> .window (Tumble over 5.milli on 'rowtime as' w) //' rowtime
>>> is the keyword
>>> .groupBy ('w)
>>> .select ('int.count)
>>>
>>> As mentioned above, the two example are event-time aggregation
>>> window, but the writing did not do the same way, batch we have a
>>> specific column, stream need 'rowtime keyword. I think we need to
>>> try to eliminate this difference. What do you think?
>>>
>>> In the current google doc I see `table.window (tumble over
>>> 1.hour on
>> 't
>>> as' w) .groupBy ('a,' w) .select ('w.start,' b.count)`, Does this
>>> mean
>> that
>>> in FLINK-5884 will remove the tableAPI 'rowtime keyword?
>>>
>>> So I am currently talking on the event-time in the SQL
>>> indicators, in
>> the
>>> table registered column attributes, does this mean that the batch
>>> and stream SQL in the writing and use of the same?
>>>
>>> Very appreciated for your feedback.
>>>
>>> Best,
>>> SunJincheng
>>>
>>> 2017-03-01 10:40 GMT+08:00 Xingcan Cui <xingc...@gmail.com>:
>>>
>>>> Hi all,
>>>>
>>>> I have a question about the designate time for `rowtime`. The
>>>> current design do this during the DataStream to Table conversion.
>>>> Does this
>> mean
>>>> that `rowtime` is only valid for the source streams and can not be
>>>> designated after a subquery? (That's why I considered using alias
>>>> to dynamically designate it in a SQL before)
>>>>
>>>> Best,
>>>> Xingcan
>>>>
>>>> On Wed, Mar 1, 2017 at 5:35 AM, Fabian Hueske <fhue...@gmail.com>
>> wrote:
>>>>> Hi Jincheng Sun,
>>>>>
>>>>> registering watermark functions for different attributes to allow
>> each
>>> of
>>>>> them to be used in a window is an interesting idea.
>>>>>
>>>>> However, watermarks only work well if the streaming data is
>>>>> (almost)
>> in
>>>>> timestamp order. Since it is not possible to sort a stream, all
>>>> attributes
>>>>> that would qualify as event-time attributes need to be in almost
>>>>> the
>>> same
>>>>> order. I think this limits the benefits of having multiple
>>>>> watermark functions quite significantly. But maybe you have a good
>>>>> use case
>> that
>>>> you
>>>>> can share where multiple event-time attributes would work well.
>>>>>
>>>>> So far our approach has been that a DataStream which is converted
>> into
>>> a
>>>>> Table has already timestamps and watermarks assigned. We also
>>>>> assumed
>>>> that
>>>>> a StreamTableSource would provide watermarks and timestamps and
>>> indicate
>>>>> the name of the attribute that carries the timestamp.
>>>>>
>>>>> @Stefano: That's great news. I'd suggest to open a pull request
>>>>> and
>>> have
>>>> a
>>>>> look at PR #3397 which handles the (partitioned) unbounded case.
>> Would
>>> be
>>>>> good to share some code between these approaches.
>>>>>
>>>>> Thanks, Fabian
>>>>>
>>>>> 2017-02-28 18:17 GMT+01:00 Stefano Bortoli <
>> stefano.bort...@huawei.com
>>>> :
>>>>>> Hi all,
>>>>>>
>>>>>> I have completed a first implementation that works for the SQL
>> query
>>>>>> SELECT a, SUM(b) OVER (PARTITION BY c ORDER BY a RANGE BETWEEN 2
>>>>>> PRECEDING) AS sumB FROM MyTable
>>>>>>
>>>>>> I have SUM, MAX, MIN, AVG, COUNT implemented but I could test it
>> just
>>>> on
>>>>>> simple queries such as the one above. Is there any specific case
>>>>>> I
>>>> should
>>>>>> be looking at?
>>>>>>
>>>>>> Regards,
>>>>>> Stefano
>>>>>>
>>>>>> -----Original Message-----
>>>>>> From: jincheng sun [mailto:sunjincheng...@gmail.com]
>>>>>> Sent: Tuesday, February 28, 2017 12:26 PM
>>>>>> To: dev@flink.apache.org
>>>>>> Subject: Re: [DISCUSS] Table API / SQL indicators for event and
>>>>> processing
>>>>>> time
>>>>>>
>>>>>> Hi everyone, thanks for sharing your thoughts. I really like
>>>>>> Timo’s proposal, and I have a few thoughts want to share.
>>>>>>
>>>>>> We want to keep the query same for batch and streaming. IMO.
>> “process
>>>>> time”
>>>>>> is something special to dataStream while it is not a well defined
>>> term
>>>>> for
>>>>>> batch query. So it is kind of free to create something new for
>>>>> processTime.
>>>>>> I think it is a good idea to add a proctime as a reserved keyword
>> for
>>>>> SQL.
>>>>>> Regarding to “event time”, it is well defined for batch query.
