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SQL data types: INT, VARCHAR, CHAR,.pptx
- 1. 1. SQL Data Types(Domain Types)
- 2. Domain Types in SQL • char(n) - Fixed length character string, with user-specified length n. • varchar(n) - Variable length character strings, with user-specified maximum length n. • int - Integer (a finite subset of the integers that is machine- dependent). • Smallint - Small integer (a machine-dependent subset of the integer domain type). • numeric(p,d) - Fixed point number, with user-specified precision of p digits, with d digits to the right of decimal point. (ex., numeric(3,1), allows 44.5 to be stores exactly, but not 444.5 or 0.32) • real, double precision - Floating point and double-precision floating point numbers, with machine-dependent precision. • float(n) - Floating point number, with user-specified precision of at least n digits.
- 4. Create Table Construct • An SQL relation is defined using the create table command: create table r (A1 D1, A2 D2, ..., An Dn, (integrity-constraint1), ..., (integrity-constraintk)) – r is the name of the relation – each Ai is an attribute name in the schema of relation r – Di is the data type of values in the domain of attribute Ai • Example: create table instructor ( ID char(5), name varchar(20), dept_name varchar(20), salary numeric(8,2))
- 5. Integrity Constraints in Create Table: • Types of integrity constraints – primary key (A1, ..., An ) – foreign key (Am, ..., An ) references r – not null – Check Costraint – Unique Constraint • SQL prevents any update to the database that violates an integrity constraint. • Example: create table instructor ( ID int, name varchar(20) not null, dept_name varchar(20), salary int, primary key (ID), foreign key (dept_name) references department);
- 6. And a Few More Relation Definitions • create table student ( ID varchar(5), name varchar(20) not null, dept_name varchar(20), tot_cred numeric(3,0), primary key (ID), foreign key (dept_name) references department);
- 7. • create table course ( course_id varchar(8), title varchar(50), dept_name varchar(20), credits numeric(2,0), primary key (course_id), foreign key (dept_name) references department);
- 8. Referential Integrity • The Value appears in one relation(referencing relation) for a given set of attributes also appears for a certain set of attributes in another relation(referenced relation) .Such conditions are called referential integrity constraints and foreign keys are a form of a referential integrity constraints.
- 9. • Unique constraint Unique ( A1, ..., An ) -No two tuples in the relation can be equal on all the listed attributes • Check constraint Checks(P)- Specifies a predicate P that must be satisfied by every tuple in a relation create table instructor ( ID int, name varchar(20) not null, dept_name varchar(20), salary int check (salary > 50000), primary key (ID), foreign key (dept_name) references department); • Assigning names to constraints salary int ,constraint minsalary check (salary > 50000) • Drop Constraint-alter table instructor drop constraint minsalary;
- 10. 3. SQL Basic Structure
- 11. Basic Query Structure • A typical SQL query has the form: select A1, A2, ..., An from r1, r2, ..., rm where P – Ai represents an attribute – Ri represents a relation – P is a predicate. • The result of an SQL query is a relation.
- 12. The select Clause • The select clause lists the attributes desired in the result of a query – corresponds to the projection operation of the relational algebra • Example: find the names of all instructors: select name from instructor • NOTE: SQL names are case insensitive (i.e., you may use upper- or lower-case letters.) – E.g., Name ≡ NAME ≡ name
- 13. The select Clause (Cont.) • SQL allows duplicates in relations as well as in query results. • To force the elimination of duplicates, insert the keyword distinct after select. • Find the department names of all instructors, and remove duplicates select distinct dept_name from instructor • The keyword all specifies that duplicates should not be removed. select all dept_name from instructor
- 14. The select Clause (Cont.) • An asterisk in the select clause denotes “all attributes” select * from instructor
- 15. The select Clause (Cont.) • The select clause can contain arithmetic expressions involving the operation, +, –, *, and /, and operating on constants or attributes of tuples. – The query: select ID, name, salary/12 from instructor would return a relation that is the same as the instructor relation, except that the value of the attribute salary is divided by 12. – Can rename “salary/12” using the as clause: select ID, name, salary/12 as monthly_salary
- 16. The where Clause • The where clause specifies conditions that the result must satisfy – Corresponds to the selection predicate of the relational algebra. • To find all instructors in Comp. Sci. dept select name from instructor where dept_name = 'Comp. Sci.' • SQL allows the use of the logical connectives and, or, and not • The operands of the logical connectives can be expressions involving the comparison operators <, <=, >, >=, =, and <>. • Comparisons can be applied to results of arithmetic expressions • To find all instructors in Comp. Sci. dept with salary > 70000 select name from instructor where dept_name = 'Comp. Sci.' and salary > 70000
- 17. Where Clause Predicates • SQL includes a between comparison operator • Example: Find the names of all instructors with salary between $90,000 and $100,000 (that is, ≥ $90,000 and ≤ $100,000) select name from instructor where salary between 90000 and 100000 • Tuple comparison select name, course_id from instructor, teaches (Cartesian Product(instructor X teaches)) where (instructor.ID, dept_name) = (teaches.ID, 'Biology');
- 18. teaches relation instructor relation Name Course_id crick BIO-101 crick BIO-301 Output
- 19. The from Clause • The from clause lists the relations involved in the query – Corresponds to the Cartesian product operation of the relational algebra. • Find the Cartesian product (instructor X teaches) select * from instructor, teaches – generates every possible instructor – teaches pair, with all attributes from both relations. – For common attributes (e.g., ID), the attributes in the resulting table are renamed using the relation name (e.g., instructor.ID) • Cartesian product not very useful directly, but useful combined with where-clause condition (selection operation in relational algebra).
