SQL Server 2022: Query Store Hints and Performance Tuning
By Tom Nonmacher
The SQL Server 2022 has brought significant improvements and new features that enhance query performance and developer productivity. One such feature is the Query Store Hints, a much-awaited addition that allows developers to optimize their queries for better performance. This blog post will delve into the usage of Query Store Hints and how to leverage them for performance tuning in your SQL Server 2022 environment.
Query Store Hints offer a way to control the execution plan of queries. Instead of letting the SQL Server decide how to execute a query, developers can provide specific instructions, known as hints, to influence the choice of execution plans. This gives developers more control over query performance. While SQL Server's query optimizer usually does an excellent job, there are situations where it might not choose the most efficient plan. That's where Query Store Hints come in.
-- Using a Query Store Hint
SELECT *
FROM Sales.Orders
OPTION (USE HINT('QUERY_STORE_FORCE_LAST_GOOD_PLAN'));
The hint 'QUERY_STORE_FORCE_LAST_GOOD_PLAN' forces the query to use the last known good plan from the Query Store. This can be useful in situations where a query’s performance has degraded due to an inefficient plan choice by the SQL Server’s optimizer.
With the integration of SQL Server 2022 and Azure SQL, developers can take advantage of Microsoft Fabric, a powerful distributed systems platform that makes it easier to build, package, deploy, and manage scalable and reliable applications. Developers can use Microsoft Fabric to develop applications that utilize SQL Server 2022 and Azure SQL databases, and leverage Query Store Hints for performance tuning across these applications.
Delta Lake, a storage layer that brings ACID transactions to Apache Spark and big data workloads, is another technology that can be combined with SQL Server 2022 and Azure SQL. By using Delta Lake, developers can ensure the reliability of their data and maintain the performance of their queries. Query Store Hints can be used to fine-tune the performance of queries against Delta Lake tables.
OpenAI has also made significant strides in integrating with SQL to improve query performance. The OpenAI SQL optimizer can analyze your queries and suggest Query Store Hints when it detects potential performance issues. This makes it easier for developers to optimize their queries without needing to understand the intricacies of SQL Server's query execution plans.
Databricks, a unified analytics platform, can be used with SQL Server 2022 to manage and analyze large data sets. Developers can use Databricks to run Spark jobs against their SQL Server data, and use Query Store Hints to optimize the performance of these jobs. This combination of technologies provides a powerful tool for data analytics and performance tuning.
In conclusion, Query Store Hints and other performance tuning techniques in SQL Server 2022 offer developers more control over their queries' execution plans. With the integration of technologies like Azure SQL, Microsoft Fabric, Delta Lake, OpenAI, and Databricks, developers have a powerful suite of tools at their disposal to optimize the performance of their applications and queries.