How Can PostgreSQL's pg_trgm Module Efficiently Find Similar Strings in Large Datasets?

Finding Similar Strings with PostgreSQL Quickly

One of the common requirements in text retrieval is to find strings that are similar to a given input string. PostgreSQL provides the pg_trgm module for this purpose. However, when dealing with large datasets, the brute-force approach of calculating similarity scores for every pair of strings can become inefficient.

The conventional approach involves creating a GiST index on the name column using gist_trgm_ops as the index operator. The problem with this approach is that it requires calculating similarity scores for every pair of elements, resulting in a quadratic time complexity.

A more efficient solution is to use the % operator provided by pg_trgm. By setting the pg_trgm.similarity_threshold parameter to a predefined value (e.g., 0.8), the optimizer can use the trigram GiST index to filter out candidate pairs that are below the specified similarity threshold. This significantly reduces the number of similarity calculations required and improves the query performance.

SET pg_trgm.similarity_threshold = 0.8;

SELECT similarity(n1.name, n2.name) AS sim, n1.name, n2.name
FROM   names n1
JOIN   names n2 ON n1.name <> n2.name
               AND n1.name % n2.name
ORDER  BY sim DESC;

This optimized query uses the % operator to pre-filter the candidate pairs before calculating the similarity scores, significantly improving the query performance.

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