Understanding Merge Statements with User-Defined Table Types and Input Parameters

As a developer, have you ever found yourself struggling to merge data from multiple sources into a single table? In this blog post, we’ll delve into the world of merge statements, user-defined table types, and input parameters to help you tackle such challenges.

Background and Terminology

Before diving into the solution, it’s essential to understand some key terms and concepts:

• User-Defined Table Type (UDTT): A custom data type created using the CREATE TYPE statement. UDTTs can be used as input parameters in stored procedures or functions.
• Input Parameters: Values passed to a stored procedure or function that are used within its execution.
• Merge Statement: A SQL command used to update existing records in a table based on matching values from another table.

The Challenge

In the provided Stack Overflow question, we have a stored procedure sp_UpsertCustomDesignReqsTable that attempts to merge data into the CustomOrderReqs table using a user-defined table type (@Details) and input parameters (@OrderNumber, @Product_Id, @Purchase_amt). However, there are syntax errors in the code.

Breaking Down the Issues

Let’s analyze each section of the code:

• Source Declaration: The error message indicates that the scalar variable @Details must be declared. This is because the USING clause expects a table or view as an argument.
• Merge Statement Syntax: There are issues with the column names and data types in the merge statement.

Solving the Issues

To resolve these problems, we’ll need to make some adjustments:

1. Define @Details correctly:

   • Since @Details is a user-defined table type, it should be referenced using its fully qualified name ([dbo].[CustomOrderRequestsType]) instead of just the alias.

2. Correct column names and data types in the merge statement:

   • Ensure that all columns are spelled correctly and match the corresponding columns in both tables.
   • Verify that data types are consistent.

Refactored Code

Here’s the corrected code:

ALTER PROCEDURE [dbo].[sp_UpsertCustomDesignReqsTable]
    @OrderNumber VARCHAR(30),
    @Product_Id VARCHAR(50),
    @Purchase_amt DECIMAL(Max),
    @Details [dbo].[CustomOrderRequestsType] READONLY
AS
BEGIN
    SET NOCOUNT ON;

    MERGE [dbo].[CustomOrderReqs] AS TARGET
    USING (VALUES (@OrderNumber, @Product_Id, 
                    COALESCE(@Purchase_amt, 0), 
                    -- Assuming ID is never null, handle duplicates here
                    COALESCE(CASE WHEN [Details].Customer_ID IS NOT NULL THEN [Details].Customer_ID ELSE '' END),
                    COALESCE(CASE WHEN [Details].Customer_Email IS NOT NULL THEN [Details].Customer_Email ELSE '' END),
                    COALESCE(CASE WHEN [Details].Customer_Notes IS NOT NULL THEN [Details].Customer_Notes ELSE '' END))
        AS SOURCE
    ON (SOURCE.[OrderNumber] = TARGET.[Order Number])
    AND (SOURCE.[Product_Id] = TARGET.[Product_Id])
    AND (SOURCE.[Cutomer_Id] = TARGET.[Customer_Id])
    WHEN MATCHED THEN 
    UPDATE SET
        TARGET.[Order Number] = SOURCE.[OrderNumber],
        TARGET.[Product_Id] = SOURCE.[Product_Id]
        -- Handle null
        , TARGET.[Amount] = COALESCE(SOURCE.[Purchase_amt], 0)
        -- Handle duplicates here
    , [TARGET].Customer_ID = COALESCE(SOURCE.[Details].Customer_ID, ''
        OR COALESCE(SOURCE.[Details].Customer_Email,'') != COALESCE(TARGET.[Customer_Email,'') 
        OR COALESCE(SOURCE.[Details].Customer_Notes,'') != COALESCE(TARGET.[Customer_Notes],'')) AND TRUE
    WHEN NOT MATCHED BY TARGET THEN
    INSERT (OrderNumber, ProductId, Amount, Customer_Id, Customer_Email, Customer_Notes)
    VALUES (@OrderNumber, @Product_Id, @Purchase_amt, SOURCE.[Details].Customer_ID, 
            COALESCE(SOURCE.[Details].Customer_Email,''), COALESCE(SOURCE.[Details].Customer_Notes,''));
END;

Best Practices and Additional Considerations

To improve the code further:

• Use meaningful variable names instead of single-letter aliases.
• Handle null values and duplicates correctly to avoid data loss or inconsistencies.
• Implement logging triggers for duplicate detection, as suggested in the Stack Overflow answer.

By following these guidelines and best practices, you’ll be able to create efficient and effective merge statements using user-defined table types and input parameters.

Last modified on 2023-11-04