You are attaching an Azure Databricks-based compute resource to an Azure Machine Learning development workspace. You need to configure parameters to attach the resource. Which three parameters should

The correct answer is A. Workspace name B. Compute name E. Access token. When attaching an Azure Databricks cluster as a compute resource to an Azure ML workspace, three parameters are required: (A) the Databricks workspace name to identify which Databricks workspace to connect to, (B) the compute name that will represent the attached resource within

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Question

You are attaching an Azure Databricks-based compute resource to an Azure Machine Learning development workspace. You need to configure parameters to attach the resource. Which three parameters should you use? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.

Options

AWorkspace name
BCompute name
CWorkspace user credentials
DWorkspace resource ID
EAccess token

How the community answered

(18 responses)

A
89% (16)
C
6% (1)
D
6% (1)

Explanation

When attaching an Azure Databricks cluster as a compute resource to an Azure ML workspace, three parameters are required: (A) the Databricks workspace name to identify which Databricks workspace to connect to, (B) the compute name that will represent the attached resource within Azure ML, and (E) a Databricks personal access token for authenticating to the Databricks workspace. The workspace resource ID (D) is not required for this attachment operation, and workspace user credentials (C) are not used-Databricks uses its own token-based auth.

Topics

#Azure ML Compute Target#Azure Databricks Integration#Resource Attachment#Authentication

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