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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.
Explanation:
The correct answer is C because:
Databricks SQL Query Scheduling: In Databricks SQL, queries can be scheduled directly from the query's page to refresh at specified intervals. This is the most appropriate approach for a SQL query that needs to be refreshed daily.
SQL Endpoint vs Query Page: Option A and B mention scheduling from the SQL endpoint's page, which is incorrect. SQL endpoints are for configuring compute resources, not for scheduling query refreshes.
Jobs UI Alternative: While options D and E (using Jobs UI) could technically work, they are not the most direct or appropriate solution for a Databricks SQL query. The Jobs UI is better suited for running notebooks, scripts, or JARs as part of data engineering pipelines, not for scheduling SQL query refreshes.
Daily Requirement: The manager needs results updated each day, so a 1-day refresh schedule (option C) is appropriate. A 12-hour schedule (options B and E) would be more frequent than needed.
Key Concept: In Databricks SQL, you can schedule queries to refresh automatically from the query's details page, which is the recommended approach for ensuring query results are updated on a regular schedule without manual intervention.