Simple SQL Queries (contd.)

Transcription

1 Simple SQL Queries (contd.) Example of a simple query on one relation Query 0: Retrieve the birthdate and address of the employee whose name is 'John B. Smith'. Q0: SELECT BDATE, ADDRESS FROM EMPLOYEE WHERE FNAME='John' AND MINIT='B AND LNAME='Smith Similar to a SELECT-PROJECT pair of relational algebra operations: The SELECT-clause specifies the projection attributes and the WHERE-clause specifies the selection condition However, the result of the query may contain duplicate tuples Slide 2-1

2 SET OPERATIONS SQL has directly incorporated some set operations There is a union operation (UNION), and in some versions of SQL there are set difference (MINUS) and intersection (INTERSECT) operations The resulting relations of these set operations are sets of tuples; duplicate tuples are eliminated from the result The set operations apply only to union compatible relations; the two relations must have the same attributes and the attributes must appear in the same order Slide 2-2

3 SET OPERATIONS (contd.) Query 4: Make a list of all project numbers for projects that involve an employee whose last name is 'Smith' as a worker or as a manager of the department that controls the project. Q4: (SELECT PNAME FROM PROJECT, DEPARTMENT, EMPLOYEE WHERE DNUM=DNUMBER AND MGRSSN=SSN AND LNAME='Smith') UNION (SELECT PNAME FROM WHERE PROJECT, WORKS_ON, EMPLOYEE PNUMBER=PNO AND ESSN=SSN AND NAME='Smith') Slide 2-3

4 Joined Relations Feature in SQL2 Can specify a "joined relation" in the FROMclause Looks like any other relation but is the result of a join Allows the user to specify different types of joins (regular "theta" JOIN, NATURAL JOIN, LEFT OUTER JOIN, RIGHT OUTER JOIN, CROSS JOIN, etc) Slide 2-4

5 Joined Relations Feature in SQL2 (contd.) Examples: Q1: SELECT FNAME, LNAME, ADDRESS FROM EMPLOYEE, DEPARTMENT WHERE DNAME='Research' AND DNUMBER=DNO could be written as: Q1: SELECT FNAME, LNAME, ADDRESS FROM (EMPLOYEE JOIN DEPARTMENT ON DNUMBER=DNO) WHERE DNAME='Research or as: Q1: SELECT FNAME, LNAME, ADDRESS FROM (EMPLOYEE NATURAL JOIN DEPARTMENT WHERE DNAME='Research Slide 2-5

6 Slide 2-6

7 NESTING OF QUERIES A complete SELECT query, called a nested query, can be specified within the WHERE-clause of another query, called the outer query Many of the previous queries can be specified in an alternative form using nesting Query 1: Retrieve the name and address of all employees who work for the 'Research' department. Q1: SELECT FNAME, LNAME, ADDRESS FROM EMPLOYEE WHERE DNO IN (SELECT DNUMBER FROM DEPARTMENT WHERE DNAME='Research' ) Slide 2-7

8 NESTING OF QUERIES (contd.) The nested query selects the number of the 'Research' department The outer query select an EMPLOYEE tuple if its DNO value is in the result of either nested query The comparison operator IN compares a value v with a set (or multi-set) of values V, and evaluates to TRUE if v is one of the elements in V In general, we can have several levels of nested queries A reference to an unqualified attribute refers to the relation declared in the innermost nested query In this example, the nested query is not correlated with the outer query Slide 2-8

9 CORRELATED NESTED QUERIES If a condition in the WHERE-clause of a nested query references an attribute of a relation declared in the outer query, the two queries are said to be correlated The result of a correlated nested query is different for each tuple (or combination of tuples) of the relation(s) the outer query Query 12: Retrieve the name of each employee who has a dependent with the same first name as the employee. Q12: SELECT E.FNAME, E.LNAME FROM EMPLOYEE AS E WHERE E.SSN IN (SELECT ESSN FROM DEPENDENT WHERE ESSN=E.SSN AND E.FNAME=DEPENDENT_NAME) Slide 2-9