- 21. Cartesian product of Instructor and teaches
- 22. Examples • Find the names of all instructors who have taught some course and the course_id select name, course_id from instructor , teaches where instructor.ID = teaches.ID
- 23. •Find the names of all instructors in the Art department who have taught some course and the course_id select name, course_id from instructor , teaches where instructor.ID = teaches.ID and instructor. dept_name = 'Art'
- 24. 4. Operations
- 25. The Rename Operation • The SQL allows renaming relations and attributes using the as clause: old-name as new-name • Find the names of all instructors who have a higher salary than some instructor in 'Comp. Sci'. select distinct T.name from instructor as T, instructor as S where T.salary > S.salary and S.dept_name = 'Comp. Sci.’ T&S copies of instructor(aliases).T and S is called Correlation name Above Question Rewritten as “Find the name of all instructors who earn more than the lowest paid instructor in Comp. Sci dept” • Keyword as is optional and may be omitted instructor as T ≡ instructor T
- 26. String Operations • SQL includes a string-matching operator for comparisons on character strings. The operator like uses patterns that are described using two special characters: – percent ( % ) The % character matches any substring – underscore ( _ ) The _ character matches any character • Find the names of all instructors whose name includes the substring “dar” select name from instructor where name like '%nivas%' • Match the string “100%” like ‘abc %' 🡪 beginning with ”abc” escape '' like ‘abcd%’ beginning with 🡪 ”abcd” in that above we use backslash () as the escape character
- 27. String Operations (Cont.) • Patterns are case sensitive. • Pattern matching examples: – 'Intro%' matches any string beginning with “Intro”. – '%Comp%' matches any string containing “Comp” as a substring. – '_ _ _' matches any string of exactly three characters. – '_ _ _ %' matches any string of at least three characters.
- 28. Ordering the Display of Tuples • List in alphabetic order the names of all instructors select distinct name from instructor order by name • We may specify desc for descending order or asc for ascending order, for each attribute; ascending order is the default. – Example: order by name desc • Can sort on multiple attributes – Example: order by dept_name, name
- 29. Set Operations • Find courses that ran in Fall 2017 or in Spring 2018 (select course_id from section where sem = 'Fall' and year = 2017) union (select course_id from section where sem = 'Spring' and year = 2018) • Find courses that ran in Fall 2017 and in Spring 2018 (select course_id from section where sem = 'Fall' and year = 2017) intersect (select course_id from section where sem = 'Spring' and year = 2018) • Find courses that ran in Fall 2017 but not in Spring 2018 (select course_id from section where sem = 'Fall' and year = 2017) except (select course_id from section where sem = 'Spring' and year = 2018)
- 30. Section Relation (Refer this Relation for previous slide)
- 31. Set Operations (Cont.) • Set operations union, intersect, and except – Each of the above operations automatically eliminates duplicates • To retain all duplicates use the – union all, – intersect all – except all.
- 32. Null Values • It is possible for tuples to have a null value, denoted by null, for some of their attributes • null signifies an unknown value or that a value does not exist. • The result of any arithmetic expression involving null is null – Example: 5 + null returns null • The predicate is null can be used to check for null values. – Example: Find all instructors whose salary is null. select name from instructor where salary is null
- 34. Aggregate Functions • These functions operate on the multiset of values of a column of a relation, and return a value avg: average value min: minimum value max: maximum value sum: sum of values count: number of values
- 35. Aggregate Functions Examples • Find the average salary of instructors in the Computer Science department – select avg (salary) from instructor where dept_name= 'Comp. Sci.'; • Find the total number of instructors who teach a course in the Spring 2018 semester – select count (distinct ID) from teaches where semester = 'Spring' and year = 2018; • Find the number of tuples in the course relation – select count (*) from course;
- 36. Aggregate Functions – Group By • Find the average salary of instructors in each department – select dept_name, avg (salary) as avg_salary from instructor group by dept_name;
- 37. Aggregate Functions – Having Clause • Find the names and average salaries of all departments whose average salary is greater than 42000 • Note: predicates in the having clause are applied after the formation of groups whereas predicates in the where clause are applied before forming groups select dept_name, avg (salary) as avg_salary from instructor group by dept_name having avg (salary) > 42000;