Explanation

To view the status of an Azure Synapse Analytics job written in Scala, the optimal approach is to use Synapse Studio's built-in monitoring capabilities specifically designed for Apache Spark applications.

Why Option C is Correct

• Direct Monitoring Interface: Synapse Studio provides a dedicated monitoring section for Apache Spark applications, which includes Scala jobs. This interface displays real-time status information including running, completed, failed, or canceled states.
• Comprehensive Job Details: The Apache Spark applications monitor shows detailed information such as execution time, resource utilization, and application logs, making it the most comprehensive tool for job status monitoring.
• Native Integration: This approach leverages Azure Synapse Analytics' native monitoring capabilities without requiring additional configuration or external tools.

Why Other Options Are Less Suitable

Option A (SQL requests monitor): This is designed for SQL pool queries and dedicated SQL pool operations, not for Scala-based Spark jobs. Scala jobs run on Apache Spark pools, which have different monitoring requirements.

Option B (Azure Monitor with AzureDiagnostics table): While Azure Monitor can collect diagnostic data, this approach requires additional configuration and Kusto query expertise. It's less direct and more complex than using the built-in Synapse Studio monitoring.

Option D (Azure Monitor with SparkLoggingEvent_CL table): This table may not be available by default and requires custom logging configuration. Even if configured, it provides log data rather than direct job status information, making it less efficient for simple status checking.

Best Practice Recommendation

For routine monitoring of Scala jobs in Azure Synapse Analytics, using Synapse Studio's Apache Spark applications monitor is the recommended approach as it provides immediate, comprehensive status information without additional setup or query complexity.