Free Access GAQM.Databricks-Certified-Data-Engineer-Associate.v2025-10-18.q113 Practice Test (Page 17)

Question 76

A data engineer needs access to a table new_uable, but they do not have the correct permissions. They can ask the table owner for permission, but they do not know who the table owner is.
Which approach can be used to identify the owner of new_table?

A.There is no way to identify the owner of the table

B.Review the Owner field in the table's page in the cloud storage solution

C.Review the Permissions tab in the table's page in Data Explorer

D.Review the Owner field in the table's page in Data Explorer

Question 77

An engineering manager uses a Databricks SQL query to monitor ingestion latency for each data source. The manager checks the results of the query every day, but they are manually rerunning the query each day and waiting for the results.
Which of the following approaches can the manager use to ensure the results of the query are updated each day?

A.They can schedule the query to refresh every 1 day from the SQL endpoint's page in Databricks SQL.

B.They can schedule the query to refresh every 12 hours from the SQL endpoint's page in Databricks SQL.

C.They can schedule the query to refresh every 1 day from the query's page in Databricks SQL.

D.They can schedule the query to run every 1 day from the Jobs UI.

E.They can schedule the query to run every 12 hours from the Jobs UI.

Question 78

A data analyst has created a Delta table sales that is used by the entire data analysis team. They want help from the data engineering team to implement a series of tests to ensure the data is clean. However, the data engineering team uses Python for its tests rather than SQL.
Which of the following commands could the data engineering team use to access sales in PySpark?

A.spark.table("sales")

B.spark.sql("sales")

C.spark.delta.table("sales")

D.There is no way to share data between PySpark and SQL.

E.SELECT * FROM sales

Question 79

In order for Structured Streaming to reliably track the exact progress of the processing so that it can handle any kind of failure by restarting and/or reprocessing, which of the following two approaches is used by Spark to record the offset range of the data being processed in each trigger?

A.Replayable Sources and Idempotent Sinks

B.Write-ahead Logs and Idempotent Sinks

C.Structured Streaming cannot record the offset range of the data being processed in each trigger.

D.Checkpointing and Write-ahead Logs

E.Checkpointing and Idempotent Sinks

Question 80

A Delta Live Table pipeline includes two datasets defined using streaming live table. Three datasets are defined against Delta Lake table sources using live table.
The table is configured to run in Production mode using the Continuous Pipeline Mode.
What is the expected outcome after clicking Start to update the pipeline assuming previously unprocessed data exists and all definitions are valid?

A.All datasets will be updated once and the pipeline will shut down. The compute resources will be terminated.

B.All datasets will be updated at set intervals until the pipeline is shut down. The compute resources will persist to allow for additional testing.

C.All datasets will be updated once and the pipeline will shut down. The compute resources will persist to allow for additional testing.

D.All datasets will be updated at set intervals until the pipeline is shut down. The compute resources will be deployed for the update and terminated when the pipeline is stopped.

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