Select aggregate function and all other columns in MySQL


Let us first create a table −

mysql> create table DemoTable1621
    -> (
    -> StudentId int NOT NULL AUTO_INCREMENT PRIMARY KEY,
    -> StudentName varchar(20),
    -> StudentMarks int
    -> );
Query OK, 0 rows affected (1.69 sec)

Insert some records in the table using insert command −

mysql> insert into DemoTable1621(StudentName,StudentMarks) values('Chris',45);
Query OK, 1 row affected (0.22 sec)
mysql> insert into DemoTable1621(StudentName,StudentMarks) values('Bob',78);
Query OK, 1 row affected (0.13 sec)
mysql> insert into DemoTable1621(StudentName,StudentMarks) values('David',89);
Query OK, 1 row affected (0.16 sec)
mysql> insert into DemoTable1621(StudentName,StudentMarks) values('Adam',87);
Query OK, 1 row affected (0.20 sec)

Display all records from the table using select statement −

mysql> select * from DemoTable1621;

This will produce the following output −

+-----------+-------------+--------------+
| StudentId | StudentName | StudentMarks |
+-----------+-------------+--------------+
|         1 | Chris       |           45 |
|         2 | Bob         |           78 |
|         3 | David       |           89 |
|         4 | Adam        |           87 |
+-----------+-------------+--------------+
4 rows in set (0.00 sec)

Following is the query to select aggregate function −

mysql> select tblData.*,( select max(StudentMarks) from DemoTable1621) as MaximumMarks from DemoTable1621 tblData;

This will produce the following output −

+-----------+-------------+--------------+--------------+
| StudentId | StudentName | StudentMarks | MaximumMarks |
+-----------+-------------+--------------+--------------+
|         1 | Chris       |           45 |           89 |
|         2 | Bob         |           78 |           89 |
|         3 | David       |           89 |           89 |
|         4 | Adam        |           87 |           89 |
+-----------+-------------+--------------+--------------+
4 rows in set (0.00 sec)
raja
Published on 08-Nov-2019 11:12:02
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