Thanks for your example, Maciej
I can explain more about the design.
> Let's have events.
> S1, id1, v1, 1
> S2, id1, v2, 1
>
> Nothing is happening as none of the streams have reached the watermark.
> Now let's add
> S2, id2, v2, 101
> This should trigger join for id1 because we have all the kno
ts.
stream, id, value, ts
S1, id1, v1, 1
S2, id1, v2, 1
For this events and internal join Flink will emit an event in the output stream:
id1, v1, v2, 1
Despite the fact the watermark for both streams is not reached.
Now similar situation for Event Time Temporal Join
SELECT id, value1, value2, t
Hello, Maciej
> I agree the watermark should pass on versioned table side, because
> this is the only way to know which version of record should be used.
> But if we mimics behaviour of interval join then main stream watermark
> could be skipped.
IIRC, rowtime interval join requires the watermark
essage is late or early. If we only
> use the watermark on versioned table side, we have no means to determine
> whether the event in the main stream is ready to emit.
>
> Best,
> Shengkai
>
> maverick 于2021年4月26日周一 上午2:31写道:
>>
>> Hi,
>> I'm curious why
curious why Event Time Temporal Join needs watermarks from both sides
> to
> perform join.
>
> Shouldn't watermark on versioned table side be enough to perform join ?
>
>
>
>
>
> --
> Sent from:
> http://apache-flink-user-mailing-list-archive.2336050.n4.nabble.com/
>
Hi,
I'm curious why Event Time Temporal Join needs watermarks from both sides to
perform join.
Shouldn't watermark on versioned table side be enough to perform join ?
--
Sent from: http://apache-flink-user-mailing-list-archive.2336050.n4.nabble.com/
NULL
> >
> > I'd like to run the following query on this schema -
> >
> > select sum(F.C0), D.C1, tumble_start(F.R, interval '1' second)
> > from F join D ON F.C1 = D.C1
> > group by D.C1, tumble(F.R, interval '1
wtime attributes must not be in the input rows of a regular join.
As a workaround you can cast the time attributes of input tables to
TIMESTAMP before."
My understanding reading the docs is that Time Temporal Join is
meant to solve this problem. So I model table D as the fol
ON F.C1 = D.C1
> group by D.C1, tumble(F.R, interval '1' second)
>
> However, I run into the following error while running the above query -
>
> "Rowtime attributes must not be in the input rows of a regular join. As a
> workaround you can cast the time attrib
und you can cast the time attributes of input tables to TIMESTAMP
before."
My understanding reading the docs is that Time Temporal Join is meant to
solve this problem. So I model table D as the following -
D:
|-- C0: BIGINT
|-- C1: STRING NOT NULL
|-- R: TIMESTAMP(3)
|-- WATERMARK
t...@gmail.com>> a écrit :
>> Hi, Eric
>>
>> Firstly FileSystemTableSource doe not implement LookupTableSource which
>> means we cannot directly lookup a Filesystem table.
>>
>> In FLINK-19830, we plan to support Processing-time temporal join any
>> table
eonard Xu a écrit :
>
>> Hi, Eric
>>
>> Firstly FileSystemTableSource doe not implement LookupTableSource which
>> means we cannot directly lookup a Filesystem table.
>>
>> In FLINK-19830, we plan to support Processing-time temporal join any
>> table/views by lookup
t directly lookup a Filesystem table.
>
> In FLINK-19830, we plan to support Processing-time temporal join any
> table/views by lookup the data in join operator state which scanned from the
> filesystem table, but as the issue described: join processing for left stream
> doesn'
écrit :
> Hi, Eric
>
> Firstly FileSystemTableSource doe not implement LookupTableSource which
> means we cannot directly lookup a Filesystem table.
>
> In FLINK-19830, we plan to support Processing-time temporal join any
> table/views by lookup the data in join operator sta
Hi, Eric
Firstly FileSystemTableSource doe not implement LookupTableSource which means
we cannot directly lookup a Filesystem table.
In FLINK-19830, we plan to support Processing-time temporal join any
table/views by lookup the data in join operator state which scanned from the
filesystem
nk 1.12.1 i read in the doc that Processing-time temporal
> join is supported for kv like join but when i try i get a:
>
> Exception in thread "main" org.apache.flink.table.api.TableException:
> Processing-time temporal join i
Hello
Working with flink 1.12.1 i read in the doc that Processing-time temporal
join is supported for kv like join but when i try i get a:
Exception in thread "main" org.apache.flink.table.api.TableException:
Processing-time temporal join is not supported yet.
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