mgs 8020 business intelligence relational algebra and structured query language oct 2 2014 n.
Skip this Video
Loading SlideShow in 5 Seconds..
MGS 8020 Business Intelligence Relational Algebra and Structured Query Language Oct 2, 2014 PowerPoint Presentation
Download Presentation
MGS 8020 Business Intelligence Relational Algebra and Structured Query Language Oct 2, 2014

Loading in 2 Seconds...

play fullscreen
1 / 38

MGS 8020 Business Intelligence Relational Algebra and Structured Query Language Oct 2, 2014 - PowerPoint PPT Presentation

  • Uploaded on

MGS 8020 Business Intelligence Relational Algebra and Structured Query Language Oct 2, 2014. SQL. Agenda. Queries. Join. Set Operations. Unary. Restriction. Projection. Binary. Union. Intersection. ?. ?. Difference. UNION. SQL Building Blocks. CREATE, ALTER, DROP

I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
Download Presentation

MGS 8020 Business Intelligence Relational Algebra and Structured Query Language Oct 2, 2014

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
    Presentation Transcript
    1. MGS 8020Business Intelligence Relational Algebra and Structured Query Language Oct 2, 2014

    2. SQL Agenda Queries Join

    3. Set Operations Unary Restriction Projection Binary Union Intersection ? ? Difference UNION

    4. SQL Building Blocks • CREATE, ALTER, DROP • INSERT, DELETE, UPDATE • SELECT • UNION, INTERSECT, MINUS • JOIN • INDEX • VIEWS • Utilities (introduced throughout the examples). • Transaction Management Features • Additional Features

    5. Horizontal Slices • Restriction • Specifying Conditions Algebra: selection or restriction (R) • Unconditional • List all students • select * • from STUDENT; • (Student) • Conditional • List all student with GPA > 3.0 • select * • from STUDENT • where GPA > 3.0; • GPA > 3.0(Student)

    6. List all CIS courses. select * from COURSE where course# like CIS%’; Pattern Matching ‘%’ any string with n characters, n>=0 ‘_’ any single character. x exact sequence of string x. List all CIS 3200 levelcourses. select * from COURSE where course# like ? ;

    7. Specifying Conditions List all students in ... select * from STUDENT where city in (‘Boston’,’Atlanta’); List all students in ... select * from STUDENT where zip not between 60115 and 60123;

    8. Vertical Slices • Projection • Specifying Elements Algebra: projection <A1,A2,...Am> (R) • No Specification • List all information about Students • select * • from STUDENT; • (Student) • Conditional • List IDs, names, and addresses of all students • selectID, name, address • from STUDENT; • ID, name, address(Student)

    9. Does SQL treat Relations as ‘Sets’ • What are the different salaries we pay to our employees? • select salary • from EMPLOYEE; • OR is the following better? • select DISTINCT salary • from EMPLOYEE; • Is the following necessary?

    10. Horizontal and Vertical Query: Lista all student ID, names and addresses who have GPA > 3.0 and age >20. select ID, Name, Address from STUDENT where GPA > 3.0 and DOB < ‘1-Jan-6’ order by Name DESC; Algebra: ID,name, address ( GPA > 3.0 and DOB < ‘1-Jan-74’ (STUDENT) Order by sorts result in descending (DESC) order. Note: The defauld order is ascending (ASC) as in: order by Name;

    11. SQL Agenda Queries Join

    12. Relational Database • A relational database is a collection of data items organized as a set of formally-described tables from which data can be accessed or reassembled in many different ways without having to reorganize the database tables. The relational database was invented by E. F. Codd at IBM in 1970. • The standard user and application program interface to a relational database is the structured query language (SQL). SQL statements are used both for interactive queries for information from a relational database and for gathering data for reports. • A relational database is a set of tables containing data fitted into predefined categories. Each table (which is sometimes called a relation) contains one or more data categories in columns. Each row contains a unique instance of data for the categories defined by the columns. For example, a typical business order entry database would include a table that described a customer with columns for name, address, phone number, and so forth. Another table would describe an order: product, customer, date, sales price, and so forth. A user of the database could obtain a view of the database that fitted the user's needs. For example, a branch office manager might like a view or report on all customers that had bought products after a certain date. A financial services manager in the same company could, from the same tables, obtain a report on accounts that needed to be paid.

