20 Basic SQL queries used in DataStage ?

 

1. Select All Records

   SELECT * FROM employees;

2. Select Specific Columns

   SELECT first_name, last_name FROM employees;

3. Where Clause

   SELECT * FROM employees WHERE department = 'Sales';

4. Order By

   SELECT * FROM employees ORDER BY last_name ASC;

5. Group By

   SELECT department, COUNT(*) FROM employees GROUP BY department;

6. Having Clause

   SELECT department, COUNT(*) FROM employees GROUP BY department HAVING COUNT(*) > 10;

7. Join (Inner Join)

   SELECT e.first_name, d.department_name FROM employees e

   JOIN departments d ON e.department_id = d.department_id;
   

8. Left Join

   SELECT e.first_name, d.department_name 

   FROM employees e
   LEFT JOIN departments d ON e.department_id = d.department_id;
   

9. Right Join

   SELECT e.first_name, d.department_name 

   FROM employees e
   RIGHT JOIN departments d ON e.department_id = d.department_id;
   

10. Full Join

    SELECT e.first_name, d.department_name 

    FROM employees e
    FULL JOIN departments d ON e.department_id = d.department_id;
    

11. Insert Into Table

    INSERT INTO employees (first_name, last_name, department_id) VALUES ('John', 'Doe', 1);

12. Update Records

    UPDATE employees SET department_id = 2 WHERE employee_id = 101;

13. Delete Records

    DELETE FROM employees WHERE employee_id = 101;

14. Distinct Clause

    SELECT DISTINCT department FROM employees;

15. In Clause

    SELECT * FROM employees WHERE department_id IN (1, 2, 3);

16. Between Clause

    SELECT * FROM employees WHERE hire_date BETWEEN '2022-01-01' AND '2022-12-31';

17. Like Clause

    SELECT * FROM employees WHERE first_name LIKE 'J%';

18. Subquery

    SELECT * FROM employees WHERE department_id = (SELECT department_id FROM departments WHERE department_name = 'Sales');

19. Aggregate Functions

    SELECT AVG(salary) FROM employees;

20. Limit Results

    SELECT * FROM employees LIMIT 10;

These SQL queries form the foundation of data manipulation and querying in DataStage and other data warehousing tools.

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