SELECT * vs. SELECT Columns: How Does Column Selection Impact Database Query Performance?

*Database query performance: SELECT compared with SELECT Columns**

In a database query, choosing whether to retrieve the entire record (SELECT ) or just specific columns (SELECT column_1, column_2, ...) affects performance. While SELECT seems convenient, it also introduces potential efficiency issues.

I/O and memory considerations

When executing a SELECT * query, the database engine usually retrieves the entire record. Therefore, the I/O overhead is the same regardless of the number of columns requested. However, if the query only requires a subset of columns, SELECT column_1, column_2, ... can avoid unnecessary retrieval, thereby reducing network overhead.

In addition, SELECT * incurs memory overhead. After retrieving the tuple, the database engine must discard the unnecessary columns. This process is computationally expensive, making SELECT column_1, column_2, ... more memory efficient.

Performance impact

Using SELECT * instead of selecting specific columns can cause some performance issues:

• Excessive data retrieval and transfer: Extracting unnecessary data increases network bandwidth usage and slows down data processing.
• Reduced index utilization: Non-clustered indexes can improve performance by covering a subset of columns. SELECT * prevents the optimizer from considering such indexes.
• Increased query duration: The additional I/O and memory operations associated with SELECT * cause the query to execute longer.

Conclusion

For best query performance, SELECT * must be avoided. Instead, carefully select the columns required for a specific operation. Doing so minimizes data retrieval, reduces network and memory usage, and increases query speed and efficiency. Remember, the rule of thumb is to always specify necessary columns in SELECT queries to avoid performance degradation and maximize query efficiency.

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