Answer-first summary for fast verification
Answer: resource ID of the Synapse Spark pool and a user-defined name
The correct answer is B because the SynapseSparkCompute constructor in Azure ML SDK v2 requires two parameters: the resource ID of the Synapse Spark pool (to identify the specific compute resource in Azure) and a user-defined name (to identify this compute target within the Azure ML workspace). This is confirmed by the community discussion where multiple users validate this answer, with one comment specifically stating that the constructor requires 'resource_id - resource ID of the Synapse Spark pool' and 'name - user-defined name of the new attached Synapse Spark pool.' The Microsoft documentation link provided in the discussion also supports this parameter requirement. Other options are incorrect: A uses workspace web URL and Spark pool name instead of resource ID, C uses pool URL instead of resource ID and suggests system-assigned name instead of user-defined, and D uses workspace identifiers rather than the specific Spark pool resource ID.
Author: LeetQuiz Editorial Team
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You manage an Azure Machine Learning workspace named workspace1.
You need to develop Python SDK v2 code to attach an Azure Synapse Spark pool as a compute target in workspace1. The code must use the constructor of the SynapseSparkCompute class.
Which code should you use?
A
Synapse workspace web URL and Spark pool name
B
resource ID of the Synapse Spark pool and a user-defined name
C
pool URL of the Synapse Spark pool and a system-assigned name
D
Synapse workspace name and workspace web URL
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