Databricks Data Engineer Associate Question 365
Select 3You are tasked with creating a new Delta Live Tables (DLT) pipeline in Databricks to transform raw data into clean, usable datasets. Which components do you need to configure to successfully create the pipeline?
- A
The storage location for pipeline output and checkpoints
- B
A cluster policy to enforce pipeline execution settings
- C
A target database name for storing resulting tables
- D
A Python or SQL notebook containing the transformation logic
- E
The compute cluster type (e.g., Standard, High Concurrency) for the pipeline
Show answer and explanation
Correct answers: A, C, D
Explanation
To create a Delta Live Tables (DLT) pipeline, you must configure several key components. A storage location is required to store outputs and checkpoints, a target database is needed to store the resulting tables, and transformation logic must be provided in a Python or SQL notebook. Cluster policies and manually defining cluster types are not necessary for DLT pipelines, as Databricks handles compute resources automatically for DLT execution.
- A. Correct.
Correct. You must define a storage location for the pipeline to store output data and maintain state (e.g., checkpoints).
- B. Incorrect.
Incorrect. While cluster policies are useful in Databricks, they are not necessary to create or run a DLT pipeline.
- C. Correct.
Correct. You need to specify a target database where the resulting tables will be stored after the pipeline runs.
- D. Correct.
Correct. The transformation logic must be defined in a Python or SQL notebook to create a DLT pipeline.
- E. Incorrect.
Incorrect. You do not need to explicitly define the compute cluster type for a DLT pipeline, as Databricks automatically provisions compute resources for pipeline execution.