MySQL与openGauss 时间操作比较分析
表创建以及数据打桩
-- mysql
CREATE TABLE `a` (
`b_datetime` DATETIME(6) NULL DEFAULT NULL
)
COLLATE='utf8mb4_0900_ai_ci'
ENGINE=InnoDB
;
INSERT INTO a VALUES('2022-07-19 11:44:50.674000');
INSERT INTO a VALUES(NULL);
-- opengauss
CREATE TABLE b (
b_datetime timestamp without time zone
)
WITH (orientation=row, compression=no);
INSERT INTO b (b_datetime)VALUES (timestamp '2022-07-19 11:44:50.674000');
INSERT INTO a VALUES(NULL)
-- mysql时间字段datetime 迁移到opengauss 时间字段类型为timestamp原始数据查询
#MySQL
select * from a;
+----------------------------+
| b_datetime |
+----------------------------+
| 2022-07-19 11:44:50.674000 |
| NULL |
+----------------------------+
2 rows in set (0.00 sec)
===============================================================
#openGauss
select * from test.a;
b_datetime
-------------------------
2022-07-19 11:44:50.674
(2 rows)
查询结果：
mysql 时间输出 年-月-日 时:分:秒.微妙
opengauss 时间输出 年-月-日 时:分:秒.微妙 (微妙低位0被抹除)
TO_CHAR与DATE_FORMAT 时间转换为字符串格式化
#MySQL
SELECT DATE_FORMAT(`b_datetime`, '%Y-%m-%d %H:%i:%s.%f') from `test`.`a`;
+---------------------------------------------------+
| DATE_FORMAT(`b_datetime`, '%Y-%m-%d %H:%i:%s.%f') |
+---------------------------------------------------+
| 2022-07-19 11:44:50.674000 |
| NULL |
+---------------------------------------------------+
2 rows in set (0.00 sec)
===============================================================
#openGauss
SELECT to_char(b_datetime, 'YYYY-MM-DD HH24:MI:SS.FF') from "test"."a" ;
to_char
----------------------------
2022-07-19 11:44:50.674000
(2 rows)查询结果：时间查询结果一致，但是双方对NULL处理方式产生差异。
时间转字符串，对NULL值进行格式化处理（0000-00-00 00:00:00）
#MySQL
select IFNULL(b_datetime, CAST('0000-00-00 00:00:00' AS date)) from `test`.`a`;
+---------------------------------------------------------+
| IFNULL(b_datetime, CAST('0000-00-00 00:00:00' AS date)) |
+---------------------------------------------------------+
| 2022-07-19 11:44:50.674000 |
| NULL |
+---------------------------------------------------------+
2 rows in set, 1 warning (0.00 sec)
IFNULL(v1,v2) ：如果 v1 的值不为 NULL，则返回 v1，否则返回 v2。 懵逼了
select IFNULL(b_datetime, '0000-00-00 00:00:00') from `test`.`a`;
+-------------------------------------------+
| IFNULL(b_datetime, '0000-00-00 00:00:00') |
+-------------------------------------------+
| 2022-07-19 11:44:50.674000 |
| 0000-00-00 00:00:00 |
+-------------------------------------------+
2 rows in set (0.00 sec)
IFNULL 内部不进行类型转换 去掉CAST函数 OK了 ，赞一下。
SELECT DATE_FORMAT(IFNULL(b_datetime, '0000-00-00 00:00:00'), '%Y-%m-%d %H:%i:%s.%f') from `test`.`a`;
+--------------------------------------------------------------------------------+
| DATE_FORMAT(IFNULL(b_datetime, '0000-00-00 00:00:00'), '%Y-%m-%d %H:%i:%s.%f') |
+--------------------------------------------------------------------------------+
| 2022-07-19 11:44:50.674000 |
| NULL |
+--------------------------------------------------------------------------------+
2 rows in set, 1 warning (0.00 sec)
DATE_FORMAT(IFNULL()) 格式化 错误，未到预期结果，郁闷下。DATE_FORMAT 格式化0000-00-00 00:00:00时间返回NULL
