Databricks Certified Data Engineer - Associate
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A data engineering team is designing a Databricks Job to orchestrate a multi-step ETL pipeline. The pipeline consists of three sequential stages: loading raw data from external sources, transforming the data, and generating business reports. The team wants to ensure that each stage only starts after the previous one has completed successfully, and they also want to optimize for performance and ease of troubleshooting.
Simulated
A
It allows for parallel execution of independent tasks, potentially reducing total pipeline runtime.
B
It enables detailed monitoring and easier debugging by isolating failures to specific tasks.
C
It provides built-in support for defining and enforcing dependencies between tasks.
D
All of the above.
Explanation:
Configuring a pipeline as a multi-task Databricks Job allows for parallel execution of independent tasks, which can improve performance. It also enables granular monitoring and debugging, as failures can be traced to specific tasks. Additionally, it provides a framework for managing dependencies, ensuring tasks execute in the correct order and improving overall reliability.
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