The security team is exploring whether or not the Databricks secrets module can be leveraged for connecting to an external database.
After testing the code with all Python variables being defined with strings, they upload the password to the secrets module and configure the correct permissions for the currently active user. They then modify their code to the following (leaving all other variables unchanged).

Which statement describes what will happen when the above code is executed?

• A.The connection to the external table will fail; the string "redacted" will be printed.
• B.An interactive input box will appear in the notebook; if the right password is provided, the connection will succeed and the encoded password will be saved to DBFS.
• C.An interactive input box will appear in the notebook; if the right password is provided, the connection will succeed and the password will be printed in plain text.
• D.The connection to the external table will succeed; the string value of password will be printed in plain text.
• E.The connection to the external table will succeed; the string "redacted" will be printed.

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A data engineer is analyzing a large, partitioned retail dataset in Databricks, where each row represents a sale made by a salesperson. The dataset contains millions of records with the following schema:
sales_df: [salesperson_id: string, region: string, sale_amount: double, sale_date: date] The data engineer needs to generate a DataFrame that ranks salespeople within each region based on their total cumulative sales, with the highest seller ranked as 1. If multiple salespeople have the same total sales, they should share the same rank.
The data engineer wants to implement this logic using a PySpark window function and the dense_rank () function.
Which code snippet will perform this ranking?

• A.
• B.
• C.
• D.

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A data engineer and a platform engineer are working together to automate their system tasks. A script needs to be executed outside of Databricks only if a particular daily Databricks job finishes successfully for the day. Databricks CLI command was used to check the last execution of the job. What are the required command options for that task?

• A.databricks jobs list-runs --job-id JOB_ID --start-time-to TODAY_MIDNIGHT_EPOCH_MS -- completed-only
• B.databricks jobs list-runs --job-id JOB_ID --start-time-from TODAY_MIDNIGHT_EPOCH_MS -- active-only
• C.databricks jobs list-runs --job-id JOB_ID --start-time-to TODAY_MIDNIGHT_EPOCH_MS --active- only
• D.databricks jobs list-runs --job-id JOB_ID --start-time-from TODAY_MIDNIGHT_EPOCH_MS -- completed-only

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A new data engineer notices that a critical field was omitted from an application that writes its Kafka source to Delta Lake. This happened even though the critical field was in the Kafka source.
That field was further missing from data written to dependent, long-term storage. The retention threshold on the Kafka service is seven days. The pipeline has been in production for three months.
Which describes how Delta Lake can help to avoid data loss of this nature in the future?

• A.The Delta log and Structured Streaming checkpoints record the full history of the Kafka producer.
• B.Delta Lake schema evolution can retroactively calculate the correct value for newly added fields, as long as the data was in the original source.
• C.Delta Lake automatically checks that all fields present in the source data are included in the ingestion layer.
• D.Data can never be permanently dropped or deleted from Delta Lake, so data loss is not possible under any circumstance.
• E.Ingestine all raw data and metadata from Kafka to a bronze Delta table creates a permanent, replayable history of the data state.

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Which statement describes the default execution mode for Databricks Auto Loader?

• A.New files are identified by listing the input directory; new files are incrementally and idempotently loaded into the target Delta Lake table.
• B.Cloud vendor-specific queue storage and notification services are configured to track newly arriving files; new files are incrementally and impotently into the target Delta Lake table.
• C.Webhook trigger Databricks job to run anytime new data arrives in a source directory; new data automatically merged into target tables using rules inferred from the data.
• D.New files are identified by listing the input directory; the target table is materialized by directory querying all valid files in the source directory.
• E.Cloud vendor-specific queue storage and notification services are configured to track newly arriving files; the target table is materialized by directly querying all valid files in the source directory.

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