oracle裡面查比如存儲過程裡面與表SALES有關jobs: SELECT * FROM (SELECT a.name,upper(b.what)AS what,SYS.UTL_MATCH.edit_distance_similarity (a.name,upper(b.what)) AS sim ...
oracle裡面查比如存儲過程裡面與表SALES有關jobs:
SELECT * FROM (SELECT a.name,upper(b.what)AS what,SYS.UTL_MATCH.edit_distance_similarity (a.name,upper(b.what)) AS similarity FROM dba_source a,dba_jobs b WHERE SYS.UTL_MATCH.edit_distance_similarity(a.name,upper(b.what))>80 AND upper(a.text) LIKE '%SALES%' AND b.what NOT LIKE '%dbms_refresh%') ORDER BY 3 DESC;
有自帶相似度函數 SYS.UTL_MATCH.edit_distance_similarity 可以直接用。
mysql8裡面我只查到了一個搜索相關的文檔文檔地址並不適合我自己用,找了一下大佬的文章,發現了一個能用的自定義函數,用於計算字元串相似度。
DELIMITER $$ CREATE DEFINER=`root`@`localhost` FUNCTION `COMPARE_STRING`( s1 text, s2 text) RETURNS int(11) DETERMINISTIC BEGIN DECLARE s1_len, s2_len, i, j, c, c_temp, cost INT; DECLARE s1_char CHAR; DECLARE cv0, cv1 text; SET s1_len = CHAR_LENGTH(s1), s2_len = CHAR_LENGTH(s2), cv1 = 0x00, j = 1, i = 1, c = 0; IF s1 = s2 THEN RETURN 0; ELSEIF s1_len = 0 THEN RETURN s2_len; ELSEIF s2_len = 0 THEN RETURN s1_len; ELSE WHILE j <= s2_len DO SET cv1 = CONCAT(cv1, UNHEX(HEX(j))), j = j + 1; END WHILE; WHILE i <= s1_len DO SET s1_char = SUBSTRING(s1, i, 1), c = i, cv0 = UNHEX(HEX(i)), j = 1; WHILE j <= s2_len DO SET c = c + 1; IF s1_char = SUBSTRING(s2, j, 1) THEN SET cost = 0; ELSE SET cost = 1; END IF; SET c_temp = CONV(HEX(SUBSTRING(cv1, j, 1)), 16, 10) + cost; IF c > c_temp THEN SET c = c_temp; END IF; SET c_temp = CONV(HEX(SUBSTRING(cv1, j+1, 1)), 16, 10) + 1; IF c > c_temp THEN SET c = c_temp; END IF; SET cv0 = CONCAT(cv0, UNHEX(HEX(c))), j = j + 1; END WHILE; SET cv1 = cv0, i = i + 1; END WHILE; END IF; RETURN c; END$$ DELIMITER ; DELIMITER $$ CREATE DEFINER=`root`@`localhost` FUNCTION `SIMILARITY_STRING`(a text, b text) RETURNS double BEGIN RETURN ABS(((COMPARE_STRING(a, b) / length(b)) * 100) - 100); END$$ DELIMITER ;
試了一下還挺好用的,一些邏輯可以自己再適當的修改。
而在gp裡面,我找了許久,發現一個 fuzzystrmatch 看起來比較高檔的函數,這個函數需要安裝:
[gpadmin@SZWPLDB1085 ~]$ psql -d postgres -f $GPHOME/share/postgresql/contrib/fuzzystrmatch.sql
SET
CREATE FUNCTION
CREATE FUNCTION
CREATE FUNCTION
CREATE FUNCTION
CREATE FUNCTION
CREATE FUNCTION
CREATE FUNCTION
CREATE FUNCTION
CREATE FUNCTION
CREATE FUNCTION
然後會在 postgres 庫多出一些函數:
用法在文檔地址