>>>>>> So
>>> IMO,
>>>>> we
>>>>>> should keep the way of defining a streaming window exactly same
>>>>>> as
>>>> batch
>>>>>> window. Therefore, the row for event time is nothing special, but
>>> just
>>>> a
>>>>>> normal column. The major difference between batch and stream is
>> that
>>> in
>>>>>> dataStream the event time column must be associated with a
>> watermark
>>>>>> function. I really like the way Timo proposed, that we can select
>> any
>>>>>> column as rowtime. But I think instead of just clarify a column
>>>>>> is
>> a
>>>>>> rowtime (actually I do not think we need this special rowtime
>>> keyword),
>>>>> it
>>>>>> is better to register/associate the waterMark function to this
>> column
>>>>> when
>>>>>> creating the table. For dataStream, we will validate a rowtime
>> column
>>>>> only
>>>>>> if it has been associated with the waterMark function. A
>>>>>> prototype
>>> code
>>>>> to
>>>>>> explain how it looks like is shown as below:
>>>>>>
>>>>>> TableAPI：
>>>>>> toTable(tEnv, 'a, 'b, 'c)
>>>>>> .registeredWatermarks('a, waterMarkFunction1)
>>>>>>
>>>>>> batchOrStreamTable
>>>>>> .window(Tumble over 5.milli on 'a as 'w)
>>>>>> .groupBy('w, 'b)
>>>>>> .select('b, 'a.count as cnt1, 'c.sum as cnt2)
>>>>>>
>>>>>> SQL：
>>>>>> addTable[(Int, String, Long)]("MyTable", 'a, 'b, 'c)
>>>>>> .registeredWatermarks('a, waterMarkFunction1)
>>>>>>
>>>>>> SELECT a, SUM(b) OVER (PARTITION BY c ORDER BY a RANGE
>>>>>> BETWEEN
>> 2
>>>>>> PRECEDING) AS sumB FROM MyTable
>>>>>>
>>>>>> What do you think ?
>>>>>>
>>>>>> 2017-02-22 23:44 GMT+08:00 Timo Walther <twal...@apache.org>:
>>>>>>
>>>>>>> Hi everyone,
>>>>>>>
>>>>>>> I have create an issue [1] to track the progress of this topic.
>>>>>>> I
>>>> have
>>>>>>> written a little design document [2] how we could implement the
>>>>>>> indicators and which parts have to be touched. I would suggest
>>>>>>> to implement a prototype, also to see what is possible and can
>>>>>>> be integrated both in Flink and Calcite. Feedback is welcome.
>>>>>>>
>>>>>>> Regards,
>>>>>>> Timo
>>>>>>>
>>>>>>> [1] https://issues.apache.org/jira/browse/FLINK-5884
>>>>>>> [2] https://docs.google.com/document/d/1JRXm09x_wKst6z6UXdCGF9tg
>>>>>>> F1ueOAsFiQwahR72vbc/edit?usp=sharing
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>> Am 21/02/17 um 15:06 schrieb Fabian Hueske:
>>>>>>>
>>>>>>> Hi Xingcan,
>>>>>>>> thanks for your thoughts.
>>>>>>>> In principle you are right that the monotone attribute property
>>>> would
>>>>>>>> be sufficient, however there are more aspects to consider than
>>> that.
>>>>>>>> Flink is a parallel stream processor engine which means that
>> data
>>> is
>>>>>>>> processed in separate processes and shuffle across them.
>>>>>>>> Maintaining a strict order when merging parallel streams would
>> be
>>>>>>>> prohibitively expensive.
>>>>>>>> Flink's watermark mechanism helps operators to deal with
>>>> out-of-order
>>>>>>>> data (due to out-of-order input or shuffles).
>>>>>>>> I don't think we can separate the discussion about time
>> attributes
>>>>>>>> from watermarks if we want to use Flink as a processing engine
>> and
>>>>>>>> not reimplement large parts from scratch.
>>>>>>>>
>>>>>>>> When transforming a time attribute, we have to either align it
>>> with
>>>>>>>> existing watermarks or generate new watermarks.
>>>>>>>> If we want to allow all kinds of monotone transformations, we
>> have
>>>> to
>>>>>>>> adapt the watermarks which is not trivial.
>>>>>>>> Instead, I think we should initially only allow very few
>> monotone
>>>>>>>> transformations which are aligned with the existing watermarks.
>> We
>>>>>>>> might later relax this condition if we see that users request
>> this
>>>>>> feature.
>>>>>>>> You are right, that we need to track which attribute can be
>>>>>>>> used
>>> as
>>>> a
>>>>>>>> time attribute (i.e., is increasing and guarded by watermarks).
>>>>>>>> For that we need to expose the time attribute when a Table is
>>>> created
>>>>>>>> (either when a DataStream is converted like:
>> stream.toTable(tEnv,
>>>> 'a,
>>>>>>>> 'b,
>>>>>>>> 't.rowtime) or in a StreamTableSource) and track how it is used
>> in
>>>>>>>> queries.
>>>>>>>> I am not sure if the monotone property would be the right
>>>>>>>> choice here, since data is only quasi-monotone and a monotone
>> annotation
>>>>>>>> might trigger some invalid optimizations which change the
>>> semantics
>>>> of
>>>>>> a query.
>>>>>>>> Right now, Calcite does not offer a quasi-monotone property (at
>>>> least
>>>>>>>> I haven't found it).
>>>>>>>>
>>>>>>>> Best, Fabian
>>>>>>>>
>>>>>>>>
>>>>>>>> 2017-02-21 4:41 GMT+01:00 Xingcan Cui <xingc...@gmail.com>:
>>>>>>>>
>>>>>>>> Hi all,
>>>>>>>>> As I said in another thread, the main difference between
>>>>>>>>> stream
>>> and
>>>>>>>>> table is that a stream is an ordered list while a table is an
>>>>>> unordered set.
>>>>>>>>> Without considering the out-of-order problem in practice,
>> whether
>>>>>>>>> event-time or processing-time can be just taken as a
>>> monotonically
>>>>>>>>> increasing field and that's why the given query[1] would work.
>> In
>>>>>>>>> other words, we must guarantee the "SELECT MAX(t22.rowtime)
>> ..."
>>>>>>>>> subquery returns a single value that can be retrieved from the
>>>>>>>>> cached dynamic table since it's dangerous to join two
>> un-windowed
>>>>>>>>> streams.
