SQL Server query performance guide with CTE and large datasets
I'm refactoring my project and I'm running into a important performance scenario with a SQL Server query that uses a Common Table Expression (CTE) to retrieve data from a large dataset... The CTE is supposed to aggregate some values before I join it with another table, but the query execution time is exceedingly long, taking over 30 seconds on a dataset of approximately 1 million rows. Here's the structure of my query: ```sql WITH CTE_Aggregate AS ( SELECT UserID, COUNT(*) AS TotalOrders FROM Orders WHERE OrderDate >= '2023-01-01' GROUP BY UserID ) SELECT U.UserID, U.UserName, C.TotalOrders FROM Users U LEFT JOIN CTE_Aggregate C ON U.UserID = C.UserID WHERE U.IsActive = 1; ``` I've indexed the `OrderDate` column in the `Orders` table, but the performance still seems sluggish. I've tried rewriting the query to use a subquery instead of a CTE, but that didn't yield any improvement. I also looked into the execution plan and noticed a lot of reads happening on the `Orders` table, which seems to be the bottleneck. Is there a more efficient way to structure this query, or perhaps a different approach to achieve the same result? I'm looking for best practices or techniques that could help improve the performance here. Any insights would be greatly appreciated! This is part of a larger web app I'm building. My development environment is Ubuntu. What's the best practice here? Could this be a known issue? The stack includes Sql and several other technologies. Thanks for your help in advance!