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How to write efficient TSQL

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Over the past two months, I’ve authored a six-part blog series that delves into common errors found in SQL Server. This month, my focus has shifted towards crafting an article on T-SQL. When it comes to composing T-SQL (Transact-SQL) code, there exist a multitude of vital considerations developers should bear in mind to guarantee that their code remains efficient, maintainable, and secure.

  1. Performance Optimization:
    • Use proper indexing to speed up query execution.
    • Minimize the use of complex subqueries and functions that can slow down queries.
    • Avoid using SELECT * as it can lead to unnecessary data transfer and slow down queries.
  2. Avoid Cursors:
    • Cursors should be avoided whenever possible, as they can be slow and resource-intensive. Instead, try to use set-based operations.
  3. Error Handling:
    • Implement error handling to capture and handle exceptions gracefully using TRY…CATCH blocks.
    • Log errors and provide informative error messages for troubleshooting.
  4. Parameterization:
    • Always use parameterized queries to prevent SQL injection attacks.
    • Avoid dynamic SQL unless it’s necessary and safe.
  5. Normalization:
    • Design your database schema with proper normalization to minimize data redundancy and maintain data integrity.
  6. Transactions:
    • Use transactions to ensure data consistency and to make a series of related changes atomic (all or nothing).
  7. Code Readability:
    • Use meaningful table and column names.
    • Indent and format your code consistently to improve readability.
    • Use comments to explain complex logic or the purpose of the code.
  8. Testing and Validation:
    • Test your T-SQL code thoroughly on different data sets and scenarios.
    • Validate the results to ensure accuracy.
  9. Maintenance and Version Control:
    • Use version control systems (e.g., Git) to manage your T-SQL code.
    • Document your code and changes for easy maintenance.
  10. Data Type Selection:
    • Choose appropriate data types for your columns to minimize storage and improve performance.
  11. Plan Caching:
    • Be aware of query plan caching and the impact of parameter sniffing. Use OPTION (RECOMPILE) when necessary to force recompilation of query plans.
  12. Resource Management:
    • Be mindful of resource consumption, especially in terms of memory and CPU, when writing complex queries.
  13. Join Types:
    • Understand different join types (INNER JOIN, LEFT JOIN, etc.) and choose the appropriate one for your query.
  14. Indexes and Statistics:
    • Keep statistics updated to help the query optimizer make better decisions.
    • Monitor and manage indexes to ensure they are effective.
  15. Security:
    • Follow the principle of least privilege when granting permissions to database objects.
    • Implement role-based security and avoid using sa (system administrator) account in application connections.
  16. Scalability:
    • Design your database and queries to be scalable as data volume grows.
  17. Consistency:
    • Follow naming conventions and coding standards consistently throughout your T-SQL codebase.
  18. Monitoring and Tuning:
    • Use tools like SQL Server Profiler and Database Engine Tuning Advisor to identify performance issues and optimize queries.
  19. Documentation:
    • Document your database schema, stored procedures, and any custom functions for future reference and collaboration with other developers.
  20. Version Compatibility:
    • Be aware of the SQL Server version you are targeting and ensure your code is compatible with that version.

These considerations are essential for writing efficient, secure, and maintainable T-SQL code. Adhering to best practices and continuously improving your skills will lead to better database performance and a more robust application.

The post How to write efficient TSQL appeared first on SQL Server Citation.

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