Databricks Certified Data Engineer - Professional
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A Databricks job is designed to perform an ETL process on two distinct datasets using a single notebook task. This notebook extracts CSV files from an AWS S3 bucket, processes the data, and then stores the transformed data in an Azure blob storage. Subsequently, the data is retrieved from Azure, further transformed, and finally loaded into a Google Cloud bucket. Scheduled to run daily, the job encountered a failure after successfully writing data to Azure blob storage. The data engineer plans to use the Repair Run utility to address the failed task. What is the outcome of applying the Repair Run utility in this scenario?
A
The Repair Run utility will initiate the task from the cell that failed during the previous execution, leveraging Databricks' checkpoint mechanism.
B
Upon execution, the Repair Run utility will remove the data stored in Azure blob storage and re-execute the entire task.
C
Thanks to Databricks notebook's version control, the task will recommence from the initially failed cell.
D
The Repair Run utility is not applicable for jobs consisting of a single task.
E
The task will be restarted from the beginning, executing all cells in the notebook sequentially.