10 CORRELATED NESTED QUERIES (contd.) In Q12, the nested query has a different result in the outer query A query written with nested SELECT... FROM... WHERE... blocks and using the = or IN comparison operators can always be expressed as a single block query. For example, Q12 may be written as in Q12A Q12A: SELECT FROM WHERE E.FNAME, E.LNAME EMPLOYEE E, DEPENDENT D E.SSN=D.ESSN AND E.FNAME=D.DEPENDENT_NAME Slide 2-10

11 CORRELATED NESTED QUERIES (contd.) The original SQL as specified for SYSTEM R also had a CONTAINS comparison operator, which is used in conjunction with nested correlated queries This operator was dropped from the language, possibly because of the difficulty in implementing it efficiently Most implementations of SQL do not have this operator The CONTAINS operator compares two sets of values, and returns TRUE if one set contains all values in the other set Reminiscent of the division operation of algebra Slide 2-11

12 CORRELATED NESTED QUERIES (contd.) Query 3: Retrieve the name of each employee who works on all the projects controlled by department number 5. Q3: SELECT FNAME, LNAME FROM EMPLOYEE WHERE ( (SELECT PNO FROM WORKS_ON WHERE SSN=ESSN) CONTAINS (SELECT PNUMBER FROM PROJECT WHERE DNUM=5) ) Slide 2-12

13 CORRELATED NESTED QUERIES (contd.) In Q3, the second nested query, which is not correlated with the outer query, retrieves the project numbers of all projects controlled by department 5 The first nested query, which is correlated, retrieves the project numbers on which the employee works, which is different for each employee tuple because of the correlation Slide 2-13

14 examples Slide 2-14

15 emp ID name address salary depid gender 1 Hanan NC F 2 Ismail NC M 3 Mostafa NC M 4 Maha Dokki F 5 Mohamed heliopolis M 6 Hesham NC M 7 Menna NC F dep ID name bldg 1 IS A 2 CS B 3 DS C 4 IT A

16 SELECT dep.name, emp.name from dep,emp where dep.id=depid order by dep.name, emp.name dep.name CS DS IS IS IS IS IS emp.name Mostafa Maha Hanan Hesham Ismail Menna Mohamed

17 SELECT dep.name, emp.name from dep,emp where dep.id=depid order by dep.name DESC, emp.name DESC dep.name IS IS IS IS IS DS CS emp.name Mohamed Menna Ismail Hesham Hanan Maha Mostafa

18 SELECT name FROM emp Where name like M% ; SELECT name FROM emp Where name like M _ ; name Mostafa Maha Mohamed Menna name Maha

19 SELECT address, gender, Avg(salary) FROM emp GROUP BY address, gender address gender Expr1002 Dokki F 4000 helio M 2000 NC F 1500 NC M

20 SELECT address, gender, Avg(salary), FROM emp GROUP BY address, gender HAVING Count(*)>=3 and avg(salary)>1000; address gender salary NC M 4000

21 SELECT distinct dep.id from dep where dep.id not in (select depid from emp); ID 4

22 SELECT depid from emp right join dep on dep.id=id; depid

23 SELECT dep.id from emp right join dep on dep.id=id; SELECT distinct dep.id from emp left join dep on dep.id=id; depid depid 1 2 3

24 Views Slide 2-24

25 Views in SQL A view is a virtual table that is derived from other tables Allows full query operations A convenience for expressing certain operations Slide 2-25

26 Specification of Views SQL command: CREATE VIEW a table (view) name a possible list of attribute names (for example, when arithmetic operations are specified or when we want the names to be different from the attributes in the base relations) a query to specify the table contents Slide 2-26

27 SQL Views: An Example Specify a different WORKS_ON table CREATE VIEW WORKS_ON_NEW AS SELECT FNAME, LNAME, PNAME, HOURS FROM EMPLOYEE, PROJECT, WORKS_ON WHERE SSN=ESSN AND PNO=PNUMBER GROUP BY PNAME; Slide 2-27

28 Using a Virtual Table We can specify SQL queries on a newly create table (view): SELECT FNAME, LNAME FROM WORKS_ON_NEW WHERE PNAME= Seena ; When no longer needed, a view can be dropped: DROP WORKS_ON_NEW; Slide 2-28

