How to Optimize Database Performance for Queries with Multiple LIKE Clauses and Other Operators?

Best Indexing Strategy for Queries with LIKE Clauses

Database performance can be significantly impacted by the presence of LIKE clauses in queries. When dealing with queries like the one provided, selecting the most suitable index can become challenging.

The provided query incorporates LIKE clauses in multiple fields, alongside AND, OR, and IN operators. To address this complexity, it's crucial to understand the limitations of indexing with LIKE conditions.

Referencing the MySQL documentation, we find that B-tree indexes, commonly used for equality and range comparisons, can be leveraged for LIKE comparisons only when the pattern provided doesn't start with a wildcard character.

In this case, since one of the LIKE expressions matches this criterion, a composite index on usage_guidance and name emerges as the best option. This index would facilitate efficient retrieval of results based on the second LIKE expression.

Unfortunately, the full utilization of indexes is hindered by the presence of other LIKE expressions and the NOT IN comparison. To improve performance, consider evaluating the possibility of restructuring the query. By providing the table schema and sample data, experts may offer further insights and suggest ways to optimize the query.

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