Hi Deepak,

There are many open tickets for Flink's SQL API. Documentation is at
https://ci.apache.org/projects/flink/flink-docs-master/dev/table_api.html.

https://issues.apache.org/jira/issues/?jql=project%20%3D%20FLINK%20AND%20resolution%20%3D%20Unresolved%20AND%20component%20%3D%20%22Table%20API%20%26%20SQL%22%20ORDER%20BY%20priority%20DESC

Greg

On Wed, Sep 14, 2016 at 12:27 PM, Deepak Sharma <deepakmc...@gmail.com>
wrote:

> +1
> Yes.I agree to having SQL for Flink.
> I can take up some tasks as well once this starts.
>
> Thanks
> Deepak
>
> On Wed, Sep 14, 2016 at 3:47 PM, Radu Tudoran <radu.tudo...@huawei.com>
> wrote:
>
>> Hi,
>>
>>
>>
>> As a follow up to multiple discussions that happened during Flink Forward
>> about how SQL should be supported by Flink, I was thinking to make a couple
>> of proposals.
>>
>> Disclaimer: I do not claim I have managed to synthesized all the
>> discussions and probably a great deal of things are still missing
>>
>>
>>
>> *Why supporting SQL for Flink?*
>>
>> -          A goal to support SQL for Flink should be to enable larger
>> adoption of Flink – particularly for data scientists / data engineers who
>> might not want/know how to program against the existing APIs
>>
>> -          The main implication as I see from this is that SQL should
>> serve as a translation tool of the data processing processing flow to a
>> stream topology that will be executed by Flink
>>
>> -          This would require to support rather soon an SQL client for
>> Flink
>>
>>
>>
>> *How many features should be supported?*
>>
>> -          In order to enable a (close to ) full benefit of the
>> processing capabilities of Flink, I believe most of the processing types
>> should be supported – this includes all different types of windows,
>> aggregations, transformations, joins….
>>
>> -          I would propose that UDFs should also be supported such that
>> one can easily add more complex computation if needed
>>
>> -          In the spirit of the extensibility that Flink supports for
>> the operators, functions… such custom operators should be supported to
>> replace the default implementations of the SQL logical operators
>>
>>
>>
>> *How much customization should be enabled?*
>>
>> -          Regarding customization this could be provided by
>> configuration files. Such a configuration can cover the policies for how
>> the triggers, evictors, parallelization …  will be done for the specific
>> translation of the SQL query into Flink code
>>
>> -          In order to support the integration of custom operators for
>> specific SQL logical operators, the users should be enabled also to provide
>> translation RULES that will replace the default ones  (e.g. if a user want
>> to define their own CUSTOM_TABLE_SCAN, it should be able to provide
>> something like configuration.replaceRule(DataStreamScanRule.INSTANCE ,
>> CUSTOM_TABLE_SCAN_Rule.INSTANCE) – or if the selection of the new
>> translation rule can be handled from the cost than simply
>> configuration.addRule( CUSTOM_TABLE_SCAN_Rule.INSTANCE)
>>
>>
>>
>> What do you think?
>>
>>
>>
>>
>>
>> Dr. Radu Tudoran
>>
>> Senior Research Engineer - Big Data Expert
>>
>> IT R&D Division
>>
>>
>>
>> [image: cid:image007.jpg@01CD52EB.AD060EE0]
>>
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>>
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>>
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>>
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>
>
>
> --
> Thanks
> Deepak
> www.bigdatabig.com
> www.keosha.net
>

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