    13. Relational Database When creating a relational database, you can define the domain of possible values in a data column and further constraints that may apply to that data value. For example, a domain of possible customers could allow up to ten possible customer names but be constrained in one table to allowing only three of these customer names to be specifiable. The definition of a relational database results in a table of metadata or formal descriptions of the tables, columns, domains, and constraints. Meta is a prefix that in most information technology usages means "an underlying definition or description." Thus, metadata is a definition or description of data and metalanguage is a definition or description of language. A database is a collection of data that is organized so that its contents can easily be accessed, managed, and updated. The most prevalent type of database is the relational database, a tabular database in which data is defined so that it can be reorganized and accessed in a number of different ways. A distributed database is one that can be dispersed or replicated among different points in a network. An object-oriented programming database is one that is congruent with the data defined in object classes and subclasses. SQL (Structured Query Language) is a standard interactive and programming language for getting information from and updating a database. Although SQL is both an ANSI and an ISO standard, many database products support SQL with proprietary extensions to the standard language. Queries take the form of a command language that lets you select, insert, update, find out the location of data, and so forth.

    14. Nesting Queries • SELECT attribute(s) • FROM relation(S) • WHERE attr [not] {in | comparison operator | exists } • ( query statement(s) ); • List names of students who are taking “BA201” • select Name • from Student • where ID in • ( select ID • from REGISTRATION • where course#=‘BA201’);

    15. Sub Queries List all students enrolled in CIS courses select name from STUDENT where studentnum in (select StudentId from REGISTRATION where cno like ‘CIS%’); List all courses taken by Student (Id 1011) select cname from COURSE where cnum _ any (select cno from REGISTRATION where StudentId = 1011);

    16. Sub Queries Who received the highies grade in CIS 814 select StudentId from GRADE where cnum = ‘CIS 814’ and grade >=all (select grade from GRADE where cno = ‘CIS 814’); List all students enrolled in CIS courses. select name from STUDENT S where exists (select * from REGISTRATION where StudentId = S.Studentnum and cno like “CIS%’);

    17. Recursive Queries List all employees who earn more than their immediate supervisor. select E.Emp#, E.title, E.salary from EMPLOYEE, EMPLOYEE M where E.salary > M.salary and E.ManagerEmp# = M.Wmp#;

    18. Summaries and Aggregates Calculate the average GPA select avg. (GPA) from STUDENT, Find the lowest GPA select min (GPA) as minGPA from STUDENT, How many CIS majors? select count (StudentId) from STUDENT where major=‘CIS’; Discarding duplicates select avg (distinct GPA) from STUDENT where major=‘CIS’

    19. Aggregate Functions • COUNT (attr) - a simple count of values in attr • SUM (attr) - sum of values in attr • AVG (attr) - average of values in attr • MAX (attr) - macimum value in attr • MIN (attr) - minimum value in attr • Take effect after data are retrieved from the database • Applied to either the entire resulting relation or groups • Can’t be involved in any query qualifications (where clause) • Would the following query be permitted? • select StudentId • from STUDENT • where GPA = max (GPA);

    20. Missing or Incomplete Information • List all students whose address or telephone number is missing: • select * • from STUDENT • where Address is null or GPA is null; • Truth Table T T T F F F U U U • T F U T F U T F U • ~ a • a & b • a or b

    21. Groupin Results Obtained • Show all students enrolled in each course. • select cno, stno • from REGISTRATION • group by cno; Is this grouping OK? Calculate the average GPA of students by county. • select county, avg (GPA) as County GPA • from STUDENT • group by county; Calculate the average GPA of each class. • select cno, term, year, count (stno) as enrol • from REGISTRATION • group by cno, year, term;

    22. Selections on Groups • Show all CIS courses that are full. • select cno, count (stno) • from REGISTRATION • group by cno • having count (stno) > 29;

    23. Union List students who live in Atlanta or GPA > 3.0 select ID, Name, DOB, Address from STUDENT where Address = ‘Atlanta’ union select ID, Name, DOB, Address from STUDENT where GPA > 3.0; Can we perform a Union on any two Relations ?