>>>>>>>>>
>>>>>>>>> Under this circumstance, I just consider adding a "monotonic
>>>>>>>>> hint"(INC or
>>>>>>>>> DEC) to the field of a (generalized) table (maybe using an
>>>>>>>>> annotation on the registerDataXX method) that can be used to
>>>>>>>>> indicate whether a field is monotonically increasing or
>>> decreasing.
>>>>>>>>> Then by taking rowtime as common (monotonically increasing)
>>> field,
>>>>>>>>> there are several benefits:
>>>>>>>>>
>>>>>>>>> 1) This can uniform the table and stream by importing total
>>>> ordering
>>>>>>>>> relation to an unordered set.
>>>>>>>>>
>>>>>>>>> 2) These fields can be modified arbitrarily as long as they
>> keep
>>>> the
>>>>>>>>> declared monotonic feature and the watermark problem does not
>>> exist
>>>>>>>>> any more.
>>>>>>>>>
>>>>>>>>> 3) The monotonic hint will be useful in the query optimization
>>>>> process.
>>>>>>>>> What do you think?
>>>>>>>>>
>>>>>>>>> Best,
>>>>>>>>> Xingcan
>>>>>>>>>
>>>>>>>>> [1]
>>>>>>>>> SELECT t1.amount, t2.rate FROM
>>>>>>>>> table1 AS t1,
>>>>>>>>> table2 AS t2
>>>>>>>>> WHERE
>>>>>>>>> t1.currency = t2.currency AND
>>>>>>>>> t2.rowtime = (
>>>>>>>>> SELECT MAX(t22.rowtime) FROM table2 AS
>>>>>>>>> t22
>>>>>>>>> AND t22.rowtime <= t1.rowtime)
>>>>>>>>>
>>>>>>>>> On Tue, Feb 21, 2017 at 2:52 AM, Fabian Hueske <
>>> fhue...@gmail.com>
>>>>>>>>> wrote:
>>>>>>>>>
>>>>>>>>> Hi everybody,
>>>>>>>>>> When Timo wrote to the Calcite mailing list, Julian Hyde
>> replied
>>>>>>>>>> and gave good advice and explained why a system attribute for
>>>>>>>>>> event-time would be
>>>>>>>>>>
>>>>>>>>> a
>>>>>>>>>
>>>>>>>>>> problem [1].
>>>>>>>>>> I thought about this and agree with Julian.
>>>>>>>>>>
>>>>>>>>>> Here is a document to describe the problem, constraints in
>> Flink
>>>>>>>>>> and a proposal how to handle processing time and event time
>>>>>>>>>> in Table API and
>>>>>>>>>>
>>>>>>>>> SQL:
>>>>>>>>>
>>>>>>>>>> ->
>>>>>>>>>> https://docs.google.com/document/d/1MDGViWA_
>>>>>>>>>>
>>>>>>>>> TCqpaVoWub7u_GY4PMFSbT8TuaNl-
>>>>>>>>>
>>>>>>>>>> EpbTHQ
>>>>>>>>>>
>>>>>>>>>> Please have a look, comment and ask questions.
>>>>>>>>>>
>>>>>>>>>> Thank you,
>>>>>>>>>> Fabian
>>>>>>>>>>
>>>>>>>>>> [1]
>>>>>>>>>> https://lists.apache.org/thread.html/
>>>> 6397caf0ca37f97f2cd27d96f7a12c
>>>>>>>>>> 6fa845d6fd0870214fdce18d96@%3Cdev.calcite.apache.org%3E
>>>>>>>>>>
>>>>>>>>>> 2017-02-16 1:18 GMT+01:00 Fabian Hueske <fhue...@gmail.com>:
>>>>>>>>>>
>>>>>>>>>> Thanks everybody for the comments.
>>>>>>>>>>> Actually, I think we do not have much choice when deciding
>>>> whether
>>>>>>>>>>> to
>>>>>>>>>>>
>>>>>>>>>> use
>>>>>>>>>> attributes or functions.
>>>>>>>>>>> Consider the following join query:
>>>>>>>>>>>
>>>>>>>>>>> SELECT t1.amount, t2.rate FROM
>>>>>>>>>>> table1 AS t1,
>>>>>>>>>>> table2 AS t2
>>>>>>>>>>> WHERE
>>>>>>>>>>> t1.currency = t2.currency AND
>>>>>>>>>>> t2.rowtime = (
>>>>>>>>>>> SELECT MAX(t22.rowtime) FROM table2 AS
>>>>>>>>>>> t22
>>>>>>>>>>> AND t22.rowtime <= t1.rowtime)
>>>>>>>>>>>
>>>>>>>>>>> The query joins two streaming tables. Table 1 is a streaming
>>>> table
>>>>>>>>>>> with amounts in a certain currency. Table 2 is a (slowly
>>>> changing)
>>>>>>>>>>> streaming table of currency exchange rates.
>>>>>>>>>>> We want to join the amounts stream with the exchange rate of
>>> the
>>>>>>>>>>> corresponding currency that is valid (i.e., last received
>> value
>>>> ->
>>>>>>>>>>> MAX(rowtime)) at the rowtime of the amounts row.
>>>>>>>>>>> In order to specify the query, we need to refer to the
>> rowtime
>>> of
>>>>>>>>>>> the different tables. Hence, we need a way to relate the
>>> rowtime
>>>>>>>>>>> expression
>>>>>>>>>>>
>>>>>>>>>> (or
>>>>>>>>>>
>>>>>>>>>>> marker) to a table.
>>>>>>>>>>> This is not possible with a parameterless scalar function.
