Optimizing MERGE Statements: The Role of Temporary Tables in SQL Server Performance

Understanding the Mysterious Case of SELECT into Temp Table vs MERGE Performance

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As a technical blogger, I recently came across a puzzling Stack Overflow question regarding the performance difference between using a table-valued function (TVF) directly in a MERGE statement versus storing its results in a temporary table and then using that temp table in the MERGE statement. The question sought to understand why it seemed that the first approach, although seemingly less efficient due to the extra step of writing data to a table, resulted in a faster execution time compared to directly using the TVF in the MERGE query.

In this article, we will delve into the world of SQL optimization, exploring the factors that contribute to performance differences between these two approaches. We’ll examine how temporary tables can provide valuable information to the optimizer, which might seem counterintuitive at first glance.

Theoretical Background: Temporary Tables and TVFs

Temporary Tables

Temporary tables are a fundamental concept in SQL Server (and other databases) that allow you to store data temporarily while performing calculations or transformations. When a temporary table is created, it occupies space on disk until it is explicitly dropped. This means that the storage of data within the temp table will require disk I/O operations.

Table-Valued Functions

Table-valued functions (TVFs), on the other hand, are similar to regular functions but can return result sets instead of values. When a TVF is used in a query, it creates an execution plan that involves materializing its output into a temporary result set. Once the result set has been computed, the optimizer uses this information to generate an optimal execution plan for further processing.

The Role of Temporary Tables in Optimization

Temporary tables provide the optimizer with additional information about the data and operations involved in the query. This includes:

Estimated row count: By knowing how many rows a temporary table will contain after being populated, the optimizer can better estimate the number of rows that need to be processed, which helps it choose more efficient algorithms for processing.
Disk space allocation: With information about disk space requirements (e.g., page allocation), the optimizer can allocate necessary resources to ensure optimal performance.
Input/Output operations: Temporary tables allow the optimizer to estimate input/output operations that occur during execution. Knowing these will enable the optimizer to choose more efficient I/O sequences.

In contrast, when using a TVF directly in a query, there’s less information available about the temporary result set before its computation is complete. This can lead to difficulties for the optimizer in selecting an optimal execution plan early on.

Analysis of the Performance Results

The question provided two examples: one with the table-valued function used directly in the MERGE statement and another where it was first stored in a temporary table, followed by the MERGE operation. By comparing these results, we can deduce why using a temp table seems to yield better performance.

The Case Against Direct Use of TVF

Less efficient I/O operations: Without information about the size of the result set until after its computation is complete, the optimizer might be forced to perform additional disk reads or writes during execution.
Higher overhead due to function evaluation: Materializing the entire output of a table-valued function into memory may incur higher CPU costs compared to using an existing temp table.

The Benefits of Temp Tables

Using temporary tables allows the optimizer to take advantage of information about row counts, disk space allocation, and input/output operations earlier in the optimization process. This enables it to select more efficient algorithms for processing data from the source function results.

For instance:

Estimated row count: Knowing that a temp table can contain up to 10 million rows (as shown in the question’s example) lets the optimizer choose an optimized algorithm with lower memory requirements.
Page allocation and deallocation: By understanding how disk space is allocated for the temporary result set, the optimizer can minimize the number of page allocations and deallocations during execution.

Example and Discussion

Let’s examine a more detailed scenario to see this in action. Suppose we have two tables: TableA with 5 million rows, and TableB that has 3 times as many rows (15 million) but doesn’t change frequently.

-- Create sample data for Table A and Table B
CREATE TABLE TableA (
    ID INT,
    Value INT
);

INSERT INTO TableA (ID, Value)
SELECT TOP(5_000_000) * FROM sys.tables;

CREATE TABLE TableB (
    ID INT,
    Value INT
);
INSERT INTO TableB (ID, Value)
SELECT TOP(15_000_000) * FROM sys.tables;

Now let’s use a table-valued function to populate Table A with data from Table B:

-- Create TVF
CREATE FUNCTION GetTableAVariation (@StartDate INT, @EndDate INT)
RETURNS TABLE
AS
RETURN 
    SELECT T2.Value
    FROM TableB T1
        INNER JOIN TableA T2 ON T1.ID = T2.ID + 10000000
    WHERE T1.Date > @StartDate AND T1.Date <= @EndDate;

In the following MERGE query, we compare the performance of using this TVF directly with storing its results in a temporary table:

Direct Use

-- Using TVF directly without temp tables
MERGE INTO TableA AS Target
USING GetTableAVariation(@StartDate, @EndDate) Source ON Target.ID = Source.ID
WHEN MATCHED THEN UPDATE SET Value = Source.Value
WHEN NOT MATCHED THEN INSERT (ID,Value) VALUES(Source.ID,Source.Value);

Temporary Tables

-- Using TVF results stored in a temp table
SELECT *
INTO #TempTableVariation
FROM GetTableAVariation(@StartDate, @EndDate);

MERGE INTO TableA AS Target
USING #TempTableVarition AS Source ON Target.ID = Source.ID
WHEN MATCHED THEN UPDATE SET Value = Source.Value
WHEN NOT MATCHED THEN INSERT (ID,Value) VALUES(Source.ID,Source.Value);
DROP TABLE #TempTableVariation;

In the case of our sample data and TVF function, we would expect storing its results in a temporary table (#TempTableVarition) to outperform directly using it in the MERGE statement.

Conclusion

Understanding why the performance difference exists between MERGE statements involving direct table-valued functions versus those that store their results in temporary tables is rooted in how these approaches provide information to the optimizer about the execution environment and data distribution. Temporary tables allow for more efficient planning by offering row counts, disk space usage estimates, and I/O patterns, which ultimately leads to better query performance.

While it may seem counterintuitive at first that storing TVF results in a temporary table could outperform using the function directly, this difference highlights an important aspect of SQL Server’s optimizer: its ability to take advantage of available information during optimization.

Last modified on 2024-12-22