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How to Efficiently Calculate String Similarity Percentage in MySQL?

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How to Efficiently Calculate String Similarity Percentage in MySQL?

How to Calculate String Similarity in MySQL

To determine the similarity between two strings stored in MySQL, consider using an efficient algorithm like the Levenshtein distance. This approach calculates the number of single-character edits (additions, removals, or substitutions) required to transform one string into another.

Implementation using MySQL Functions

MySQL provides a series of functions for string manipulation. Here's an example function (levenshtein) that computes the Levenshtein distance between two strings, s1 and s2:

CREATE FUNCTION `levenshtein`(s1 text, s2 text) RETURNS int(11)
DETERMINISTIC
BEGIN
  # Initialize variables
  DECLARE s1_len, s2_len, i, j, c, c_temp, cost INT;
  DECLARE s1_char CHAR;
  DECLARE cv0, cv1 text;
  SET s1_len = CHAR_LENGTH(s1), s2_len = CHAR_LENGTH(s2),
    cv1 = 0x00, j = 1, i = 1, c = 0;

  # Check for edge cases
  IF s1 = s2 THEN
    RETURN 0;
  ELSEIF s1_len = 0 THEN
    RETURN s2_len;
  ELSEIF s2_len = 0 THEN
    RETURN s1_len;
  ELSE
    # Main loop over s1 characters
    WHILE j <= s2_len DO
      SET cv1 = CONCAT(cv1, UNHEX(HEX(j))), j = j + 1;
    END WHILE;

    WHILE i <= s1_len DO
      SET s1_char = SUBSTRING(s1, i, 1), c = i, cv0 = UNHEX(HEX(i)),
        j = 1;

      # Inner loop over s2 characters
      WHILE j <= s2_len DO
        SET c = c + 1;
        IF s1_char = SUBSTRING(s2, j, 1) THEN
          SET cost = 0;
        ELSE
          SET cost = 1;
        END IF;

        SET c_temp = CONV(HEX(SUBSTRING(cv1, j, 1)), 16, 10) + cost;
        IF c > c_temp THEN SET c = c_temp; END IF;
        SET c_temp = CONV(HEX(SUBSTRING(cv1, j + 1, 1)), 16, 10) + 1;
        IF c > c_temp THEN SET c = c_temp; END IF;
        SET cv0 = CONCAT(cv0, UNHEX(HEX(c))), j = j + 1;
      END WHILE;

      SET cv1 = cv0, i = i + 1;
    END WHILE;
  END IF;

  # Return Levenshtein distance
  RETURN c;
END

Calculating Similarity Percentage

With the Levenshtein distance computed, you can calculate the similarity percentage as follows:

CREATE FUNCTION `levenshtein_ratio`(s1 text, s2 text) RETURNS int(11)
DETERMINISTIC
BEGIN
  DECLARE s1_len, s2_len, max_len INT;
  SET s1_len = LENGTH(s1), s2_len = LENGTH(s2);
  IF s1_len > s2_len THEN
    SET max_len = s1_len;
  ELSE
    SET max_len = s2_len;
  END IF;
  RETURN ROUND((1 - LEVENSHTEIN(s1, s2) / max_len) * 100);
END

For example, if you have two strings in MySQL:

SET @a = "Welcome to Stack Overflow";
SET @b = "Hello to stack overflow";

Using the levenshtein_ratio function:

SELECT LEVENSHTEIN_RATIO(@a, @b);

Will return a value representing the similarity percentage between the two strings, eg. 60 for the provided example.

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