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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?
A
Implement custom logging within notebooks to track execution times, then manually review these logs for any patterns or outliers.
B
Utilize Azure Databricks' event logs, export them to a data lake for analysis with Azure Data Lake Analytics, focusing on query execution patterns.
C
Enable detailed query execution logs in Databricks, analyze them with the built-in Spark UI, and optimize based on the identified bottlenecks.
D
Capture performance metrics using Azure Monitor, correlate them with specific queries logged in Azure Log Analytics, and apply optimizations.
