In a large-scale database environment, monitoring and optimizing query performance is crucial for ensuring the overall health and efficiency of the system. One common challenge is identifying and troubleshooting performance regressions, where a previously well-performing query suddenly starts to perform poorly. This can have a significant impact on application response times and user experience.

Luckily, SQL Server provides a powerful feature called the Query Store, which can help analyze and diagnose query performance regressions. The Query Store captures a history of executed queries along with their performance metrics, allowing database administrators and developers to identify and understand changes in query performance over time.

Enabling the Query Store

Before we can start using the Query Store to analyze query performance regressions, we need to enable it on our SQL Server database. To do this, execute the following T-SQL command:

ALTER DATABASE YourDatabaseName
SET QUERY_STORE = ON;

Monitoring Query Performance

Once the Query Store is enabled, it automatically starts capturing query performance information. The captured information includes execution plans, average and total CPU time, logical and physical reads, and more.

To view the performance details for a specific query, you can use the following T-SQL command:

SELECT *
FROM sys.query_store_query
WHERE query_id = yourQueryId;

Replace yourQueryId with the desired query’s ID. This query will retrieve the performance details, including execution plans and performance statistics, for the specified query.

Identifying Performance Regressions

The Query Store makes it easy to identify queries that have experienced a performance regression. You can use the following T-SQL query to retrieve the top N queries with the highest average duration:

SELECT TOP(N) 
    qsqt.query_id,
    qt.query_sql_text,
    qsqt.avg_duration
FROM sys.query_store_query_text AS qsqt
JOIN sys.query_store_query AS qsq
    ON qsqt.query_text_id = qsq.query_text_id
JOIN sys.query_store_query AS qt
    ON qsqt.query_id = qt.query_id
WHERE qsqt.avg_duration IS NOT NULL
ORDER BY qsqt.avg_duration DESC;

Replace N with the desired number of queries to retrieve. This query will return the top N queries with the highest average duration, indicating potential performance regressions.

Investigating Performance Regressions

Once you have identified the queries with performance regressions, the next step is to investigate the root causes. You can start by examining the execution plans for these queries using the following T-SQL command:

SELECT *
FROM sys.query_store_plan
WHERE query_id = yourQueryId;

Replace yourQueryId with the ID of the query you want to investigate. This will return the execution plans stored in the Query Store for the specified query.

By comparing the execution plans of the query before and after the regression, you can identify any changes that may have caused the performance degradation, such as missing indexes, changes in cardinality estimation, or degraded query statistics.

Performance Optimization

Once you have identified the root causes of the performance regressions, you can take steps to optimize the affected queries. This may involve rewriting the query, adding missing indexes, updating statistics, or other performance tuning techniques.

After implementing the optimizations, it is important to monitor the query performance using the Query Store again to ensure that the regressions have been resolved and the queries are performing well.

Conclusion

The SQL Query Store is a powerful tool for analyzing and diagnosing query performance regressions in SQL Server. By enabling the Query Store, monitoring query performance, and investigating any regressions, database administrators and developers can optimize query execution and ensure the efficient operation of their database systems.

‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍

‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍

‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍

‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍#SQL #QueryStore