    24. Union Compatibility Two relations, A and B, are union-compatible • if 1) A and B contain a same number of attributes, and 2) The corresponding attributes of the two have the same domains • Examples • CIS=Student (ID: Did; Name: Dname; Address: Daddr; Grade: Dgrade); • Senior-Student (SName: Dname; S#: Did; Home: Daddr; Grade: Dgrade); • Course (C#: Dnumber; Title: Dstr; Credits: Dnumber) • Are CIS-Student and Senior-Student union compatible? • Are CIS-Student and Couse union compatible? • What happens if we have duplicate tuples? • What will be the column names in the resulting Relation?

    25. B A Union, Intersect, Minus select CUSTNAME, ZIP from CUSTOMER where STATE = ‘MA’ UNION select SUPNAME, ZIP from SUPPLIER where STATE = ‘MA’ ORDER BY 2; select CUSTNAME, ZIP from CUSTOMER where STATE = ‘MA’ INTERSECT select SUPNAME, ZIP from SUPPLIER where STATE = ‘MA’ ORDER BY 2; select CUSTNAME, ZIP from CUSTOMER where STATE = ‘MA’ MINUS select SUPNAME, ZIP from SUPPLIER where STATE = ‘MA’ ORDER BY 2; B A A B A

    26. Union, Intersect, Minus

    27. SQL Agenda Queries Join

    28. Connecting/Linking Relations • List information about all students and the classes they are taking Student Class What can we use to connect/link Relations? Join: Connecting relations so that relevant tuples can be retrieved.

    29. R1 R2 Join Cartesian Product Student: 30 tuples Class: 4 tuples Total Number of Tuples in the Cartesian Product. ? (match each tuple of student to every tuple of class) Select tuples having identical Student Ids. Expected number of such Tuples: Join Selectivity

    30. Join Forms R1 R2 • General Join Forms • Equijoin • Operator Dependent • Natural Join • Outer Join • Left • Right • Full select s.*.c.* from STUDENT s, CLASS c where s.ID = c. ID; R1 R2 = x > y <> ... select s.*.c.* from STUDENT s, CLASS c where s.ID = c. ID (+);

    31. Grouping Results after Join Calculate the average GPA of each class select course#, avg (GPA) from STUDENT S, CLASS C where S.ID = C.ID group by course#,

    32. Index • There is no order among tuples • Indexes speed up data retrieval • Find all students who live in Atlanta. • How many tuples would you have to search for this query? • What if the table was ‘indexed’? • Index Table Student

    33. Creating and Deleting Indices CREATE [UNIQUE] INDEX index name ON base-relation-name ( attr-name [order], attr-name[order] ...) [CLUSTER]; create unique index student-id on STUDENT ( ID ASC ); create index Address-index on Student (Address); create unique index Name-Age-Index on STUDENT ( Name DESC, Age ); • What are the advantages & disadvantages of Indexing?

    34. View 1 View 2 View N Base Relation 1 Base Relation 2 Relational Views • Relations derived from other relations. • Views have no stored tuples. • Are useful to provide multiple user views.

    35. View Creation • Create View view-name [ ( attr [ , attr ] ...) ] • AS subquery • [ with check option ] ; • DROP VIEW view-name; • Create a view containing the student ID, Name, Age and GPA for those who are qualified to take 300 level courses, i.e., GPA >=2.0.

    36. View Options • With Check Option enforces the query condition for insertion or update • To enforce the GPA >=2.0 condition on all new student tuples inserted into the view • A view may be derived from multiple base relations • Create a view that includes student IDs, student names and their instructors’ names for all CIS 300 students.

    37. View Retrieval Queries on views are the same as that on base relations. Queries on views are expanded into queries on their base relations. select Name, Instructor-Name from CIS300-Student where Name = Instructor-Name; ?

    38. View: Update Update on a view actually changes its base relation(s)! update Qualified-Student set GPA = GPA-0.1 where SID = ‘s3’; insert into Qualified-Student values ( ‘s9’, ‘Lisa’, 4.0 ) insert into Qualified-Student values ( ‘s10’, ‘Peter’, 1.7 ) Why are some views not updateable? What type of views are updateable?