One of the key features in Microsoft SQL Server is the Query Store, which can be used to monitor and analyze query performance in a database. With the Query Store, you can retrieve historical data about executed queries, their execution plans, and performance metrics.

In this blog post, we will explore how to use the historical data stored in the Query Store to understand query performance trends over time. This can be particularly useful for identifying long-term performance issues, assessing the impact of code changes, and making informed decisions for query optimization.

Table of Contents

• Enabling and configuring the SQL Query Store
• Retrieving historical query data
• Analyzing query performance trends
• Identifying regression and improvement
• Summary and conclusion

Enabling and configuring the SQL Query Store

Before we can start using the Query Store, we need to enable and configure it for our database. The Query Store is enabled at the database level, and you can configure various settings such as data retention period and query capture mode.

To enable the Query Store, execute the following T-SQL command:

ALTER DATABASE [YourDatabase] SET QUERY_STORE = ON;

Once enabled, the Query Store will start capturing query data for the specified retention period.

Retrieving historical query data

To retrieve historical query data from the Query Store, you can use the built-in system views and functions.

One important view is the sys.query_store_query view, which contains information about executed queries along with their associated performance metrics. You can use this view to extract useful information such as query execution time, CPU time, and number of executions.

SELECT 
    q.query_id,
    q.query_hash,
    q.query_text,
    q.execution_count,
    q.total_elapsed_time,
    q.total_worker_time,
    q.max_elapsed_time,
    q.max_worker_time
FROM sys.query_store_query AS q
ORDER BY q.total_elapsed_time DESC;

Analyzing query performance trends

Once you have retrieved the historical query data, you can analyze the performance trends over time. This can help you identify queries that have become slower or faster over a period.

One useful metric for analysis is the total_elapsed_time, which represents the total execution time of a query. By comparing this metric for different time periods, you can spot trends and patterns.

You can also retrieve the execution plans for different versions of a query using the sys.query_store_plan view. This allows you to compare and analyze any plan changes that might have impacted query performance.

Identifying regression and improvement

By analyzing the historical query data, you can identify queries that have regressed or improved in performance. This information can be valuable for troubleshooting and optimizing query performance.

For example, you can identify queries with a significantly higher total_elapsed_time compared to previous executions. This might indicate a performance regression that needs to be addressed.

On the other hand, queries with a lower total_elapsed_time could indicate improvements in query performance, which can be attributed to code changes or query optimizations.

Summary and conclusion

The SQL Query Store is a powerful tool for monitoring and analyzing query performance in SQL Server. By leveraging the historical data stored in the Query Store, you can gain valuable insights into query performance trends over time.

In this blog post, we covered the steps to enable and configure the Query Store, retrieve historical query data, analyze performance trends, and identify regression and improvement.

Understanding query performance trends can help you make informed decisions for query optimization, proactively identify performance issues, and ensure a smooth running database environment.

#sql #query-store