Hi,I gather from the replies that the plugin is not currently available in
the form expected although I am aware of the shell script.

Also have you got some benchmark results from your tests that you can
possibly share?

Thanks,

Mich Talebzadeh,
Dad | Technologist | Solutions Architect | Engineer
London
United Kingdom


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*Disclaimer:* The information provided is correct to the best of my
knowledge, sourced from both personal expertise and other resources but of
course cannot be guaranteed . It is essential to note that, as with any
advice, one verified and tested result holds more weight than a thousand
expert opinions.


On Thu, 15 Feb 2024 at 01:18, Chao Sun <sunc...@apache.org> wrote:

> Hi Praveen,
>
> We will add a "Getting Started" section in the README soon, but basically
> comet-spark-shell
> <https://github.com/apache/arrow-datafusion-comet/blob/main/bin/comet-spark-shell>
>  in
> the repo should provide a basic tool to build Comet and launch a Spark
> shell with it.
>
> Note that we haven't open sourced several features yet including shuffle
> support, which the aggregate operation depends on. Please stay tuned!
>
> Chao
>
>
> On Wed, Feb 14, 2024 at 2:44 PM praveen sinha <praveen.si...@gmail.com>
> wrote:
>
>> Hi Chao,
>>
>> Is there any example app/gist/repo which can help me use this plugin. I
>> wanted to try out some realtime aggregate performance on top of parquet and
>> spark dataframes.
>>
>> Thanks and Regards
>> Praveen
>>
>>
>> On Wed, Feb 14, 2024 at 9:20 AM Chao Sun <sunc...@apache.org> wrote:
>>
>>> > Out of interest what are the differences in the approach between this
>>> and Glutten?
>>>
>>> Overall they are similar, although Gluten supports multiple backends
>>> including Velox and Clickhouse. One major difference is (obviously)
>>> Comet is based on DataFusion and Arrow, and written in Rust, while
>>> Gluten is mostly C++.
>>> I haven't looked very deep into Gluten yet, but there could be other
>>> differences such as how strictly the engine follows Spark's semantics,
>>> table format support (Iceberg, Delta, etc), fallback mechanism
>>> (coarse-grained fallback on stage level or more fine-grained fallback
>>> within stages), UDF support (Comet hasn't started on this yet),
>>> shuffle support, memory management, etc.
>>>
>>> Both engines are backed by very strong and vibrant open source
>>> communities (Velox, Clickhouse, Arrow & DataFusion) so it's very
>>> exciting to see how the projects will grow in future.
>>>
>>> Best,
>>> Chao
>>>
>>> On Tue, Feb 13, 2024 at 10:06 PM John Zhuge <jzh...@apache.org> wrote:
>>> >
>>> > Congratulations! Excellent work!
>>> >
>>> > On Tue, Feb 13, 2024 at 8:04 PM Yufei Gu <flyrain...@gmail.com> wrote:
>>> >>
>>> >> Absolutely thrilled to see the project going open-source! Huge
>>> congrats to Chao and the entire team on this milestone!
>>> >>
>>> >> Yufei
>>> >>
>>> >>
>>> >> On Tue, Feb 13, 2024 at 12:43 PM Chao Sun <sunc...@apache.org> wrote:
>>> >>>
>>> >>> Hi all,
>>> >>>
>>> >>> We are very happy to announce that Project Comet, a plugin to
>>> >>> accelerate Spark query execution via leveraging DataFusion and Arrow,
>>> >>> has now been open sourced under the Apache Arrow umbrella. Please
>>> >>> check the project repo
>>> >>> https://github.com/apache/arrow-datafusion-comet for more details if
>>> >>> you are interested. We'd love to collaborate with people from the
>>> open
>>> >>> source community who share similar goals.
>>> >>>
>>> >>> Thanks,
>>> >>> Chao
>>> >>>
>>> >>> ---------------------------------------------------------------------
>>> >>> To unsubscribe e-mail: dev-unsubscr...@spark.apache.org
>>> >>>
>>> >
>>> >
>>> > --
>>> > John Zhuge
>>>
>>> ---------------------------------------------------------------------
>>> To unsubscribe e-mail: user-unsubscr...@spark.apache.org
>>>
>>>

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