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How Can I Efficiently Update 120 Million Database Records Without Using an Update Statement?
- Patricia ArquetteOriginal
- 2025-01-01 00:34:09562browse
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:
- 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.
- Perform a test insert using 1000 rows to validate the functionality and data accuracy.
- Truncate the second table and initiate the full insert.
- Reconstruct all non-clustered primary keys/unique constraints/indexes, foreign key constraints, default constraints, and check constraints as separate batches.
- Transfer the original table to a backup schema and the second table to the primary schema.
- 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:
- This approach is ideal for offline operations to minimize potential data integrity issues during live system updates.
- For large-scale datasets, consider implementing bulk-logged or simple recovery models to optimize performance.
- Carefully review the requirements and data structure before attempting any modifications to ensure successful and accurate results.
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