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Data modification modification
2022-07-24 13:45:00 【Hua Weiyun】
12.2 Data update
MySQL Support to update the data in the data table , Use UPDATE Statement to update the data records in the data table . All records in the data table can be updated , You can also specify update conditions to update specific records in the data table .
The syntax format of the updated data is as follows ：
UPDATE table_nameSET column1=value1, column2=value2, … , column=valuen[WHERE condition]The syntax format is described as follows ：
·table_name： The name of the table that needs to update the data .
·column1,column2,…,columnn： Field name to be updated .
·value1,value2,…,valuen： The updated value of the field .
·condition： The conditions and restrictions that the updated records need to meet .
among ,WHERE Conditional statements can be omitted , When omitting WHERE Conditional statement , Update all data in the data table .
12.2.1 Update all records in the data table
Update all records in the data table , Only need to UPDATE Of the statement WHERE Omit the condition .
for example , take t_goods In the data sheet t_upper_time The fields are uniformly updated to “2020-12-12 00:00:00”.
mysql> UPDATE t_goods SET t_upper_time = '2020-12-12 00:00:00';Query OK, 12 rows affected (0.11 sec)Rows matched: 12 Changed: 12 Warnings: 0SQL Statement executed successfully , Next look at t_goods Data in the data table .
mysql> SELECT * FROM t_goods;+----+---------------+-----------------+------------+---------+---------+---------------------+| id | t_category_id | t_category | t_name | t_price | t_stock | t_upper_time |+----+---------------+-----------------+------------+---------+---------+---------------------+| 1 | 1 | Women's wear / Women's Boutique | T T-shirt | 39.90 | 1000 | 2020-12-12 00:00:00 || 2 | 1 | Women's wear / Women's Boutique | dress | 79.90 | 2500 | 2020-12-12 00:00:00 || 3 | 1 | Women's wear / Women's Boutique | fleece | 79.90 | 1500 | 2020-12-12 00:00:00 || 4 | 1 | Women's wear / Women's Boutique | A pair of jeans | 0.00 | 0 | 2020-12-12 00:00:00 || 5 | 1 | Women's wear / Women's Boutique | Pleated skirt | 29.90 | 500 | 2020-12-12 00:00:00 || 6 | 1 | Women's wear / Women's Boutique | Woolen coat | 399.90 | 1200 | 2020-12-12 00:00:00 || 7 | 2 | Outdoor sports | Bicycle | 399.90 | 1000 | 2020-12-12 00:00:00 || 8 | 2 | Outdoor sports | Mountain Bike | 1399.90 | 2500 | 2020-12-12 00:00:00 || 9 | 2 | Outdoor sports | Alpenstocks | 59.90 | 1500 | 2020-12-12 00:00:00 || 10 | 2 | Outdoor sports | Riding equipment | 399.90 | 3500 | 2020-12-12 00:00:00 || 11 | 2 | Outdoor sports | Sport coat | 799.90 | 500 | 2020-12-12 00:00:00 || 12 | 2 | Outdoor sports | Skate | 499.90 | 1200 | 2020-12-12 00:00:00 |+----+---------------+-----------------+------------+---------+---------+---------------------+12 rows in set (0.00 sec)t_goods In the data sheet t_upper_time The data of the field is uniformly modified to “2020-12-12 00:00:00”, It indicates that the data is updated successfully .
12.2.2 Update specific data rows in the table
MySQL Support to update specific data rows in the table , here , Need to add WHERE Conditions restrict the updated data records .
for example , take t_goods In the data table id by 2 The commodity name of the data record of is modified to “ Avocado Green Dress ”. First , see t_goods In the data table id by 2 The data of .
mysql> SELECT * FROM t_goods WHERE id = 2;+----+---------------+---------------------+-----------+---------+---------+-------------------+| id | t_category_id | t_category | t_name | t_price | t_stock | t_upper_time |+----+---------------+---------------------+-----------+---------+---------+-------------------+| 2 | 1 | Women's wear / Women's Boutique | dress | 79.90 | 2500 |2020-12-12 00:00:00|+----+---------------+---------------------+-----------+---------+---------+-------------------+1 row in set (0.00 sec)You can see , Before modifying the data id by 2 The recorded commodity name of is “ dress ”. Execute the SQL sentence .
mysql> UPDATE t_goods SET t_name = ' Avocado Green Dress ' WHERE id = 2;Query OK, 1 row affected (0.38 sec)Rows matched: 1 Changed: 1 Warnings: 0SQL Statement executed successfully , Look again t_goods In the data table id by 2 Data record of .
mysql> SELECT * FROM t_goods WHERE id = 2; +----+---------------+---------------+-----------------+---------+---------+-------------------+| id | t_category_id | t_category | t_name | t_price | t_stock | t_upper_time |+----+---------------+---------------+-----------------+---------+---------+-------------------+| 2 | 1 | Women's wear / Women's Boutique | Avocado Green Dress | 79.90 |2500 |2020-12-12 00:00:00|+----+---------------+-------- ------+-----------------+---------+---------+-------------------+1 row in set (0.00 sec)The data has been modified to “ Avocado Green Dress ”, It indicates that the data is modified successfully .
