Analysis of the Performance Issue

The scenario describes a situation where commonly used queries are experiencing slow performance, while infrequently used queries show no performance degradation. This pattern strongly suggests an issue with the adaptive cache in Azure Synapse Analytics dedicated SQL pools.

Why Cache Hit Percentage is the Correct Metric

Cache Hit Percentage directly measures how effectively the workload is leveraging the built-in cache:

• High cache hit percentage indicates that queries are efficiently retrieving data from cache rather than from storage
• Low cache hit percentage suggests that frequently used queries are not benefiting from cached results, forcing them to read from storage each time
• This metric specifically addresses the pattern described: commonly used queries should have high cache utilization, but if they're not, performance will degrade

Why Other Metrics Are Less Suitable

• DWU Percentage: This measures overall resource utilization but doesn't specifically indicate cache performance issues. High DWU percentage could indicate many different resource constraints, not specifically cache-related problems.

• DWU Limit: This represents the maximum capacity of the data warehouse, not current utilization or cache effectiveness.

• Data IO Percentage: While related to storage operations, this metric doesn't distinguish between cache hits and misses, making it less specific for identifying cache-related performance issues.

Best Practice Recommendation

When troubleshooting slow performance for frequently used queries in Azure Synapse Analytics, Cache Hit Percentage should be the primary metric to investigate first, as it directly measures whether the adaptive cache is being effectively utilized. A low cache hit percentage for commonly executed queries indicates that the system is not benefiting from cached results, leading to unnecessary storage operations and degraded performance.