>>>>>>>>>>>
>>>>>>>>>>> I'd like to comment on the concerns regarding the
>> performance:
>>>>>>>>>>> In fact, the columns could be completely virtual and only
>> exist
>>>>>>>>>>> during query parsing and validation.
>>>>>>>>>>> During execution, we can directly access the rowtime
>>>>>>>>>>> metadata
>>> of
>>>> a
>>>>>>>>>> Flink
>>>>>>>>>> streaming record (which is present anyway) or look up the
>>> current
>>>>>>>>>>> processing time from the machine clock. So the processing
>>>> overhead
>>>>>>>>>> would
>>>>>>>>>> actually be the same as with a marker function.
>>>>>>>>>>> Regarding the question on what should be allowed with a
>> system
>>>>>>>>>> attribute:
>>>>>>>>>> IMO, it could be used as any other attribute. We need it at
>>> least
>>>>>>>>>> in
>>>>>>>>>> GROUP
>>>>>>>>>>
>>>>>>>>>>> BY, ORDER BY, and WHERE to define windows and joins. We
>>>>>>>>>>> could
>>>> also
>>>>>>>>>> allow
>>>>>>>>>> to
>>>>>>>>>>
>>>>>>>>>>> access it in SELECT if we want users to give access to
>> rowtime
>>>> and
>>>>>>>>>>> processing time. So @Haohui, your query could be supported.
>>>>>>>>>>> However, what would not be allowed is to modify the value of
>>> the
>>>>>>>>>>> rows, i.e., by naming another column rowtime, i.e., "SELECT
>>>>>>>>>>> sometimestamp AS rowtime" would not be allowed, because
>>>>>>>>>>> Flink
>>>> does
>>>>>>>>>>> not support to modify
>>>>>>>>>>>
>>>>>>>>>> the
>>>>>>>>>>
>>>>>>>>>>> event time of a row (for good reasons) and processing time
>>> should
>>>>>>>>>>> not
>>>>>>>>>>>
>>>>>>>>>> be
>>>>>>>>>> modifiable anyway.
>>>>>>>>>>> @Timo:
>>>>>>>>>>> I think the approach to only use the system columns during
>>>> parsing
>>>>>>>>>>> and validation and converting them to expressions afterwards
>>>> makes
>>>>>>>>>>> a lot of sense.
>>>>>>>>>>> The question is how this approach could be nicely integrated
>>> with
>>>>>>>>>> Calcite.
>>>>>>>>>>
>>>>>>>>>>> Best, Fabian
>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>> 2017-02-15 16:50 GMT+01:00 Radu Tudoran <
>>> radu.tudo...@huawei.com
>>>>> :
>>>>>>>>>>> Hi,
>>>>>>>>>>>> My initial thought would be that it makes more sense to
>> thave
>>>>>>>>>>> procTime()
>>>>>>>>>> and rowTime() only as functions which in fact are to be used
>> as
>>>>>>>>>>> markers.
>>>>>>>>>> Having the value (even from special system attributes does
>>>>>>>>>> not
>>>> make
>>>>>>>>>>> sense
>>>>>>>>>>> in some scenario such as the ones for creating windows,
>>>>>>>>>>> e.g.,
>>>>>>>>>>>> If you have SELECT Count(*) OVER (ORDER BY procTime()...)
>>>>>>>>>>>> If
>>> you
>>>>>>>>>>>> get the value of procTime you cannot do anything as you
>>>>>>>>>>>> need
>>>>>>>>>>>>
>>>>>>>>>>> the
>>>>>>>>>> marker to know how to construct the window logic.
>>>>>>>>>>>> However, your final idea of having " implement some
>> rule/logic
>>>>>>>>>>>> that translates the attributes to special RexNodes
>> internally
>>> "
>>>> I
>>>>>>>>>>>> believe
>>>>>>>>>>>>
>>>>>>>>>>> is
>>>>>>>>>> good and gives a solution to both problems. One the one hand
>> for
>>>>>>>>>> those
>>>>>>>>>>>> scenarios where you need the value you can access the
>>>>>>>>>>>> value, while for others you can see the special type of the
>>>>>>>>>>>> RexNode
>>> and
>>>>>>>>>>>> use it as a
>>>>>>>>>>>>
>>>>>>>>>>> marker.
>>>>>>>>>>> Regarding keeping this data in a table...i am not sure as
>>>>>>>>>>> you would say
>>>>>>>>>> we need to augment the data with two fields whether needed
>>>>>>>>>> or
>>>>>>>>>>> not...this
>>>>>>>>>>> is nto necessary very efficient
>>>>>>>>>>>>
>>>>>>>>>>>> Dr. Radu Tudoran
>>>>>>>>>>>> Senior Research Engineer - Big Data Expert IT R&D Division
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>> HUAWEI TECHNOLOGIES Duesseldorf GmbH European Research
>>>>>>>>>>>> Center Riesstrasse 25, 80992 München
>>>>>>>>>>>>
>>>>>>>>>>>> E-mail: radu.tudo...@huawei.com
>>>>>>>>>>>> Mobile: +49 15209084330
>>>>>>>>>>>> Telephone: +49 891588344173
>>>>>>>>>>>>
>>>>>>>>>>>> HUAWEI TECHNOLOGIES Duesseldorf GmbH Hansaallee 205, 40549
>>>>>>>>>>>> Düsseldorf, Germany, www.huawei.com Registered Office:
>>>>>>>>>>>> Düsseldorf, Register Court Düsseldorf,
>> HRB
>>>>> 56063,
>>>>>>>>>>>> Managing Director: Bo PENG, Wanzhou MENG, Lifang CHEN Sitz
>>>>>>>>>>>> der Gesellschaft: Düsseldorf, Amtsgericht Düsseldorf,
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>>>>>> 56063,
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>>>>>>>>>>>> e-mail and its attachments contain confidential
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>>>>>> from
>>>>>>>>>>>> HUAWEI, which is intended only for the person or entity
>> whose
>>>>>> address
>>>>>>>>>>> is
>>>>>>>>>> listed above. Any use of the information contained herein in
>> any
>>>> way
>>>>>>>>>>>> (including, but not limited to, total or partial
>>>>>>>>>>>> disclosure,
>>>>>>>>>>>>
>>>>>>>>>>> reproduction,
>>>>>>>>>>> or dissemination) by persons other than the intended
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>>>>> is
>>>>>>>>>>>> prohibited. If you receive this e-mail in error, please
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>>>>>>>>>>> by phone or email immediately and delete it!
