Re: [SPARK-48423] Unable to save ML Pipeline to azure blob storage

[Chhavi Bansal]

Hello Team,
I am pinging back on this thread to get a pair of eyes on this issue.
Ticket:  https://issues.apache.org/jira/browse/SPARK-48423

On Thu, 6 Jun 2024 at 00:19, Chhavi Bansal  wrote:

> Hello team,
> I was exploring on how to save ML pipeline to azure blob storage, but was
> setback by an issue where it complains of  `fs.azure.account.key`  not
> being found in the configuration even when I have provided the values in
> the pipelineModel.option(key1,value1) field. I considered raising a
> ticket on spark https://issues.apache.org/jira/browse/SPARK-48423, where
> I describe the entire scenario. I tried debugging the code and found that
> this key is being explicitly asked for in the code. The only solution was
> to again set it part of spark.conf which could result to a race condition
> since we work on multi-tenant architecture.
>
>
>
> Since saving to Azure blob storage would be common, Can someone please
> guide me if I am missing something in the `.option` clause?
>
>
>
> I would be happy to make a contribution to the code if someone can shed
> some light on how this could be solved.
>
> --
> Thanks and Regards,
> Chhavi Bansal
>


-- 
Thanks and Regards,
Chhavi Bansal

Re: Spark Decommission

[Khaldi, Ahmed]

Hey Rajesh,

Fromm y experience, it’s a stable feature, however you must keep in mind that 
it will not guarantee that you will not lose the data that is on the pods of 
the nodes getting a spot kill. Once you have a spot a kill, you have 120s to 
give the node back to the cloud provider. This is when the decommission script 
will start and sometimes 120s is enough to migrate the shuffle/rdd blocks, and 
sometimes it’s not. It really depends on your workload and data at the end.


Best regards,

Ahmed Khaldi
Solutions Architect

NetApp Limited.
+33617424566 Mobile Phone
kah...@netapp.com



From: Rajesh Mahindra 
Date: Tuesday, 18 June 2024 at 23:54
To: user@spark.apache.org 
Subject: Spark Decommission
Vous ne recevez pas souvent de courriers de la part de rjshmh...@gmail.com. 
Découvrez pourquoi cela est 
important

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Hi folks,

I am planning to leverage the "Spark Decommission" feature in production since 
our company uses SPOT instances on Kubernetes. I wanted to get a sense of how 
stable the feature is for production usage and if any one has thoughts around 
trying it out in production, especially in kubernetes environment.

Thanks,
Rajesh