Your analytics team is experiencing slow query performance in Azure Databricks notebooks. What steps would you take to use logging and monitoring to pinpoint and resolve these performance issues?

Real Exam

Implement custom logging within notebooks to track execution times, then manually review these logs for any patterns or outliers.

5.3%

Utilize Azure Databricks' event logs, export them to a data lake for analysis with Azure Data Lake Analytics, focusing on query execution patterns.

14.9%

Enable detailed query execution logs in Databricks, analyze them with the built-in Spark UI, and optimize based on the identified bottlenecks.

59.6%

Capture performance metrics using Azure Monitor, correlate them with specific queries logged in Azure Log Analytics, and apply optimizations.

20.2%

Databricks Certified Data Engineer - Professional