>>>>>>>>>>>> -----Original Message-----
>>>>>>>>>>>> From: Timo Walther [mailto:twal...@apache.org]
>>>>>>>>>>>> Sent: Wednesday, February 15, 2017 9:33 AM
>>>>>>>>>>>> To: dev@flink.apache.org
>>>>>>>>>>>> Subject: Re: [DISCUSS] Table API / SQL indicators for event
>>> and
>>>>>>>>>>>> processing time
>>>>>>>>>>>>
>>>>>>>>>>>> Hi all,
>>>>>>>>>>>>
>>>>>>>>>>>> at first I also thought that built-in functions (rowtime()
>> and
>>>>>>>>>>>> proctime()) are the easiest solution. However, I think to
>>>>>>>>>>>> be
>>>>>>>>>>>>
>>>>>>>>>>> future-proof
>>>>>>>>>>> we should make them system attributes; esp. to relate them
>> to a
>>>>>>>>>>>> corresponding table in case of multiple tables. Logically
>> they
>>>> are
>>>>>>>>>>>> attributes of each row, which is already done in Table API.
>>>>>>>>>>>>
>>>>>>>>>>>> I will ask on the Calcite ML if there is a good way for
>>>>> integrating
>>>>>>>>>>>> system attributes. Right now, I would propose the following
>>>>>>>>>>>>
>>>>>>>>>>> implementation:
>>>>>>>>>>> - we introduce a custom row type (extending RelDataType)
>>>>>>>>>>>> - in a streaming environment every row has two attributes
>>>>>>>>>>>> by
>>>>> default
>>>>>>>>>>>> (rowtime and proctime)
>>>>>>>>>>>> - we do not allow creating a row type with those attributes
>>>> (this
>>>>>>>>>>> should
>>>>>>>>>> already prevent `SELECT field AS rowtime FROM ...`)
>>>>>>>>>>>> - we need to ensure that these attributes are not part of
>>>>> expansion
>>>>>>>>>>> like
>>>>>>>>>> `SELECT * FROM ...`
>>>>>>>>>>>> - implement some rule/logic that translates the attributes
>> to
>>>>>> special
>>>>>>>>>>>> RexNodes internally, such that the opimizer does not modify
>>>> these
>>>>>>>>>>> attributes
>>>>>>>>>>> What do you think?
>>>>>>>>>>>> Regards,
>>>>>>>>>>>> Timo
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>> Am 15/02/17 um 03:36 schrieb Xingcan Cui:
>>>>>>>>>>>>
>>>>>>>>>>>>> Hi all,
>>>>>>>>>>>>>
>>>>>>>>>>>>> thanks for this thread.
>>>>>>>>>>>>>
>>>>>>>>>>>>> @Fabian If I didn't miss the point, the main difference
>>> between
>>>>> the
>>>>>>>>>>>>> two approaches is whether or not taking these time
>> attributes
>>>> as
>>>>>>>>>>>>> common table fields that are directly available to users.
>>>>> Whatever,
>>>>>>>>>>>>> these time attributes should be attached to records
>> (right?),
>>>> and
>>>>>>>>>>>> the
>>>>>>>>>> discussion lies in whether give them public qualifiers like
>>> other
>>>>>>>>>>>>> common fields or private qualifiers and related get/set
>>>> methods.
>>>>>>>>>>>>> The former (system attributes) approach will be more
>>> compatible
>>>>>> with
>>>>>>>>>>>>> existing SQL read-only operations (e.g., select, join),
>>>>>>>>>>>>> but
>>> we
>>>>> need
>>>>>>>>>>>> to
>>>>>>>>>> add restrictions on SQL modification operation (like what?).
>>>>>>>>>> I
>>>> think
>>>>>>>>>>>>> there are no needs to forbid users modifying these
>> attributes
>>>> via
>>>>>>>>>>>>> table APIs (like map function). Just inform them about
>> these
>>>>>> special
>>>>>>>>>>>>> attribute names like system built in aggregator names in
>>>>> iteration.
>>>>>>>>>>>>> As for the built in function approach, I don't know if,
>>>>>>>>>>>>> for
>>>> now,
>>>>>>>>>>>> there
>>>>>>>>>> are functions applied on a single row (maybe the value access
>>>>>>>>>>>>> functions like COMPOSITE.get(STRING)?). It seems that most
>> of
>>>> the
>>>>>>>>>>>>> built in functions work for a single field or on columns
>> and
>>>> thus
>>>>>> it
>>>>>>>>>>>>> will be mountains of work if we want to add a new kind of
>>>>> function
>>>>>>>>>>>> to
>>>>>>>>>> SQL. Maybe all existing operations should be modified to
>> support
>>>> it.
