Performance Tuning with SQL Server’s Query Store
Performance tuning in SQL Server is integral to ensuring that applications running on top of the database can perform their tasks efficiently. One of the powerful tools provided by SQL Server to aid in this process is the Query Store. In this comprehensive analysis, we will delve into how Query Store works, the benefits it brings to performance tuning, as well as practical strategies on how to effectively use it to analyze and improve query performance.
Understanding the Query Store Mechanism
SQL Server’s Query Store is a feature designed to monitor query performance and gather vital statistics which could help in understanding performance problems and fixing them. Introduced in SQL Server 2016, the Query Store serves as a flight recorder for your database by tracking query texts, execution plans, runtime statistics, and execution context information of queries over time.
When enabled, it captures a history of executed queries, their plans, and various performance metrics such as CPU time, duration, logical reads, and physical reads. All this data is stored within the context of the database itself, greatly simplifying the performance analysis process over an extended period.
Setting Up Query Store
Enabling and configuring the Query Store involves understanding and specifying values for various settings that dictate its behavior. These settings include:
- Operation mode: Can be set to Read-Write (active and capturing data) or Read-Only (no new data capture).
- Data flush interval: Determines how often data captured by the Query Store will be saved to disk.
- Statistics collection interval: Specifies the granularity of the performance data collected.
- Max storage size: Limits how much storage the Query Store can use within the database.
- Query capture mode: Controls which queries are collected, allowing for customization based on query execution frequency or resource consumption.
The actual commands to enable and configure the Query Store look like the following example:
ALTER DATABASE [DatabaseName] SET QUERY_STORE = ON;
ALTER DATABASE [DatabaseName] SET QUERY_STORE (OPERATION_MODE = READ_WRITE, DATA_FLUSH_INTERVAL_SECONDS = 900, STATISTICS_COLLECTION_INTERVAL = 60, MAX_STORAGE_SIZE_MB = 1024, QUERY_CAPTURE_MODE = AUTO);
Setting appropriate values for these options will largely depend on the specific workloads and performance concerns of your SQL Server environment.
Query Store Usage in Performance Tuning
Once the Query Store is enabled, there are two main ways it can be effectively used for performance tuning.
- Identifying Regressed Queries: Query Store makes it possible to compare historical performance data for the same query to identify whether there’s been any regression. By analyzing the collected metrics, we can identify increased resource consumption or delays.
- Forcing Execution Plans: In cases where the SQL Server query optimizer chooses different execution plans for the same query over time, you may find that certain plans perform better than others. The Query Store allows you to ‘force’ the use of a particular execution plan that you’ve determined to be the most efficient for a given query.
These strategies help to reduce the time spent analyzing and implementing performance tuning fixes, and they also provide a robust method for ensuring continued query performance over time.
Querying the Query Store Data
To analyze the data stored in the Query Store, you primarily use Transact-SQL queries against a set of catalog views provided specifically for this purpose, such as sys.query_store_runtime_stats, sys.query_store_runtime_stats_interval, sys.query_store_plan, and others. You can retrieve a range of performance-related information with these views, such as average duration, average CPU time, execution counts, and more.
Here’s a simple example that retrieves statistics for a specific query as identified by its query_id:
SELECT
qsrs.average_cpu_time,
qsrs.average_duration,
qsrs.execution_count,
qsrs.total_logical_reads
FROM sys.query_store_runtime_stats qsrs
JOIN sys.query_store_plan qsp
ON qsrs.plan_id = qsp.plan_id
WHERE qsp.query_id = 12345;
This data can help you to visually identify outlier queries that may be consuming disproportionate resources.
Best Practices for Using Query Store
Several best practices can help you extract the maximum value from the Query Store feature:
- Keep the Query Store clean by regularly purging old, irrelevant data that can skew analysis and performance.
- Use comprehensive criteria when comparing query performance over time, looking at multiple metrics rather than focusing on a single statistic.
- Monitor the Query Store’s own performance impact, as it will consume additional resources when enabled.
- Balance the Query Store’s size against database workloads, understanding that excessive data can lead to its own set of issues.
- Stay up to date with SQL Server updates, as Microsoft continually optimizes and introduces new features to the Query Store with each release.
Performance tuning is a continuous process, and the utilization of SQL Server’s Query Store can heavily influence the effectiveness of your tuning efforts. By storing and leveraging detailed query execution data, you can make informed decisions on optimizing the performance of your queries in SQL Server.
