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group by clause example


From the following table, write a SQL query to count the number of employees worked under each manager . Return manager ID and number of employees.

Sample table: employees
+-------------+-------------+-------------+----------+--------------------+------------+------------+----------+----------------+------------+---------------+
| EMPLOYEE_ID | FIRST_NAME  | LAST_NAME   | EMAIL    | PHONE_NUMBER       | HIRE_DATE  | JOB_ID     | SALARY   | COMMISSION_PCT | MANAGER_ID | DEPARTMENT_ID |
+-------------+-------------+-------------+----------+--------------------+------------+------------+----------+----------------+------------+---------------+
|         100 | Steven      | King        | SKING    | 515.123.4567       | 2003-06-17 | AD_PRES    | 24000.00 |           0.00 |          0 |            90 |
|         101 | Neena       | Kochhar     | NKOCHHAR | 515.123.4568       | 2005-09-21 | AD_VP      | 17000.00 |           0.00 |        100 |            90 |
|         102 | Lex         | De Haan     | LDEHAAN  | 515.123.4569       | 2001-01-13 | AD_VP      | 17000.00 |           0.00 |        100 |            90 |
|         103 | Alexander   | Hunold      | AHUNOLD  | 590.423.4567       | 2006-01-03 | IT_PROG    |  9000.00 |           0.00 |        102 |            60 |
|         104 | Bruce       | Ernst       | BERNST   | 590.423.4568       | 2007-05-21 | IT_PROG    |  6000.00 |           0.00 |        103 |            60 |
|         105 | David       | Austin      | DAUSTIN  | 590.423.4569       | 2005-06-25 | IT_PROG    |  4800.00 |           0.00 |        103 |            60 |
|         106 | Valli       | Pataballa   | VPATABAL | 590.423.4560       | 2006-02-05 | IT_PROG    |  4800.00 |           0.00 |        103 |            60 |
|         107 | Diana       | Lorentz     | DLORENTZ | 590.423.5567       | 2007-02-07 | IT_PROG    |  4200.00 |           0.00 |        103 |            60 |
|         108 | Nancy       | Greenberg   | NGREENBE | 515.124.4569       | 2002-08-17 | FI_MGR     | 12008.00 |           0.00 |        101 |           100 |
|         109 | Daniel      | Faviet      | DFAVIET  | 515.124.4169       | 2002-08-16 | FI_ACCOUNT |  9000.00 |           0.00 |        108 |           100 |
|         110 | John        | Chen        | JCHEN    | 515.124.4269       | 2005-09-28 | FI_ACCOUNT |  8200.00 |           0.00 |        108 |           100 |
|         111 | Ismael      | Sciarra     | ISCIARRA | 515.124.4369       | 2005-09-30 | FI_ACCOUNT |  7700.00 |           0.00 |        108 |           100 |
|         112 | Jose Manuel | Urman       | JMURMAN  | 515.124.4469       | 2006-03-07 | FI_ACCOUNT |  7800.00 |           0.00 |        108 |           100 |
|         113 | Luis        | Popp        | LPOPP    | 515.124.4567       | 2007-12-07 | FI_ACCOUNT |  6900.00 |           0.00 |        108 |           100 |
|         114 | Den         | Raphaely    | DRAPHEAL | 515.127.4561       | 2002-12-07 | PU_MAN     | 11000.00 |           0.00 |        100 |            30 |
|         115 | Alexander   | Khoo        | AKHOO    | 515.127.4562       | 2003-05-18 | PU_CLERK   |  3100.00 |           0.00 |        114 |            30 |
|         116 | Shelli      | Baida       | SBAIDA   | 515.127.4563       | 2005-12-24 | PU_CLERK   |  2900.00 |           0.00 |        114 |            30 |
|         117 | Sigal       | Tobias      | STOBIAS  | 515.127.4564       | 2005-07-24 | PU_CLERK   |  2800.00 |           0.00 |        114 |            30 |
|  
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Having clause:-
--------------
  having clause is used for allow to filter query result based on aggregate function(sum(),avg(),min(),max(),count()) and grouping(group by).

imp point:-
1.having clause is used to filter data according to condition
2.having clause is used only select clause.
3.having clause is used with group by clause
4.having clause is used after group by clause

syntax:
select column,function(column) from tablename group by column having condition;

exa:select count(*) ,salesman_id  from customer group by salesman_id having count(*)>2 ;



if we use group by ,having, where and order by clause in one query;
so sequnce is:
1.where
2.group by
3.having 
4.order by

Select count(emp_id) , mn_id from employee group by mn_id ;
Select count(emp_id) , mn_id from employee group by mn_id having count(emp_id) between 1 and 5;
select count(*) ,salesman_id  from customer where customer_id <3010 group by salesman_id having count(*)>=2 order by salesman_id desc ;

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difference between where and having clause

where:-1.where caluse is used to filter the data from the table in the specific condition.
       2. where clause cannot cointain aggregate function.
       3.where clause can be used without group by clause.
       4.where clause is used with select,update,delete.
       5.where clause is used before group by clause.
       



having:-1. having clause is uesd for filter the records from the group based on the given condition.
        2. having clause contain aggregate function.
        3. having clause cannot be used without group by clause.
        4. having clause is only used  with select clause.
        5. having clause is used after group by clause.



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assignment:

Q1. From the following table, write a SQL query to find the maximum 
order (purchase) amount in the range 2000 - 6000 (Begin and end values are included.)
 by combination of each customer and order date. 
Return customer id, order date and maximum purchase amount.

Sample table: orders

ord_no      purch_amt   ord_date    customer_id  salesman_id
----------  ----------  ----------  -----------  -----------
70001       150.5       2012-10-05  3005         5002
70009       270.65      2012-09-10  3001         5005
70002       65.26       2012-10-05  3002         5001
70004       110.5       2012-08-17  3009         5003
70007       948.5       2012-09-10  3005         5002
70005       2400.6      2012-07-27  3007         5001
70008       5760        2012-09-10  3002         5001
70010       1983.43     2012-10-10  3004         5006
70003       2480.4      2012-10-10  3009         5003
70012       250.45      2012-06-27  3008         5002
70011       75.29       2012-08-17  3003         5007
70013       3045.6      2012-04-25  3002         5001



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