>>>>>>>>>>>>> All in all, if there are existing supports for single row
>>>>> function,
>>>>>>>>>>>> I
>>>>>>>>>> prefer the built in function approach. Otherwise the system
>>>>>>>>>>>> attributes
>>>>>>>>>> approach should be better. After all there are not so much
>>>>>>>>>>>>> modification operations in SQL and maybe we can use alias
>> to
>>>>>> support
>>>>>>>>>>>>> time attributes setting (just hypothesis, not sure if it's
>>>>>>>>>>>>>
>>>>>>>>>>>> feasible).
>>>>>>>>>> @Haohui I think the given query is valid if we add a
>>>>>>>>>> aggregate
>>>>>>>>>>>>> function to (PROCTIME()
>>>>>>>>>>>>> - ROWTIME()) / 1000 and it should be executed efficiently.
>>>>>>>>>>>>>
>>>>>>>>>>>>> Best,
>>>>>>>>>>>>> Xingcan
>>>>>>>>>>>>>
>>>>>>>>>>>>> On Wed, Feb 15, 2017 at 6:17 AM, Haohui Mai <
>>>> ricet...@gmail.com>
>>>>>>>>>>>> wrote:
>>>>>>>>>>> Hi,
>>>>>>>>>>>>>> Thanks for starting the discussion. I can see there are
>>>> multiple
>>>>>>>>>>>>>> trade-offs in these two approaches. One question I have
>>>>>>>>>>>>>> is
>>>> that
>>>>> to
>>>>>>>>>>>>>> which extent Flink wants to open its APIs to allow users
>> to
>>>>> access
>>>>>>>>>>>>>> both processing and event time.
>>>>>>>>>>>>>>
>>>>>>>>>>>>>> Before we talk about joins, my understanding for the two
>>>>>> approaches
>>>>>>>>>>>>>> that you mentioned are essentially (1) treating the value
>> of
>>>>> event
>>>>>>>>>>>>> /
>>>>>>>>>> processing time as first-class fields for each row, (2)
>> limiting
>>>>>>>>>>>>> the
>>>>>>>>>> scope of time indicators to only specifying windows. Take the
>>>>>>>>>>>>>> following query as an
>>>>>>>>>>>>>> example:
>>>>>>>>>>>>>>
>>>>>>>>>>>>>> SELECT (PROCTIME() - ROWTIME()) / 1000 AS latency FROM
>> table
>>>>> GROUP
>>>>>>>>>>>>> BY
>>>>>>>>>> FLOOR(PROCTIME() TO MINUTES)
>>>>>>>>>>>>>> There are several questions we can ask:
>>>>>>>>>>>>>>
>>>>>>>>>>>>>> (1) Is it a valid query?
>>>>>>>>>>>>>> (2) How efficient the query will be?
>>>>>>>>>>>>>>
>>>>>>>>>>>>>> For this query I can see arguments from both sides. I
>> think
>>> at
>>>>> the
>>>>>>>>>>>>>> end of the day it really comes down to what Flink wants
>>>>>>>>>>>>>> to
>>>>>> support.
>>>>>>>>>>>>>> After working on FLINK-5624 I'm more inclined to support
>> the
>>>>>> second
>>>>>>>>>>>>>> approach (i.e., built-in functions). The main reason why
>> is
>>>> that
>>>>>>>>>>>>> the
>>>>>>>>>> APIs of Flink are designed to separate times from the real
>>>>>>>>>>>>> payloads.
>>>>>>>>>> It probably makes sense for the Table / SQL APIs to have the
>>> same
>>>>>>>>>>>>> designs.
>>>>>>>>>>>>> For joins I don't have a clear answer on top of my head.
>>> Flink
>>>>>>>>>>>>>> requires two streams to be put in the same window before
>>> doing
>>>>> the
>>>>>>>>>>>>>> joins. This is essentially a subset of what SQL can
>>> express. I
>>>>>>>>>>>>> don't
>>>>>>>>>> know what would be the best approach here.
>>>>>>>>>>>>>> Regards,
>>>>>>>>>>>>>> Haohui
>>>>>>>>>>>>>>
>>>>>>>>>>>>>>
>>>>>>>>>>>>>> On Tue, Feb 14, 2017 at 12:26 AM Fabian Hueske <
>>>>> fhue...@gmail.com
>>>>>>>>>>>>> wrote:
>>>>>>>>>>>>> Hi,
>>>>>>>>>>>>>>> It would as in the query I gave as an example before:
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>> SELECT
>>>>>>>>>>>>>>> a,
>>>>>>>>>>>>>>> SUM(b) OVER (PARTITION BY c ORDER BY proctime ROWS
>>>> BETWEEN
>>>>> 2
>>>>>>>>>>>>>>> PRECEDING AND CURRENT ROW) AS sumB, FROM myStream
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>> Here "proctime" would be a system attribute of the table
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>> "myStream".
>>>>>>>>>> The table would also have another system attribute called
>>>>>>>>>>>>>> "rowtime"
>>>>>>>>>> which would be used to indicate event time semantics.
>>>>>>>>>>>>>>> These attributes would always be present in tables which
>>> are
>>>>>>>>>>>>>> derived
>>>>>>>>>> from streams.
>>>>>>>>>>>>>>> Because we still require that streams have timestamps
>>>>>>>>>>>>>>> and
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>> watermarks
>>>>>>>>>> assigned (either by the StreamTableSource or the somewhere
>>>>>>>>>>>>>>> downstream the DataStream program) when they are
>> converted
>>>>> into a
>>>>>>>>>>>>>>> table, there is no
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>> need
>>>>>>>>>>>>>>
>>>>>>>>>>>>>>> to register anything.
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>> Does that answer your questions?