12.2.3 Update the data in a certain range
MySQL Support to update data in a certain range , Can pass BETWEEN…AND Statements or “>”“>=”“<”“<=”“<>”“!=” Equal operator , perhaps LIKE、IN、NOT IN And so on .
1． Use BETWEEN…AND Statement update data
for example , take t_goods In the data table id by 1～6 Of data records t_upper_time The value of the field is updated to “2020-11-11 00:00:00”.
mysql> UPDATE t_goods SET t_upper_time = '2020-11-11 00:00:00' WHERE id BETWEEN 1 AND 6;Query OK, 6 rows affected (0.00 sec)Rows matched: 6 Changed: 6 Warnings: 0SQL Statement executed successfully , Next look at t_goods Records in the data table .
mysql> SELECT * FROM t_goods;+----+---------------+---------------+----------------+---------+---------+--------------------+| id | t_category_id | t_category | t_name | t_price | t_stock | t_upper_time |+----+---------------+---------------+----------------+---------+---------+--------------------+| 1 | 1 | Women's wear / Women's Boutique | T T-shirt | 39.90 | 1000 | 2020-11-11 00:00:00|| 2 | 1 | Women's wear / Women's Boutique | Avocado Green Dress | 79.90 | 2500 | 2020-11-11 00:00:00|| 3 | 1 | Women's wear / Women's Boutique | fleece | 79.90 | 1500 | 2020-11-11 00:00:00|| 4 | 1 | Women's wear / Women's Boutique | A pair of jeans | 0.00 | 0 | 2020-11-11 00:00:00|| 5 | 1 | Women's wear / Women's Boutique | Pleated skirt | 29.90 | 500 | 2020-11-11 00:00:00|| 6 | 1 | Women's wear / Women's Boutique | Woolen coat | 399.90 | 1200 | 2020-11-11 00:00:00|| 7 | 2 | Outdoor sports | Bicycle | 399.90 | 1000 | 2020-12-12 00:00:00|| 8 | 2 | Outdoor sports | Mountain Bike | 1399.90 | 2500 | 2020-12-12 00:00:00|| 9 | 2 | Outdoor sports | Alpenstocks | 59.90 | 1500 | 2020-12-12 00:00:00|| 10 | 2 | Outdoor sports | Riding equipment | 399.90 | 3500 | 2020-12-12 00:00:00|| 11 | 2 | Outdoor sports | Sport coat | 799.90 | 500 | 2020-12-12 00:00:00|| 12 | 2 | Outdoor sports | Skate | 499.90 | 1200 | 2020-12-12 00:00:00|+----+---------------+---------------+----------------+---------+---------+--------------------+12 rows in set (0.01 sec)id by 1~6 Of data records t_upper_time The data of the field was successfully modified to “2020-11-11 00:00:00”.
2． Update data with operators
for example , The commodity price is greater than or equal to 399.90 element , Less than or equal to 799.90 The listing time of RMB products is modified to “2020-06-18 00:00:00”.
mysql> UPDATE t_goods SET -> t_upper_time = '2020-06-18 00:00:00' -> WHERE -> t_price >= 399.90 AND t_price <= 799.90;Query OK, 5 rows affected (0.00 sec)Rows matched: 5 Changed: 5 Warnings: 0SQL Statement executed successfully , see t_goods Data in the data table .
