Use GROUP BY and DATE() for this. Let us first create a table −
mysql> create table DemoTable1358 -> ( -> PurchaseDate datetime, -> ProductPrice int -> ); Query OK, 0 rows affected (1.59 sec)
Insert some records in the table using insert command. Here, we have inserted date records, with some records with similar dates −
mysql> insert into DemoTable1358 values('2019-09-20 12:34:00', 450);
Query OK, 1 row affected (0.23 sec)
mysql> insert into DemoTable1358 values('2019-09-21 11:00:00', 1050);
Query OK, 1 row affected (0.27 sec)
mysql> insert into DemoTable1358 values('2018-09-21 02:10:00', 2050);
Query OK, 1 row affected (0.18 sec)
mysql> insert into DemoTable1358 values('2019-09-21 05:20:40', 5050);
Query OK, 1 row affected (0.23 sec)
mysql> insert into DemoTable1358 values('2016-09-21 04:10:56', 1000);
Query OK, 1 row affected (0.18 sec)Display all records from the table using select statement −
mysql> select * from DemoTable1358;
This will produce the following output −
+---------------------+--------------+ | PurchaseDate | ProductPrice | +---------------------+--------------+ | 2019-09-20 12:34:00 | 450 | | 2019-09-21 11:00:00 | 1050 | | 2018-09-21 02:10:00 | 2050 | | 2019-09-21 05:20:40 | 5050 | | 2016-09-21 04:10:56 | 1000 | +---------------------+--------------+ 5 rows in set (0.00 sec)
Following is the query to sum ProductPrice values from the same day −
mysql> select PurchaseDate,sum(ProductPrice) from DemoTable1358 -> group by date(PurchaseDate);
This will produce the following output −
+---------------------+-------------------+ | PurchaseDate | sum(ProductPrice) | +---------------------+-------------------+ | 2019-09-20 12:34:00 | 450 | | 2019-09-21 11:00:00 | 6100 | | 2018-09-21 02:10:00 | 2050 | | 2016-09-21 04:10:56 | 1000 | +---------------------+-------------------+ 4 rows in set (0.00 sec)