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>> Best, Fabian
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>> 2017-02-14 2:04 GMT+01:00 Radu Tudoran <
>>>>> radu.tudo...@huawei.com
>>>>>>> :
>>>>>>>>>>>>>>> Hi Fabian,
>>>>>>>>>>>>>>>> Thanks for starting the discussion. Before I give my
>>>> thoughts
>>>>> on
>>>>>>>>>>>>>>>> this
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>> can
>>>>>>>>>>>>>>> you please give some examples of how would you see
>>>>>>>>>>>>>>> option
>>> of
>>>>>>>>>>>>>>> using
>>>>>>>>>> "system
>>>>>>>>>>>>>>>> attributes"?
>>>>>>>>>>>>>>>> Do you use this when you register the stream as a
>>>>>>>>>>>>>>>> table,
>>> do
>>>>> you
>>>>>>>>>>>>>>> use
>>>>>>>>>> if when you call an SQL query, do you use it when you
>> translate
>>>>>>>>>>>>>>>> back a
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>> table
>>>>>>>>>>>>>>> to a stream / write it to a dynamic table?
>>>>>>>>>>>>>>>> Dr. Radu Tudoran
>>>>>>>>>>>>>>>> Senior Research Engineer - Big Data Expert IT R&D
>> Division
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>> HUAWEI TECHNOLOGIES Duesseldorf GmbH European Research
>>>>>>>>>>>>>>>> Center Riesstrasse 25, 80992 München
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>> E-mail: radu.tudo...@huawei.com
>>>>>>>>>>>>>>>> Mobile: +49 15209084330 <+49%201520%209084330>
>>>>>>>>>>>>>>>> Telephone: +49 891588344173 <+49%2089%201588344173>
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>> HUAWEI TECHNOLOGIES Duesseldorf GmbH Hansaallee 205,
>>>>>>>>>>>>>>>> 40549 Düsseldorf, Germany,
>> www.huawei.com
>>>>>>>>>>>>>>>> Registered Office: Düsseldorf, Register Court
>> Düsseldorf,
>>>> HRB
>>>>>>>>>>>>>>> 56063,
>>>>>>>>>>> Managing Director: Bo PENG, Wanzhou MENG, Lifang CHEN
>>>>>>>>>>>>>>>> Sitz der Gesellschaft: Düsseldorf, Amtsgericht
>> Düsseldorf,
>>>> HRB
>>>>>>>>>>>>>>> 56063,
>>>>>>>>>>> Geschäftsführer: Bo PENG, Wanzhou MENG, Lifang CHEN
>>>>>>>>>>>>>>>> This e-mail and its attachments contain confidential
>>>>> information
>>>>>>>>>>>>>>> from
>>>>>>>>>>> HUAWEI, which is intended only for the person or entity
>>>>>>>>>>> whose
>>>>>>>>>>>>>>> address
>>>>>>>>>>> is
>>>>>>>>>>>>>>> listed above. Any use of the information contained
>>>>>>>>>>>>>>> herein
>>> in
>>>>> any
>>>>>>>>>>>>>>> way
>>>>>>>>>>> (including, but not limited to, total or partial disclosure,
>>>>>>>>>>>>>>> reproduction,
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>> or dissemination) by persons other than the intended
>>>>>> recipient(s)
>>>>>>>>>>>>>>> is
>>>>>>>>>>> prohibited. If you receive this e-mail in error, please
>> notify
>>>>>>>>>>>>>>> the
>>>>>>>>>> sender
>>>>>>>>>>>>>>> by phone or email immediately and delete it!
>>>>>>>>>>>>>>>> -----Original Message-----
>>>>>>>>>>>>>>>> From: Fabian Hueske [mailto:fhue...@gmail.com]
>>>>>>>>>>>>>>>> Sent: Tuesday, February 14, 2017 1:01 AM
>>>>>>>>>>>>>>>> To: dev@flink.apache.org
>>>>>>>>>>>>>>>> Subject: [DISCUSS] Table API / SQL indicators for event
>>> and
>>>>>>>>>>>>>>> processing
>>>>>>>>>>>>> time
>>>>>>>>>>>>>>>> Hi,
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>> I'd like to start an discussion about how Table API /
>> SQL
>>>>>> queries
>>>>>>>>>>>>>>> indicate
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>> whether an operation is done in event or processing
>> time.
>>>>>>>>>>>>>>>> 1) Why do we need to indicate the time mode?
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>> We need to distinguish event time and processing time
>> mode
>>>> for
>>>>>>>>>>>>>>> operations
>>>>>>>>>>>>>>> in queries in order to have the semantics of a query
>> fully
>>>>>>>>>>>>>>> defined.
>>>>>>>>>> This cannot be globally done in the TableEnvironment because
>>> some
>>>>>>>>>>>>>>> queries
>>>>>>>>>>>>>>> explicitly request an expression such as the ORDER BY
>>> clause
>>>> of
>>>>>>>>>>>>>>> an
>>>>>>>>>> OVER
>>>>>>>>>>>>> window with PRECEDING / FOLLOWING clauses.
>>>>>>>>>>>>>>>> So we need a way to specify something like the
>>>>>>>>>>>>>>>> following
>>>>> query:
>>>>>>>>>>>>>>>> SELECT
>>>>>>>>>>>>>>>> a,
>>>>>>>>>>>>>>>> SUM(b) OVER (PARTITION BY c ORDER BY proctime ROWS
>>>>> BETWEEN 2
>>>>>>>>>>>>>>> PRECEDING
>>>>>>>>>>>>>>> AND CURRENT ROW) AS sumB, FROM myStream
>>>>>>>>>>>>>>>> where "proctime" indicates processing time.
>>>>>>>>>>>>>>>> Equivalently
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>> "rowtime"
>>>>>>>>>> would
>>>>>>>>>>>>>>> indicate event time.
