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Since it is unanimously agreed that we should disable conversion between Timestmap and long in parameters and results of UDXs, in PR [1] we will disable it in blink planner. And we will add a release note in FLINK-14599 [2] of this incompatible modification.
Best Regards,Zhenghua Gao Hi,
+1 to disable it in 1.10. I think it's time to disable and correct the behavior now.
Also cc'ed user mailing list to have broader audiences.
Best, Jark
Hi,
+1 for disabling it in the Blink planner. Once FLIP-65 is implemented
and a UDX is registered with the new
TableEnvironment.createTemporaryFunction() we will also have the
possibility to be fully compliant with the new type system because we
can advertise a new UDF stack with new behavior.
Also the mentioned documentation page will be updated as part of FLIP-65.
Regards,
Timo
On 22.11.19 11:08, Jingsong Li wrote:
> +1 to disable, It is already introduced by new type system in TimestampType.
> I think it is time to update document too.
>
> Best,
> Jingsong Lee
>
> On Fri, Nov 22, 2019 at 6:05 PM Kurt Young <[hidden email]> wrote:
>
>> +1 to disable, we also need to highlight this in 1.10 release notes.
>>
>> Best,
>> Kurt
>>
>>
>> On Fri, Nov 22, 2019 at 5:56 PM Zhenghua Gao <[hidden email]> wrote:
>>
>>> Hi,
>>>
>>> I wanted to bring up the discuss of Disable conversion between TIMESTAMP
>>> and Long in parameters and results of UDXs.
>>>
>>> Since FLINK-12253[1] introduce the new TimestampType and conversion from
>>> and
>>> to long is not supported, the UDXs with Long parameters should not
>> receive
>>> TIMESTAMP fields and vice versa.
>>>
>>> The current situation is we use long as internal representation of
>>> TIMESTAMP, the legacy planner and blink planner DO NOT DISABLE this
>>> conversion. Now FLINK-14599[2] would introduce a new internal
>>> representation of TIMESTAMP and it's time to make a decision to DISABLE
>> it.
>>>
>>> In addition, our document[3] recommends UDXs users use long as
>>> representation of SQL_TIMESTAMP, which is obsolete too.
>>>
>>> Please let me know what you think!
>>>
>>> [1] https://issues.apache.org/jira/browse/FLINK-12253
>>> [2] https://issues.apache.org/jira/browse/FLINK-14599
>>> [3]
>>>
>>>
>> https://ci.apache.org/projects/flink/flink-docs-release-1.9/dev/table/udfs.html#best-practices-for-implementing-udfs
>>>
>>> *Best Regards,*
>>> *Zhenghua Gao*
>>>
>>
>
>
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