Hello,
I have been hearing about GPU in spark3.
For batch jobs , will it help to improve GPU performance. Also is GPU
support available only on Databricks or on cloud based Spark clusters ?
I am new , if anyone can share insight , it will help
Thanks
Rajat
Spark does not use GPUs itself, but tasks you run on Spark can.
The only 'support' there is is for requesting GPUs as resources for tasks,
so it's just a question of resource management. That's in OSS.
On Sat, Aug 13, 2022 at 8:16 AM rajat kumar
wrote:
> Hello,
>
> I have been hearing about GPU
Thanks Sean.
Also, I observed that lots of things are not supported in GPU by NVIDIA.
E.g. nested types/decimal type/Udfs etc.
So, will it use CPU automatically for running those tasks which require
nested types or will it run on GPU and fail.
Thanks
Rajat
On Sat, Aug 13, 2022, 18:54 Sean Owen
This isn't a Spark question, but rather a question about whatever Spark
application you are talking about. RAPIDS?
On Sat, Aug 13, 2022 at 10:35 AM rajat kumar
wrote:
> Thanks Sean.
>
> Also, I observed that lots of things are not supported in GPU by NVIDIA.
> E.g. nested types/decimal type/Udfs
This thread may be better suited as a discussion in our Spark plug-in’s
repo:
https://github.com/NVIDIA/spark-rapids/discussions.
Just to answer the questions that were asked so far:
I would recommend checking our documentation for what is supported as of
our latest release (22.06):
https://nvidi
One of the best things that could have happened to SPARK (now mostly an
overhyped ETL tool with small incremental optimisation changes and no
large scale innovation) is the release by NVIDIA for GPU processing. You
need some time to get your head around it, but it is supported quite easily
in AWS E
Hi,
I have a simple ETL application, where the data source schama needs to be
sanitized. Column names might include special characters that need to be
removed. For example, from "some{column}" to "some_column".
Normally I'd just alias the columns, but in this case the schema can have
thousands
