+1, very excited for this feature.

On Wed, Feb 25, 2026 at 2:53 PM huaxin gao <[email protected]> wrote:

> +1
>
> On Wed, Feb 25, 2026 at 2:47 PM Gengliang Wang <[email protected]> wrote:
>
>> Starting with my own +1.
>>
>> On Wed, Feb 25, 2026 at 2:44 PM Gengliang Wang <[email protected]> wrote:
>>
>>> Hi Spark devs,
>>>
>>> I'd like to call a vote on the SPIP*: DSV2 Enhanced Partition Stats
>>> Filtering.*
>>>
>>> *Summary:*
>>>
>>> The DataSource V2 (DSV2) framework does not currently provide full
>>> data-skipping capabilities comparable to Spark-native sources, primarily
>>> due to limitations in Catalyst expression evaluation.
>>>
>>> This SPIP bridges that gap to achieve partition-skipping parity. To
>>> support this, Spark will push new *PartitionPredicate* objects that
>>> encapsulate Catalyst partition filter expressions and the evaluation logic,
>>> allowing data sources to skip irrelevant partitions effectively.
>>>
>>> *Relevant Links:*
>>>
>>>    -
>>>
>>>    - *SPIP Doc:*
>>>    
>>> https://docs.google.com/document/d/17vcw411PxSRLWoK-BiLI56UiNdokLWtovF8JZUlDTOo/edit?usp=sharing
>>>    -
>>>
>>>    *Discuss Thread:*
>>>    https://lists.apache.org/thread/p2cwngj9bmtcbmyplds833s9lwts8bwc
>>>    -
>>>
>>>    *JIRA:* SPARK-55596
>>>    <https://issues.apache.org/jira/browse/SPARK-55596>
>>>    -
>>>
>>>    *POC PR:* PR 54459 <https://github.com/apache/spark/pull/54459>
>>>
>>> *The vote will be open for at least 72 hours. *Please vote:
>>>
>>> [ ] +1: Accept the proposal as an official SPIP
>>>
>>> [ ] +0
>>>
>>> [ ] -1: I don't think this is a good idea because ...
>>>
>>> Thanks,
>>> Gengliang Wang
>>>
>>>

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