>>>>>>>>>>>>>>>> 2) Current state
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>> The current master branch implements time support only
>> for
>>>>>>>>>>>>>>> grouping
>>>>>>>>>> windows in the Table API.
>>>>>>>>>>>>>>>> Internally, the Table API converts a 'rowtime symbol
>>> (which
>>>>>> looks
>>>>>>>>>>>>>>> like
>>>>>>>>>>>>> a
>>>>>>>>>>>>>>> regular attribute) into a special expression which
>>> indicates
>>>>>>>>>>>>>>> event-time.
>>>>>>>>>>>>>>> For example:
>>>>>>>>>>>>>>>> table
>>>>>>>>>>>>>>>> .window(Tumble over 5.milli on 'rowtime as 'w)
>>>>>>>>>>>>>>>> .groupBy('a, 'w)
>>>>>>>>>>>>>>>> .select(...)
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>> defines a tumbling event-time window.
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>> Processing-time is indicated by omitting a time
>> attribute
>>>>>>>>>>>>>>>> (table.window(Tumble over 5.milli as 'w) ).
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>> 3) How can we do that in SQL?
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>> In SQL we cannot add special expressions without
>> touching
>>>> the
>>>>>>>>>>>>>>> parser
>>>>>>>>>>> which
>>>>>>>>>>>>>>>> we don't want to do because we want to stick to the SQL
>>>>>> standard.
>>>>>>>>>>>>>>>> Therefore, I see only two options: adding system
>>> attributes
>>>> or
>>>>>>>>>>>>>>>> (parameterless) built-in functions. I list some pros
>>>>>>>>>>>>>>>> and
>>>> cons
>>>>> of
>>>>>>>>>>>>>>> the
>>>>>>>>>>> approaches below:
>>>>>>>>>>>>>>>> 1. System Attributes:
>>>>>>>>>>>>>>>> + most natural way to access a property of a record.
>>>>>>>>>>>>>>>> + works with joins, because time attributes can be
>> related
>>>> to
>>>>>>>>>>>>>>> tables
>>>>>>>>>>> - We need to ensure the attributes are not writable and
>> always
>>>>>>>>>>>>>>> present
>>>>>>>>>>>>> in
>>>>>>>>>>>>>>> streaming tables (i.e., they should be system defined
>>>>>>>>>>>>>>> attributes).
>>>>>>>>>> - Need to adapt existing Table API expressions (will not
>> change
>>>>>>>>>>>>>>> the
>>>>>>>>>> API
>>>>>>>>>>>>> but some parts of the internal translation)
>>>>>>>>>>>>>>>> - Event time value must be set when the stream is
>>> converted,
>>>>>>>>>>>>>>> processing
>>>>>>>>>>>>> time is evaluated on the fly
>>>>>>>>>>>>>>>> 2. Built-in Functions
>>>>>>>>>>>>>>>> + Users could try to modify time attributes which is
>>>>>>>>>>>>>>>> + not
>>>>>> possible
>>>>>>>>>>>>>>> with
>>>>>>>>>>>>> functions
>>>>>>>>>>>>>>>> - do not work with joins, because we need to address
>>>> different
>>>>>>>>>>>>>>> relations
>>>>>>>>>>>>>>> - not a natural way to access a property of a record
>>>>>>>>>>>>>>>> I think the only viable choice are system attributes,
>>>> because
>>>>>>>>>>>>>>> built-in
>>>>>>>>>>>>> functions cannot be used for joins.
>>>>>>>>>>>>>>>> However, system attributes are the more complex
>>>>>>>>>>>>>>>> solution
>>>>> because
>>>>>>>>>>>>>>> they
>>>>>>>>>>> need
>>>>>>>>>>>>>>>> a better integration with Calcite's SQL validator
>>>> (preventing
>>>>>>>>>>>>>>> user
>>>>>>>>>> attributes which are named rowtime for instance).
>>>>>>>>>>>>>>>> Since there are currently a several contributions on
>>>>>>>>>>>>>>>> the
>>> way
>>>>>>>>>>>>>>> (such
>>>>>>>>>> as
>>>>>>>>>>
>>>>>>>>>>> SQL
>>>>>>>>>>>>>>> OVER windows FLINK-5653 to FLINK-5658) that need time
>>>>> indicators,
>>>>>>>>>>>>>>> we
>>>>>>>>>>> need a
>>>>>>>>>>>>>>>> solution soon to be able to make progress.
>>>>>>>>>>>>>>>> There are two PRs, #3252 and #3271, which implement the
>>>>> built-in
>>>>>>>>>>>>>>> marker
>>>>>>>>>>>>> functions proctime() and rowtime() and which could serve
>> as a
>>>>>>>>>>>>>>> temporary
>>>>>>>>>>>>> solution (since we do not work on joins yet).
>>>>>>>>>>>>>>>> I would like to suggest to use these functions as a
>>> starting
>>>>>>>>>>>>>>> point
>>>>>>>>>> (once
>>>>>>>>>>>>>>> the PRs are merged) and later change to the system
>>> attribute
>>>>>>>>>>>>>>> solution
>>>>>>>>>>> which
>>>>>>>>>>>>>>>> needs a bit more time to be implemented.
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>> I talked with Timo today about this issue and he said
>>>>>>>>>>>>>>>> he
>>>> would
>>>>>>>>>>>>>>> like
>>>>>>>>>> to
>>>>>>>>>>>>> investigate how we can implement this as system functions
>>>>>>>>>>>>>>> properly
>>>>>>>>>> integrated with Calcite and the SQL Validator.
>>>>>>>>>>>>>>>> What do others think?
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>> Best, Fabian
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>>
