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Answer: Monitor a variety of metrics and logs, such as execution time, resource utilization, and query execution plans, to gain a comprehensive understanding of the pipeline's performance.
Measuring query performance in a data pipeline requires monitoring a variety of metrics and logs to gain a comprehensive understanding of the pipeline's performance. Key metrics and logs to consider include execution time, resource utilization, query execution plans, and any errors or warnings that may occur during query execution. By monitoring these metrics and logs, you can identify areas of inefficiency or potential issues and take appropriate actions to optimize the pipeline's performance. Focusing only on a single metric, such as execution time or the number of queries executed, may not provide a complete picture of the pipeline's performance and may overlook important issues.
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You are responsible for measuring the query performance in a data pipeline in Azure Data Factory. What are some key metrics and logs you should consider monitoring to gain insights into the pipeline's performance?
A
Monitor only the execution time of the queries, ignoring other metrics and logs.
B
Monitor only the number of queries executed, ignoring other metrics and logs.
C
Monitor a variety of metrics and logs, such as execution time, resource utilization, and query execution plans, to gain a comprehensive understanding of the pipeline's performance.
D
Do not monitor any metrics or logs, as they are not necessary for measuring query performance.
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