mysql> SELECT * FROM t_goods;+----+---------------+---------------+----------------+---------+---------+--------------------+| id | t_category_id | t_category | t_name | t_price | t_stock | t_upper_time |+----+---------------+---------------+----------------+---------+---------+--------------------+| 1 | 1 | Women's wear / Women's Boutique | T T-shirt | 39.90 | 1000 | 2020-11-11 0:00:00 || 2 | 1 | Women's wear / Women's Boutique | Avocado Green Dress | 79.90 | 2500 | 2020-11-11 00:00:00 || 3 | 1 | Women's wear / Women's Boutique | fleece | 79.90 | 1500 | 2020-11-11 00:00:00 || 4 | 1 | Women's wear / Women's Boutique | A pair of jeans | 0.00 | 0 | 2020-11-11 00:00:00 || 5 | 1 | Women's wear / Women's Boutique | Pleated skirt | 29.90 | 500 | 2020-11-11 00:00:00 || 6 | 1 | Women's wear / Women's Boutique | Woolen coat | 399.90 | 1200 | 2020-06-18 00:00:00 || 7 | 2 | Outdoor sports | Bicycle | 399.90 | 1000 | 2020-06-18 00:00:00 || 8 | 2 | Outdoor sports | Mountain Bike | 1399.90 | 2500 | 2020-12-12 00:00:00 || 9 | 2 | Outdoor sports | Alpenstocks | 59.90 | 1500 | 2020-12-12 00:00:00 || 10 | 2 | Outdoor sports | Riding equipment | 399.90 | 3500 | 2020-06-18 00:00:00 || 11 | 2 | Outdoor sports | Sport coat | 799.90 | 500 | 2020-06-18 00:00:00 || 12 | 2 | Outdoor sports | Skate | 499.90 | 1200 | 2020-06-18 00:00:00 |+----+---------------+---------------+----------------+---------+---------+--------------------+12 rows in set (0.00 sec)The price in 399.90~799.90 The listing time of the product has been modified to “2020-06-18 00:00:00”, It indicates that the data is modified successfully .
Be careful ： When updating data , Other operators are used in the same way , I won't repeat .
3． Use LIKE Statement update data
for example , take t_goods The commodity name in the data sheet contains “ cattle ” The shelf time of the goods of the word is modified to “2020-03-08 00:00:00”.
mysql> UPDATE t_goods SET -> t_upper_time = '2020-03-08 00:00:00' -> WHERE t_name LIKE '% cattle %';Query OK, 2 rows affected (0.00 sec)Rows matched: 2 Changed: 2 Warnings: 0SQL Statement executed successfully , see t_goods Data in the data table .
mysql> SELECT * FROM t_goods;+----+---------------+---------------+---------------+---------+---------+---------------------+| id | t_category_id | t_category | t_name | t_price | t_stock | t_upper_time |+----+---------------+---------------+---------------+---------+---------+---------------------+| 1 | 1 | Women's wear / Women's Boutique | T T-shirt | 39.90 | 1000 | 2020-11-11 00:00:00 || 2 | 1 | Women's wear / Women's Boutique | Avocado Green Dress | 79.90 | 2500 | 2020-03-08 00:00:00 || 3 | 1 | Women's wear / Women's Boutique | fleece | 79.90 | 1500 | 2020-11-11 00:00:00 || 4 | 1 | Women's wear / Women's Boutique | Cowboy | 0.00 | 0 | 2020-03-08 00:00:00 || 5 | 1 | Women's wear / Women's Boutique | Pleated skirt | 29.90 | 500 | 2020-11-11 00:00:00 || 6 | 1 | Women's wear / Women's Boutique | Woolen coat | 399.90 | 1200 | 2020-06-18 00:00:00 || 7 | 2 | Outdoor sports | Bicycle | 399.90 | 1000 | 2020-06-18 00:00:00 || 8 | 2 | Outdoor sports | Mountain Bike | 1399.90 | 2500 | 2020-12-12 00:00:00 || 9 | 2 | Outdoor sports | Alpenstocks | 59.90 | 1500 | 2020-12-12 00:00:00 || 10 | 2 | Outdoor sports | Riding equipment | 399.90 | 3500 | 2020-06-18 00:00:00 || 11 | 2 | Outdoor sports | Sport coat | 799.90 | 500 | 2020-06-18 00:00:00 || 12 | 2 | Outdoor sports | Skate | 499.90 | 1200 | 2020-06-18 00:00:00 |+----+---------------+---------------+---------------+---------+---------+---------------------+12 rows in set (0.00 sec)The trade name is “ Avocado Green Dress ” and “ A pair of jeans ” The listing time of has been modified to “2020-03-08 00:00:00”, It indicates that the data is modified successfully .
4． Use IN Statement update data
for example , take t_goods In the data table id by 7~12 The listing time of the product data of is updated to “2020-10-01 00:00:00”.
mysql> UPDATE t_goods SET -> t_upper_time = '2020-10-01 00:00:00' -> WHERE id IN (7, 8, 9, 10, 11, 12); Query OK, 6 rows affected (0.00 sec)Rows matched: 6 Changed: 6 Warnings: 0SQL Statement executed successfully , see t_goods Data in the data table .
