Tackling High CPU Load in SQL Server: Strategies and Solutions ( Part 6 of 16 )

Tackling High CPU Load in SQL Server: Strategies and Solutions

Summary

High CPU load issues are increasingly common in modern SQL Server environments. The rapid advancements in fast disk subsystems and large memory capacities often mask the underlying problems caused by nonoptimized queries. As a result, reducing CPU load becomes a primary goal in performance tuning.

Nonoptimized queries remain a significant factor in escalating CPU usage. The more data SQL Server needs to scan, the more CPU resources it consumes. General query optimization is a key approach to mitigate this issue. In systems with heavy ad-hoc workloads, query compilation can contribute significantly to CPU usage. Query parameterization is the best practice to address this. However, enabling forced parameterization at the database level can also be considered.

One challenge with parameterization is dealing with parameter-sensitive plans. SQL Server may compile and cache plans for atypical parameter values, which can be inefficient for other parameter combinations. Disabling parameter sniffing often helps alleviate this issue.

Parallelism is another factor to consider. While normal for reporting and analytical workloads, parallelism can introduce overhead in OLTP systems. It often signals the presence of expensive queries that need optimization rather than merely disabling parallelism to mask the problem. Tuning SQL Server's default parallelism settings is essential as they are generally suboptimal.

In the next chapter, we'll explore how to troubleshoot memory-related issues in SQL Server.

Troubleshooting Checklist

1. Analyze and Reduce CPU Load from External Processes :

- Identify and minimize the impact of non-SQL Server processes on CPU usage.

2. Detect and Optimize the “Worst Offenders” :

- Focus on queries that consume the most worker time and optimize them.

3. Identify Resource-Intensive Stored Procedures and T-SQL Modules :

- Detect and optimize the stored procedures and T-SQL modules that heavily utilize resources.

4. Review the Impact of Compilations :

- Analyze the frequency and impact of query compilations. Plan cache metrics can assist in this analysis.

5. Parameterize Critical Queries :

- Ensure critical queries are parameterized to reduce CPU load.

6. Consider Forced Parameterization :

- In environments with heavy ad-hoc workloads, consider enabling forced parameterization and potentially disabling parameter sniffing for better performance.

7. Tune Parallelism Settings :

- Adjust SQL Server’s parallelism settings for optimal performance in OLTP systems.

By following these strategies and the troubleshooting checklist, you can effectively manage and reduce CPU load in your SQL Server environment, ensuring a more efficient and responsive system.

Stay tuned for the next chapter, where we will delve into troubleshooting memory-related issues in SQL Server. Happy tuning!