29 Assertions Slide 2-29

30 Constraints as Assertions General constraints: constraints that do not fit in the basic SQL categories (presented in chapter 8) Mechanism: CREAT ASSERTION Components include: a constraint name, followed by CHECK, followed by a condition Slide 2-30

31 Using General Assertions Specify a query that violates the condition; include inside a NOT EXISTS clause Query result must be empty if the query result is not empty, the assertion has been violated Slide 2-31

32 Example 1 Sum of loans taken by a customer does not exceed 100,000 Create Assertion SumLoans Check ( 100,000 >= ALL Select Sum(amount) From borrower B, loan L Where B.loan_number = L.loan_number Group By customer_name ); Must return True or False (not a relation) 32

33 Triggers Slide 2-33

34 Triggers: Introduction Other application constraints are more complex Need for assertions and triggers Examples: Sum of loans taken by a customer does not exceed 100,000 Student cannot take the same course after getting a pass grade in it Age field is derived automatically from the Date-of-Birth field 34

35 Triggers A procedure that runs automatically when a certain event occurs in the DBMS The procedure performs some actions, e.g., Check certain values Fill in some values Inserts/deletes/updates other records Check that some business constraints are satisfied Commit (approve the transaction) or roll back (cancel the transaction) 35

36 Trigger Components Three components Event: When this event happens, the trigger is activated Condition (optional): If the condition is true, the trigger executes, otherwise skipped Action: The actions performed by the trigger Semantics When the Event occurs and Condition is true, execute the Action Lets see how to define these components 36

37 Trigger: Events Three event types Insert Update Delete Two triggering times Before the event After the event Two granularities Execute for each row Execute for each statement 37

38 1) Trigger: Event Trigger name Create Trigger <name> Before After Insert Update Delete ON <tablename> That is the event. Example Create Trigger ABC Before Insert On Students. Create Trigger XYZ After Update On Students. This trigger is activated when an insert statement is issued, but before the new record is inserted This trigger is activated when an update statement is issued and after the update is executed 38

39 Granularity of Event A single SQL statement may update, delete, or insert many records at the same time E.g., Update student set gpa = gpa x 0.8; Does the trigger execute for each updated or deleted record, or once for the entire statement? We define such granularity Create Trigger <name> Before After Insert Update Delete This is the event For Each Row For Each Statement. This is the granularity 39

40 Example: Granularity of Event Create Trigger XYZ After Update ON <tablename> For each statement. This trigger is activated once (per UPDATE statement) after all records are updated Create Trigger XYZ Before Delete ON <tablename> For each row. This trigger is activated before deleting each record 40

41 2) Trigger: Condition This component is optional Create Trigger <name> Before After Insert Update Delete On <tablename> For Each Row For Each Statement When <condition> That is the condition If the employee salary > 150,000 then some actions will be taken Create Trigger EmpSal After Insert or Update On Employee For Each Row When (new.salary >150,000) 41

42 3) Trigger: Action Action depends on what you want to do, e.g.: Check certain values Fill in some values Inserts/deletes/updates other records Check that some business constraints are satisfied Commit (approve the transaction) or roll back (cancel the transaction) In the action, you may want to reference: The new values of inserted or updated records (:new) The old values of deleted or updated records (:old) 42

43 Trigger: Referencing Values In the action, you may want to reference: The new values of inserted or updated records (:new) The old values of deleted or updated records (:old) Trigger body Create Trigger EmpSal After Insert or Update On Employee For Each Row When (new.salary >150,000) Begin if (:new.salary < 100,000) End; Inside When, the new and old should not have : Inside the trigger body, they should have : 43

44 Trigger: Referencing Values (Cont d) Insert Event Has only :new defined Delete Event Has only :old defined Update Event Has both :new and :old defined Before triggering (for insert/update) Can update the values in :new Changing :old values does not make sense After triggering Should not change :new because the event is already done 44

45 Assertions vs. Triggers Assertions do not modify the data, they only check certain conditions Triggers are more powerful because the can check conditions and also modify the data Assertions are not linked to specific tables in the database and not linked to specific events Triggers are linked to specific tables and specific events