Performance Considerations of Scalar Functions in JOIN or GROUP BY
Scalar functions can be used inside JOIN conditions or GROUP BY clauses, but doing so has important performance trade-offs.
Using scalar functions on columns may prevent MySQL from using indexes, leading to full table scans.
Functions are evaluated for every row processed, which increases CPU usage and slows down queries on large datasets.
In JOINs, applying functions on join keys can significantly degrade performance because the database cannot efficiently match rows using indexed keys.
In GROUP BY, using functions on grouped columns can disable grouping optimizations and force row-by-row computation.
Precompute function results in generated or computed columns that can be indexed.
Avoid applying functions directly on indexed columns in JOIN or GROUP BY clauses.
Rewrite queries to use range or equality conditions instead of function-wrapped columns.
Use indexed expressions or materialized results when frequent filtering or grouping is needed.
In summary: While scalar functions provide flexibility, using them in JOIN or GROUP BY clauses can negatively affect performance by preventing index usage and increasing per-row computation. Precomputing results or using generated columns is the recommended approach for large tables.