mysql> SELECT * FROM t_goods;+----+---------------+--------------+---------------+---------+---------+---------------------+| id | t_category_id | t_category | t_name | t_price | t_stock | t_upper_time |+----+---------------+--------------+---------------+---------+---------+---------------------+| 1 | 1 | Women's wear / Women's Boutique | T T-shirt | 39.90 | 1000 | 2020-11-11 00:00:00 || 2 | 1 | Women's wear / Women's Boutique | Avocado Green Dress | 79.90 | 2500 | 2020-03-08 00:00:00 || 3 | 1 | Women's wear / Women's Boutique | fleece | 79.90 | 1500 | 2020-11-11 00:00:00 || 4 | 1 | Women's wear / Women's Boutique | A pair of jeans | 0.00 | 0 | 2020-03-08 00:00:00 || 5 | 1 | Women's wear / Women's Boutique | Pleated skirt | 29.90 | 500 | 2020-11-11 00:00:00 || 6 | 1 | Women's wear / Women's Boutique | Woolen coat | 399.90 | 1200 | 2020-06-18 00:00:00 || 7 | 2 | Outdoor sports | Bicycle | 399.90 | 1000 | 2020-10-01 00:00:00 || 8 | 2 | Outdoor sports | Mountain Bike | 1399.90 | 2500 | 2020-10-01 00:00:00 || 9 | 2 | Outdoor sports | Alpenstocks | 59.90 | 1500 | 2020-10-01 00:00:00 || 10 | 2 | Outdoor sports | Riding equipment | 399.90 | 3500 | 2020-10-01 00:00:00 || 11 | 2 | Outdoor sports | Sport coat | 799.90 | 500 | 2020-10-01 00:00:00 || 12 | 2 | Outdoor sports | Skate | 499.90 | 1200 | 2020-10-01 00:00:00 |+----+---------------+--------------+---------------+---------+---------+---------------------+12 rows in set (0.00 sec)t_goods In the data table id by 7~12 The listing time of the product data of is modified to “2020-10-01 00:00:00”, It indicates that the data is modified successfully .
Be careful ：NOT IN The use of statement update data is the same as IN Same statement , It's just IN Statement is to update the data that the value of a field is included in the value list ,NOT IN Statement is to update the data that the value of a field is not included in the value list , I won't repeat .
12.2.4 Update the data that conforms to the regular expression
MySQL Matching regular expressions in requires the use of keywords REGEXP, stay REGEXP Keyword followed by regular expression rules .
for example , take t_goods The commodity names in the data sheet are marked with “ skirt ” The listing time of the ending product record , It is amended as follows “2020-08-08 00:00:00”.
mysql> UPDATE t_goods SET -> t_upper_time = '2020-08-08 00:00:00' -> WHERE t_name REGEXP ' skirt $';Query OK, 2 rows affected (0.21 sec)Rows matched: 2 Changed: 2 Warnings: 0SQL Statement executed successfully , see t_goods Data in the data table .
mysql> SELECT * FROM t_goods;+----+---------------+--------------+---------------+---------+---------+---------------------+| id | t_category_id | t_category | t_name | t_price | t_stock | t_upper_time |+----+---------------+--------------+---------------+---------+---------+---------------------+| 1 | 1 | Women's wear / Women's Boutique | T T-shirt | 39.90 | 1000 | 2020-11-11 00:00:00 || 2 | 1 | Women's wear / Women's Boutique | Avocado Green Dress | 79.90 | 2500 | 2020-08-08 00:00:00 || 3 | 1 | Women's wear / Women's Boutique | fleece | 79.90 | 1500 | 2020-11-11 00:00:00 || 4 | 1 | Women's wear / Women's Boutique | A pair of jeans | 0.00 | 0 | 2020-03-08 00:00:00 || 5 | 1 | Women's wear / Women's Boutique | Pleated skirt | 29.90 | 500 | 2020-08-08 00:00:00 || 6 | 1 | Women's wear / Women's Boutique | Woolen coat | 399.90 | 1200 | 2020-06-18 00:00:00 || 7 | 2 | Outdoor sports | Bicycle | 399.90 | 1000 | 2020-10-01 00:00:00 || 8 | 2 | Outdoor sports | Mountain Bike | 1399.90 | 2500 | 2020-10-01 00:00:00 || 9 | 2 | Outdoor sports | Alpenstocks | 59.90 | 1500 | 2020-10-01 00:00:00 || 10 | 2 | Outdoor sports | Riding equipment | 399.90 | 3500 | 2020-10-01 00:00:00 || 11 | 2 | Outdoor sports | Sport coat | 799.90 | 500 | 2020-10-01 00:00:00 || 12 | 2 | Outdoor sports | Skate | 499.90 | 1200 | 2020-10-01 00:00:00 |+----+---------------+--------------+---------------+---------+---------+---------------------+12 rows in set (0.00 sec)The trade name is “ Avocado Green Dress ” and “ Pleated skirt ” The listing time of the data record of is modified to “2020-08-08 00:00:00”, It indicates that the data is modified successfully .
Be careful ： Knowledge of regular expressions , Readers can refer to relevant learning materials , I won't repeat .
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