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In the rapidly evolving world of database technology, SQL Server Intelligent Query Processing (IQP) has emerged as a game-changer. Introduced in SQL Server 2019, IQP has revolutionized the way queries are processed, optimized, and managed. This post will provide a deep dive into the functionality and features of SQL Server Intelligent Query Processing to help you understand how this innovative technology can enhance your database management tasks.

IQP provides a suite of features that work together to optimize query performance and minimize resource utilization. This includes batch mode on rowstore, scalar UDF inlining, table variable deferred compilation, and adaptive joins. Let's look at batch mode on rowstore as an example.

-- Example of batch mode on rowstore

SELECT SalesOrderID, OrderQty, ProductID

FROM Sales.SalesOrderDetail

WHERE SalesOrderID IN (43670, 43669, 43667, 43663)

OPTION (USE HINT('ENABLE_BATCH_MODE'))

The batch mode on rowstore feature allows the SQL Server to process data in batches rather than row by row, significantly improving query performance. This feature is particularly beneficial for data warehousing workloads that involve large amounts of data.

Another feature of IQP is scalar UDF inlining. This feature improves the performance of scalar user-defined functions (UDFs) by integrating the logic of the function into the calling SQL statement, thereby eliminating the overhead associated with invoking a separate function.

-- Example of scalar UDF inlining

CREATE FUNCTION dbo.udf_Sales (@ProductID int)

RETURNS int

AS

BEGIN

  RETURN (SELECT SUM(OrderQty) FROM Sales.SalesOrderDetail WHERE ProductID = @ProductID)

END

The table variable deferred compilation is another significant feature of IQP. It enhances the performance of statements that reference table variables by generating an optimal query plan based on the actual table cardinality. This can result in substantial performance improvements, especially for complex queries.

Finally, the adaptive joins feature dynamically chooses the join strategy (hash join or nested loop join) based on the actual row counts. This can significantly enhance performance, especially for queries with uncertain cardinality estimates.

While SQL Server 2019 introduced these transformative features, other technologies like MySQL 8.0, DB2 11.5, Azure SQL, and Azure Synapse have also incorporated similar advanced functionalities to optimize query processing. By understanding and leveraging these features, database administrators and developers can significantly improve query performance and resource utilization, leading to more efficient and effective database management.

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