Why is Using `SELECT *` in SQL Queries Detrimental to Performance and Maintainability?

*Understanding the Pitfalls of Using `SELECT ` in SQL Queries**

While the adage "avoid premature optimization" is sound advice, using SELECT * in SQL queries introduces significant problems impacting both performance and code maintainability. This analysis details these drawbacks.

Impact on Code Clarity and Maintenance

SELECT * masks the specific columns needed by the application. This makes it difficult to understand the query's purpose and complicates necessary changes. Explicitly listing column names significantly improves readability and simplifies maintenance.

Performance Bottlenecks and Profiling

Retrieving all columns with SELECT * hinders performance profiling. It obscures potential bottlenecks, contradicting the best practice of using profilers to pinpoint and address performance issues.

Vulnerability to Schema Changes

Removing a column from a table will break queries using SELECT *, leading to unexpected errors. Conversely, specifying columns makes your queries resilient to schema modifications.

Excessive Data Transfer

SELECT * in joins retrieves all columns from all tables, leading to unnecessary data transfer and network overhead. Selecting only the required columns minimizes data retrieval and improves performance.

Database Optimization Limitations

Database systems struggle to optimize queries that retrieve all data indiscriminately. Explicit column selection enables optimizations like index usage and reduced processing.

In Summary

Although prioritizing simplicity is crucial, SELECT * undermines this by obscuring code intent, hindering profiling, increasing data transfer, and restricting database optimization. Specifying columns explicitly promotes clarity, flexibility, and better performance, resulting in higher quality and more efficient code.

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