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Answer: Use the get command to capture the settings for the existing pipeline; remove the pipeline_id and rename the pipeline; use this in a create command
The correct approach is to use the Databricks CLI `get` command to retrieve the JSON configuration of the existing pipeline. This configuration includes all necessary settings. However, the `pipeline_id` must be removed because it is unique to the existing pipeline and cannot be reused. The engineer should also rename the pipeline to avoid conflicts. The modified JSON can then be used with the `create` command to generate a new pipeline. Option C correctly outlines this process. Other options either use incorrect commands (e.g., `list` does not provide full specs), involve unnecessary steps (e.g., stopping/resetting in B), or do not explicitly handle pipeline_id and versioning (e.g., cloning in D might not produce a versioned JSON file).
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Which Databricks CLI command should a data engineer use to extract pipeline settings from an existing workspace configuration and save them as a versioned JSON file for creating a new pipeline?
A
Use list pipelines to get the specs for all pipelines; get the pipeline spec from the returned results; parse and use this to create a pipeline
B
Stop the existing pipeline; use the returned settings in a reset command
C
Use the get command to capture the settings for the existing pipeline; remove the pipeline_id and rename the pipeline; use this in a create command
D
Use the clone command to create a copy of an existing pipeline; use the get JSON command to get the pipeline definition; save this to git