In today’s technology-driven world, optimizing query performance is crucial for maintaining efficient database systems. One powerful tool that can help in this endeavor is the SQL Query Store. The SQL Query Store, introduced in Microsoft SQL Server 2016, provides valuable insights and metrics about query performance, allowing database administrators to identify and address performance issues. One particularly useful feature of the SQL Query Store is the ability to create query performance baselines. In this blog post, we will explore how to implement query performance baselining with the SQL Query Store.

Table of Contents

1. What is Query Performance Baselining?
2. Enabling the SQL Query Store
3. Capturing Query Performance Data
4. Analyzing Query Performance Baselines
5. Conclusion

What is Query Performance Baselining?

Query performance baselining involves creating a historical performance baseline for queries in the database. By capturing query execution plans, statistics, and other performance data over time, it becomes possible to compare the current performance of a query against its historical baseline. This allows for efficient monitoring and troubleshooting of performance issues, as well as tracking the impact of any optimizations or changes made to the queries.

Enabling the SQL Query Store

To begin implementing query performance baselining, the first step is to enable the SQL Query Store on the target database. This can be done using the following T-SQL statement:

-- Enable the Query Store on the target database
ALTER DATABASE YourDatabaseName
SET QUERY_STORE = ON;

By enabling the Query Store, the SQL Server will start capturing query execution data, making it available for analysis and baselining.

Capturing Query Performance Data

Once the SQL Query Store is enabled, it will automatically start capturing query performance data. The captured data includes execution plans, query runtime statistics, and other relevant information. This data can then be used to establish query performance baselines.

To capture the query performance data, you can use the following query:

-- Capture query performance data for a specific time range
SELECT *
FROM sys.query_store_runtime_stats
WHERE start_time BETWEEN '2022-01-01' AND '2022-01-31';

This query will retrieve the query performance data for the specified time range. You can adjust the date range as needed to capture the relevant data for baselining.

Analyzing Query Performance Baselines

With the captured query performance data, you can now analyze and establish query performance baselines. This involves comparing the current performance of each query against its historical performance data.

One approach to analyzing query performance baselines is using the following query:

-- Compare query average execution time against the baseline
SELECT q.name AS QueryName,
       rs.avg_duration AS CurrentAverageExecutionTime,
       ps.avg_duration AS BaselineAverageExecutionTime
FROM sys.query_store_query q
JOIN sys.query_store_runtime_stats rs ON q.query_id = rs.query_id
JOIN sys.query_store_plan p ON rs.plan_id = p.plan_id
JOIN sys.query_store_runtime_stats ps ON q.query_id = ps.query_id
JOIN sys.query_store_plan pp ON ps.plan_id = pp.plan_id
WHERE rs.start_time = '2022-02-01'
      AND ps.start_time = '2021-02-01'
      AND p.is_baseline = 0
      AND pp.is_baseline = 1;

This query compares the average execution time of queries against their baseline average execution time. It provides insights into any performance deviations and identifies queries that might require optimization or further investigation.

Conclusion

Implementing query performance baselining with the SQL Query Store can greatly enhance the ability to monitor and optimize query performance in SQL Server databases. By capturing and analyzing query performance data, database administrators can identify performance issues, track the impact of changes, and ensure efficient database operations.

In this blog post, we explored the concept of query performance baselining and the steps involved in implementing it using the SQL Query Store. By following the outlined process, you can take a proactive approach to query performance optimization and ensure the smooth and efficient operation of your SQL Server databases.

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