Execute spark jobs in Azure ML studio - azure

I am trying to run some spark scripts using execute python script in azure ML studio. And getting an error saying
unable to import spark libraries
Basically i am trying to create web services using ML studio for the models that are developed.
Is it possible or feasible to run spark jobs using ML studio?
Can anyone please help me on this.
Thanks in advance.

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The base runtime i can simply extend in a dockerfile by doing:
FROM databricksruntime/standard:9.x
Can i do something similar for the ML runtime?
As a follow-up can I see the source code of the ml runtime?
Cheers
ML Runtime = Standard Runtime + ML Libs.
Databricks Runtime 10.2 ML is built on top of Databricks Runtime 10.2.
Reference
You can recreate it by installing the libraries mentioned here.
ver 10.2 is used as an example in this answer.

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If you are using an old SDK so upgrade to the latest SDK and pandas.
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I am using Visual Studio Code (VS Code) to compile and then submit usql scripts on our Azure platform.
Something happend and I cannot compile or submit any usql jobs anymore, with following error message:
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Reinstall visual studio code
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Reinstall the Azure Data Lake Tools package
Remove all generated folders and files and start from scratch
I made sure this is not access-related (I can run jobs on Azure web portal)
The script does not have any bugs and it is supposed to run (checked on Azure web portal)
I work on MS Windows VM x64, VS Code version 1.38.
I am completely puzzled by that, any help greatly appreciated!
I can't reproduce your issue on my side. I follow steps in this detailed guide and it works well for me.
Since you already sorted out several possible issues, I would suggest you checking if you missed some installations follow above link. In particular, the following steps:
2.1 To install BuildTools, click visualcppbuildtools_full.exe in the LocalRunDependency folder, then follow the wizard instructions.
2.2 To install Win10SDK 10240, click sdksetup.exe in the LocalRunDependency/Win10SDK_10.0.10240_2 folder, then follow the
wizard instructions.
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You can define that spark environment using Environments tab in project and then utilize that runtime when you create notebook or change service for existing notebook.
#Veer as #charles said Spark services are now accessible via Environments. When creating a notebook select a Spark compatible environment and import pyspark in your notebook.

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Currently I am working on Text analytics related code and as part of that I want to get the singular values of SVD decomposition something like below
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U = lsa.fit_transform(X)
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AttributeError: 'TruncatedSVD' object has no attribute 'singular_values_'
Process returned with non-zero exit code 1
Already referred to below questions as well
Stackoverflow questions related to upgrade packages in Azure ML studio
How can I install Python packages in Azure ML?
Currently this is the limitation with Azure ML studio. The only way is to reach out to support who generates the necessary package and we can upload it to Azure ML Studio.

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