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I had a table of names, containing 200,000 rows. This has now been updated to include over 11 million rows.

The table is queried using a SOUNDS LIKE 'str' and the result is then passed through levenshtein_ratio() [a custom function that compares string similarity]. This worked quickly with the 200,000 rows, but with 11 million rows it is now taking two seconds.

I believe I can make this work a lot quicker by saving the soundex of each name, indexing that column, and then searching by this. But am concerned that the levenshtein_ratio() will be slow as it is now being few with potentially 2,000-3,000 result.

I am interested to know how database professional would consider approaching this issue. In particular, I am wondering if it might be better to compute the levenshtein_ratio in PHP.

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