4. Group functions cannot be used in the WHERE clause:
SELECT type_code
FROM d_songs
WHERE SUM (duration) = 100; (this will give an error)
Group functions ignore NULL values. In the example below, the (null) values were not used to find the average overtime rate.

5. You can have more than one group function in the SELECT clause, on the same or different columns.
You can also restrict the group function to a subset of the table using a WHERE clause.
SELECT MAX(salary), MIN(salary), MIN(employee_id)
FROM employees
WHERE department_id = 60;

21. 19 rows exists in employees table from which only 7 are distinct (not repeated)

24. Number of rows in employees table 20 rows while the group function returns 4 rows that is not null values

28. GROUP BY Guidelines
Important guidelines to remember when using a GROUP BY clause are:
If you include a group function (AVG, SUM, COUNT, MAX, MIN, STDDEV, VARIANCE) in a SELECT clause and any other individual columns, each individual column must also appear in the GROUP BY clause.
You cannot use a column alias in the GROUP BY clause.
The WHERE clause excludes rows before they are divided into groups.

29. All column in select clause must be included in group by clause

30. NESTING GROUP FUNCTIONS
Group functions can be nested to a depth of two when GROUP BY is used.
SELECT max(avg(salary))
FROM employees
GROUP by department_id;
How many values will be returned by this query?
The answer is one – the query will find the average salary for eachdepartment, and then from that list, select the single largest value.

37. ROLLUP
In GROUP BY queries you are quite often required to produce subtotals and totals, and the ROLLUP operation can do that for you.
The action of ROLLUP is straightforward: it creates subtotals that roll up from the most detailed level to a grand total, following a grouping list specified in the ROLLUP clause. ROLLUP takes as its argument an ordered list of grouping columns.
First, it calculates the standard aggregate values specified in the GROUP BY clause.
Then, it creates progressively higher-level subtotals, moving from right to left through the list of grouping columns. Finally, it creates a grand total.

38. Rollup for total departments
Rollup for department 10
Rollup for department 20
Rollup for department 50
Rollup for department 60
Rollup for department 80
Rollup for total departments
in query
Rollup for department 90

39. SELECT department_id, job_id, SUM(salary) FROM employees
CUBE
CUBE is an extension to the GROUP BY clause like ROLLUP. It produces cross-tabulation reports.
It can be applied to all aggregate functions including AVG, SUM, MIN, MAX and COUNT.
CUBE
In the following statement the rows in red are generated by the CUBE operation:
SELECT department_id, job_id, SUM(salary)
FROM employees
WHERE department_id < 50
GROUP BY CUBE (department_id, job_id)

42. GROUPING SETS
The point of GROUPING SETS is that if you want to see data from the EMPLOYEES table grouped by (department_id, job_id , manager_id), but also by (department_id, manager_id) and also by
(job_id, manager_id) then you would normally have to write 3 different select statements with the only difference being the GROUP BY clauses.
For the database this means retrieving the same data in this case 3 times, and that can be quite a big overhead. Imagine if your company had 3,000,000 employees. Then you are asking the database to retrieve 9 million rows instead of just 3 million rows, quite a big difference.
So GROUPING SETS are much more efficient when writing complex reports.

43. GROUPING SETS
In the following statement the rows in red are generated by the GROUPING SETS operation:
SELECT department_id, job_id, manager_id, SUM(salary)
FROM employees
WHERE department_id < 50
GROUP BY GROUPING SETS
((job_id, manager_id), (department_id, job_id), (department_id, manager_id))

46. Subquary can retrieve data from more than one table

57. IN Compares if value is in the list of all values returned by the subquery. 

65. MULTIPLE-COLUMN SUBQUERIES
Subqueries can use one or more columns.
A multiple-column subquery can be either pair-wise comparisons or non-pair-wise comparisons.
pair-wise comparisons
SELECT employee_id,
manager_id,
department_id
FROM employees
WHERE (manager_id,department_id)
IN (SELECT manager_id,department_id
WHERE employee_id IN (149,174))
AND employee_id NOT IN (149,174)
The query is listing the employees
whose manager and departments are the same as the manager and
department of employees 149 or 174.

