Performance Testing with SQL Server Distributed Replay
By Tom Nonmacher
SQL Server Distributed Replay is a powerful tool that enables you to replay captured database workloads on a target environment. This can be extremely beneficial when conducting performance testing, as it allows you to accurately simulate the workload of your production environment in a testing scenario. This article will cover how to use SQL Server Distributed Replay for performance testing, with a focus on SQL Server 2016 and SQL Server 2017, but also touching on MySQL 5.7, DB2 11.1, and Azure SQL.
Before diving into the details, it's important to understand the architecture of SQL Server Distributed Replay. At a high level, it consists of four components: the administration tool, the controller, one or more clients, and the target server. The administration tool is used to control the distribution of the replay, the controller orchestrates the clients, the clients execute the workload against the target server, and the target server is the system being tested.
To set up a replay, you first need to capture a trace from your production environment. This can be done using SQL Server Profiler. Once you have a trace file, you can use the Distributed Replay administration tool to preprocess the trace and distribute the replay data to the clients.
Here is an example of how you might preprocess a trace using T-SQL:
EXEC sp_trace_setfilter @TraceID, 10, 0, 7, N'SQL Server Profiler - 9c697734-79c6-4d20-bf38-83eef6d0a5a4'
EXEC sp_trace_setstatus @TraceID, 1
EXEC sp_trace_setstatus @TraceID, 2
Once the preprocessing is done, you can use the administration tool to start the replay. The clients will execute the replay data against the target server, allowing you to observe how your system performs under the simulated workload.
The following example shows how you might start a replay with T-SQL:
EXEC sp_trace_setstatus @TraceID, 1
EXEC sp_trace_setstatus @TraceID, 0
While this article focused on SQL Server, it's worth noting that similar testing can be performed on other database platforms as well. For instance, MySQL 5.7 and DB2 11.1 both have their own tools for workload capture and replay, and Azure SQL offers an equivalent service in the form of the Database Experimentation Assistant.
In conclusion, SQL Server Distributed Replay is a valuable tool for performance testing. By capturing and replaying production workloads, you can gain a realistic understanding of how your system will perform under load, helping you to identify and address performance bottlenecks before they become a problem in your production environment.