DP-100 · Question #544
You manage an Azure Machine Learning workspace. You configure a standalone Apache Spark job in the workspace by using Python SDK v2. You need to create the job by using an Azure Machine Learning…
The correct answer is B. Spark D. MLClient. To submit a standalone serverless Spark job in Azure Machine Learning using Python SDK v2, you need two key classes: the Spark class (B), which defines the job specification including inputs, outputs, compute configuration (set to serverless), and identity; and the MLClient…
Question
Options
- ASynapseSparkCompute
- BSpark
- CIdentityConfiguration
- DMLClient
How the community answered
(29 responses)- A3% (1)
- B83% (24)
- C14% (4)
Explanation
To submit a standalone serverless Spark job in Azure Machine Learning using Python SDK v2, you need two key classes: the Spark class (B), which defines the job specification including inputs, outputs, compute configuration (set to serverless), and identity; and the MLClient class (D), which is used to authenticate with the workspace and submit the job via ml_client.jobs.create_or_update(). SynapseSparkCompute (A) is used for attached Synapse pools, not serverless compute. IdentityConfiguration (C) is a supporting class that may be embedded within the Spark job definition, not a separately configured class for the job itself.
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