66. non-pair-wise multiple-column subquery
A non-pair-wise multiple-column subquery also uses more than one column in the subquery, but it compares them one at a time, so the comparisons take place in different subqueries. You will need to write one subquery per column you want to compare against when performing non-pair-wise multiple column subqueries.
SELECT employee_id,
manager_id,
department_id
FROM employees
WHERE manager_id IN
(SELECT manager_id
WHERE employee_id IN
(174,199))
AND department_id IN
(SELECT department_id
AND employee_id NOT IN(174,199);

67. Correlated Subqueries
The Oracle server performs a correlated subquery when the subquery references a column from a table referred to in the parent statement.
A correlated subquery is evaluated once for each row processed by the parent statement.
The parent statement can be a SELECT, UPDATE or DELETE statement.
A correlated subquery, however, executes once for each candidate row considered by the outer query. In other words, the inner query is driven by the outer query. The part that makes this
example a correlated subquery is marked in red.
SELECT o.first_name,
o.last_name, o.salary
FROM employees o
WHERE o.salary >
(SELECT AVG(i.salary)
FROM employees i
WHERE i.department_id =
o.department_id);

69. Correlated subquery and WITH clause
The WITH clause retrieves the results of one or more query blocks and stores those results for the user who runs the query.
The WITH clause improves performance.
The WITH clause makes the query easier to read.
The with clause is used to write a very complex query with joins and aggregations used many times
WITH clause
The syntax for the WITH clause is as follows:
WITH subquery-name AS (subquery),
subquery-name AS (subquery)
SELECT column-list
FROM {table | subquery-name | view}
WHERE condition is true;

70. WITH
dept_costs
AS (SELECT d.department_name, SUM(e.salary) AS dept_total
FROM employees e JOIN departments d ON e.department_id = d.department_id
GROUP BY d.department_name),
avg_cost
AS (SELECT SUM(dept_total)/COUNT(*) AS dept_avg
FROM dept_costs)
SELECT *
FROM dept_costs
WHERE dept_total >
(SELECT dept_avg
FROM avg_cost)
ORDER BY department_name;
Display the department name and total salaries for those departments whose total salary is greater than the average salary across departments.

71. SET Operators
Set operators are used to combine the results from different SELECT statements into one single result output.
SET operators can return the rows found in both statements, the rows that are in one table and not the other, or the rows common to both statements.

72. Guidelines for set operators
•The number of columns and the data types of the columns being selected by the SELECT statements in the queries, must be identical in all the SELECT statements used in the query.
•The names of the columns need not be identical.
•Column names in the output are taken from the column names in the first SELECT statement. So any column aliases should be entered in the first statement as you would want to see them in the finished report.

73. the following two lists will be used throughout this lesson:
A = {1, 2, 3, 4, 5}
B = {4, 5, 6, 7, 8}
Or in reality: two tables, one called A and one called B.
UNION
The UNION operator returns all rows from both tables, after eliminating duplicates.
SELECT a_id
FROM a
UNION
SELECT b_id
FROM b;
The result of listing all elements in A and B
eliminating duplicates is {1, 2, 3, 4, 5, 6, 7, 8}.
If you joined A and B you would get only {4, 5}.
You would have to perform a full outer join to get
the same list as above.
(similar to full outer join)

74. UNION ALL The UNION ALL operator returns all rows from both
tables, without eliminating duplicates.
SELECT a_id
FROM a
UNION ALL
SELECT b_id
FROM b;
The result of listing all elements in A and B without
eliminating duplicates is {1, 2, 3, 4, 5, 4, 5, 6, 7, 8}.
Observe the difference between
UNION and UNION ALL

75. INTERSECT
The INTERSECT operator returns all rows common to both tables.
SELECT a_id
FROM a
INTERSECT
SELECT b_id
FROM b;
The result of listing all elements found in both A
and B is {4, 5}.

76. MINUS The MINUS operator returns all rows found in one
table but not the other.
SELECT a_id
FROM a
MINUS
SELECT b_id
FROM b;
The result of listing all elements found in
A but not B is {1, 2, 3},
and B MINUS A would give {6, 7, 8}.

77. TO_CHAR(null) – matching the select list
SELECT location_id, department_name "Department", TO_CHAR(NULL) "Warehouse"
FROM departments
UNION
SELECT location_id, TO_CHAR(NULL) "Department", warehouse_name
FROM warehouses;
This query will SELECT the location_id and the department_name from the
departments table and it includes a reference to a NULL value as a “stand-in”
for a column in the warehouses table. The column in the warehouses table is
a varchar2 column, to a call to the TO_CHAR function is used to ensure the
datatypes of all columns in the two statements match. A similar reference has
been made to a column in the SELECT from warehouses clause. The result
can be seen on the next slide.

78. SELECT location_id, department_name "Department", TO_CHAR(NULL) "Warehouse"
FROM departments
UNION
SELECT location_id, TO_CHAR(NULL) "Department", warehouse_name
FROM warehouses;

79. SEE YOU NEXT MEETING Raafat Rashad GOOD LUCK raafat_rashad@yahoo.co.uk