Dynamic Table Update Script for SQL Server

As a developer, we often find ourselves in the need to update columns in one table based on another table with similar column names and data types. This can be particularly challenging when dealing with large datasets or complex database structures.

In this article, we will explore how to create a dynamic script to update all columns in one table (TableB) using the columns from another table (TableA), assuming they have the same name and data type.

Understanding the Challenges

There are several challenges to consider when attempting to update multiple tables dynamically:

Identity columns: These cannot be updated directly, as their values are automatically managed by SQL Server.
Computed columns: Some column calculations cannot be set manually due to constraints or triggers that enforce specific data types or validation rules.
Data type incompatibility: The source and target columns might have different data types, making it impossible to update the values directly.
Constraints and Triggers: Some constraints or triggers might prevent certain values from being inserted into a column.

Approach

To overcome these challenges, we can utilize the sys.columns system view in SQL Server. This allows us to inspect the metadata of each table and generate an update script dynamically based on the available columns.

We will use this approach to create a dynamic script that iterates through the columns of TableA, selects the corresponding columns from TableB, and updates them with the values from TableA.

Creating the Dynamic Script

Here’s how we can achieve this using SQL Server:

DECLARE @srcTable sysname = N'TableA',
        @trgTable sysname = N'TableB',
        @joinCol  sysname = N'id',
        @cols     nvarchar(max),
        @update   nvarchar(max);

SELECT @cols = STRING_AGG(CONVERT(nvarchar(max), 
    CONCAT(N'   trg.', QUOTENAME(src.name), 
           N' = src.', QUOTENAME(src.name))), 
           ',' + char(13) + char(10) + space(4))
WITHIN GROUP (ORDER BY src.column_id)
FROM sys.columns AS src
INNER JOIN sys.columns AS trg
ON src.name = trg.name
INNER JOIN sys.tables AS srct
    ON srct.[object_id] = src.[object_id]
INNER JOIN sys.tables AS trgt
    ON trgt.[object_id] = trg.[object_id]
WHERE src.name &lt;&gt; @joinCol
    AND srct.name = @srcTable
    AND trgt.name = @trgTable;

SELECT @update = CONCAT(N'UPDATE trg SET 
', @cols, N'
FROM dbo.', @srcTable, N' AS src
INNER JOIN dbo.', @trgTable, N' AS trg
ON src.', QUOTENAME(@joinCol), N' = trg.',
          QUOTENAME(@joinCol), N'
WHERE src.ModifiedOn &gt;= DATEADD(DAY,-1,getdate());');

PRINT @update;

This script first declares the necessary variables and then uses the STRING_AGG function to concatenate the column names from TableA into a single string. It does this by joining the metadata of each column (sys.columns) with its corresponding metadata in TableB (sys.tables). The resulting columns are filtered out based on their names.

The second part of the script generates the actual update query using these aggregated column names. We use string concatenation to build the SQL statement, carefully including spaces and newline characters for readability.

Note: As a best practice, it’s recommended to execute this script within an IF block or a test environment before applying it in production environments.

Handling Identity Columns, Computed Columns, Data Type Incompatibility, and Constraints/Triggers

While our approach provides a solid foundation for generating dynamic table updates, we must address the potential pitfalls mentioned earlier:

Identity columns: To handle identity columns that cannot be updated directly, you can use techniques like creating a temporary column to store values from TableA or by using triggers and computed columns.
Computed columns: In case of computed columns that enforce constraints or validation rules due to triggers, you would need to add logic to these functions that allows updating them in accordance with the rule requirements. One might consider adding new computed columns to bypass this constraint.
Data type incompatibility: This scenario is addressed by using TRY_CAST and TRY_CONVERT functions when setting column values from one data type to another.

Using TRY_CAST and TRY_CONVERT for Data Type Incompatibility

Here’s how you could modify the update script to incorporate these checks:

UPDATE trg SET 
   trg.[a] = TRY_CAST(src.[a] AS nvarchar(100))
   ,trg.[b] = TRY_CAST(src.[b] AS nvarchar(50))
   ,trg.[c] = TRY_CONVERT(int, src.[c])
   ,trg.[d] = TRY_CONVERT(bigint, src.[d])
   ,trg.[e] = TRY_CONVERT(bigint, src.[e])
   ,trg.[ModifiedOn] = src.[ModifiedOn]
FROM dbo.TableA AS src
INNER JOIN dbo.TableB AS trg
ON src.[id] = trg.[id]
WHERE src.ModifiedOn >= DATEADD(DAY,-1,getdate());

Conclusion

In this article, we explored the process of creating a dynamic script to update multiple tables in SQL Server based on metadata retrieved from sys.columns. This approach helps you handle identity columns, computed column constraints, data type incompatibilities, and triggers dynamically. By adapting these techniques, you can develop robust scripts for complex table updates that ensure reliability and maintainability.

Next Steps

Test the script: Before applying this script to production tables, execute it on a test environment or schema to identify potential issues.
Monitor database performance: Keep an eye on performance metrics after running this dynamic update script to detect any performance degradation.

SQL Server provides extensive support for advanced table updates and data manipulation. This solution highlights the power of metadata-driven scripting in SQL development.

Last modified on 2024-01-27