Optimizing Index Selection for LIKE Queries

Database performance can significantly suffer when LIKE clauses are involved, as conventional indexes cannot efficiently support wildcard searches. This is particularly evident in queries with multiple clauses and operators.

In the provided query, you have a complex expression with LIKE, OR, and NOT IN conditions. To determine the best index, consider the following:

LIKE Operator

LIKE expressions can only utilize indexes if the search pattern is a constant string without leading wildcards. In your query, the LIKE comparisons satisfy this condition for the usage_guidance column.

Multiple Clauses

Queries with multiple clauses can benefit from composite indexes. In your case, combining the name and usage_guidance columns in an index would allow efficient searching on both LIKE expressions.

Recommended Index

Based on the above considerations, the ideal index for your query is:

CREATE INDEX idx_tags_LIKE ON tags (usage_guidance, name);

This index will enable faster query execution by utilizing the index for the LIKE comparison on usage_guidance and exploiting the name column for sorting and filtering.

Additional Optimization Tips

To further enhance performance, consider the following:

• Limit the use of wildcard searches, as they are highly inefficient.
• Rewrite the query to use full-text indexing if necessary.
• Cache the results of frequent LIKE queries for improved response times.

By implementing these recommendations, you can significantly optimize your LIKE queries and improve the overall performance of your database system.