1、参考别人的相似度函数

CREATE FUNCTION levenshtein_distance(s1 VARCHAR(255), s2 VARCHAR(255))
RETURNS INT
DETERMINISTIC
BEGINDECLARE s1_len, s2_len, i, j, c,cost,cmin INT;DECLARE s1_char CHAR;DECLARE cv0, cv1 VARCHAR(255);SET s1_len = CHAR_LENGTH(s1), s2_len = CHAR_LENGTH(s2), cv1 = '', j = 1, i = 1, c = 0;IF s1 = s2 THENRETURN 0;ELSEIF s1_len = 0 THENRETURN s2_len;ELSEIF s2_len = 0 THENRETURN s1_len;ELSEWHILE j <= s2_len DOSET cv1 = CONCAT(cv1, UNHEX(HEX(j))), j = j + 1;END WHILE;WHILE i <= s1_len DOSET s1_char = SUBSTRING(s1, i, 1), c = i, cv0 = UNHEX(HEX(i)), j = 1;WHILE j <= s2_len DOSET c = c + 1;IF s1_char = SUBSTRING(s2, j, 1) THENSET cost = 0;ELSESET cost = 1;END IF;SET cmin = CONV(HEX(SUBSTRING(cv1, j, 1)), 16, 10) + cost;SET c = IF(c > cmin, cmin, c) + 1;SET cv0 = CONCAT(cv0, UNHEX(HEX(c))), j = j + 1;END WHILE;SET cv1 = cv0, i = i + 1;END WHILE;END IF;RETURN c;
END;

2、使用

  select * from  com_base_shangpin  ORDER BY levenshtein_distance(spdm, '000000') ASC LIMIT 1000;

用是能用，就是数据多了超级慢