How Can I Efficiently Update 120 Million Database Records Without Using an Update Statement?

Efficiently Updating 120 Million Records Using a Non-Update Approach

To enhance the performance of updating a vast table containing 120 million records, it is essential to adopt a non-update approach. This technique involves utilizing a SELECT statement to populate a second table with the required modifications.

Implementation:

1. Create a separate schema to store the second table, ensuring that the clustered index, identity columns, computed columns, and the new INT column are included. Exclude triggers, foreign key constraints, and non-clustered indexes during this creation process.
2. Perform a test insert using 1000 rows to validate the functionality and data accuracy.
3. Truncate the second table and initiate the full insert.
4. Reconstruct all non-clustered primary keys/unique constraints/indexes, foreign key constraints, default constraints, and check constraints as separate batches.
5. Transfer the original table to a backup schema and the second table to the primary schema.
6. Utilize a trigger to log all DML on the original table during the schema transfer process for potential true-up operations.

Benefits:

This non-update approach offers significant advantages over traditional update methods. It eliminates prolonged and inefficient update processes, ensuring a faster and more reliable data modification experience.

Additional Considerations:

1. This approach is ideal for offline operations to minimize potential data integrity issues during live system updates.
2. For large-scale datasets, consider implementing bulk-logged or simple recovery models to optimize performance.
3. Carefully review the requirements and data structure before attempting any modifications to ensure successful and accurate results.

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