SELECT if(`b_datetime` is NULL, '0000-00-00 00:00:00' , DATE_FORMAT(`b_datetime`, '%Y-%m-%d %H:%i:%s.%f')) datetime from `test`.`a`;
+----------------------------+
| datetime |
+----------------------------+
| 2022-07-19 11:44:50.674000 |
| 0000-00-00 00:00:00 |
+----------------------------+
2 rows in set (0.00 sec)
使用if(,,)函数，目标达成。赞美自己
===============================================================
#openGauss
SELECT nvl(to_char(b_datetime, 'YYYY-MM-DD HH24:MI:SS.FF') ,'0000-00-00 00:00:00') datetime from "test"."a" ;
datetime
----------------------------
2022-07-19 11:44:50.674000
0000-00-00 00:00:00
(2 rows)
#备注
NULLIF(value1,value2)函数：在mysql和opengauss中都存在，用法一致。 只有当value1和value2相等时，NULLIF才返回NULL。否则它返回value1。
IFNULL 函数只有MySQL有，IFNULL(v1,v2) 如果 v1 的值不为 NULL，则返回 v1，否则返回 v2。
NVL函数只有opengauss有，NVL(value1,value2) 如果value1为NULL则返回value2，如果value1非NULL，则返回value1。
日期转为时间戳
#MySQL
SELECT UNIX_TIMESTAMP(b_datetime),b_datetime from `test`.`a`;
+----------------------------+----------------------------+
| UNIX_TIMESTAMP(b_datetime) | b_datetime |
+----------------------------+----------------------------+
| 1658202290.674000 | 2022-07-19 11:44:50.674000 |
| NULL | NULL |
+----------------------------+----------------------------+
2 rows in set (0.00 sec)
SELECT UNIX_TIMESTAMP(b_datetime)*1000,b_datetime from `test`.`a`;
+---------------------------------+----------------------------+
| UNIX_TIMESTAMP(b_datetime)*1000 | b_datetime |
+---------------------------------+----------------------------+
| 1658202290674.000000 | 2022-07-19 11:44:50.674000 |
| NULL | NULL |
+---------------------------------+----------------------------+
2 rows in set (0.00 sec)
SELECT UNIX_TIMESTAMP(b_datetime)*1000000,b_datetime from `test`.`a`;
+------------------------------------+----------------------------+
| UNIX_TIMESTAMP(b_datetime)*1000000 | b_datetime |
+------------------------------------+----------------------------+
| 1658202290674000.000000 | 2022-07-19 11:44:50.674000 |
| NULL | NULL |
+------------------------------------+----------------------------+
2 rows in set (0.00 sec)
===============================================================
#openGauss
select extract(epoch from b_datetime) datetime,b_datetime from "test"."a";
datetime | b_datetime
----------------+-------------------------
1658231090.674 | 2022-07-19 11:44:50.674
|
(2 rows)
select extract(epoch from b_datetime)*1000 datetime,b_datetime from "test"."a";
datetime | b_datetime
---------------+-------------------------
1658231090674 | 2022-07-19 11:44:50.674
|
(2 rows)
select extract(epoch from b_datetime)*1000000 datetime,b_datetime from "test"."a";
datetime | b_datetime
--------------------+-------------------------
1.658231090674e+15 | 2022-07-19 11:44:50.674
|
(2 rows)
# 数据分析：
opengauss在微妙转换时，达到16位会进行数据转换，转为科学计数
另mysql和opengauss 再讲时间转换为毫秒时，产生数据差异：
opengauss 1658231090674
mysql 1658202290674.000000
select (1658231090674 - 1658202290674) time_diff ,(1658231090674 - 1658202290674)/(1000*60*60*8) _8hour;
time_diff | _8hour
-----------+--------
28800000 | 1
(1 row)opengauss 和mysql 转换时间戳，基于时区处理。这里要考虑数据库时间的时区属性。