DAA-C01 Exam Dumps | A data pipeline is failing intermittently, with the error logs indicating 'Insufficient compute resources'.

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Question 70/151

A data pipeline is failing intermittently, with the error logs indicating 'Insufficient compute resources'. You are tasked with collecting data to diagnose the root cause. What combination of Snowflake features and data collection strategies would be MOST effective in identifying if warehouse auto-scaling or query performance is the primary contributor to the issue?

A. Monitor the Snowflake warehouse resource monitor metrics (e.g., QUEUED LOAD BYTES, EXECUTION TIME) using the Snowflake web interface or view, focusing on periods coinciding with pipeline failures.

B. Increase the warehouse size significantly and observe if the pipeline failures cease.

C. Analyze the average query execution time for all queries run by the pipeline using the QUERY_HISTORY view and compare it to the warehouse's average execution time. Additionally, check for queries spilling to local disk (using WAREHOUSE LOAD) during failure periods.

D. Create a new, larger warehouse and migrate the pipeline to it without analyzing the current warehouse's performance.

E. Collect only error logs generated by the data pipeline to understand underlying problem.

Correct Answer: A,C

Options A and C provide a targeted approach. A allows tracking warehouse resource usage during the pipeline failures, identifying if the warehouse is reaching its limits. C helps identify slow-running queries contributing to resource exhaustion and detects queries using excessive local disk, indicating potential optimization opportunities. Increasing the warehouse size without analysis (B & D) is not cost-effective. Collecting only error logs (E) is not sufficient for a comprehensive diagnostic approach. It is too narrow and may not expose warehouse load issues and bottlenecks.

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