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MIS 3053 Database Design & Applications The University of Tulsa Professor: Akhilesh Bajaj RM/SQL Lecture 1 ©Akhilesh Bajaj, 2000, 2002, 2003, 2004. All.

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Presentation on theme: "MIS 3053 Database Design & Applications The University of Tulsa Professor: Akhilesh Bajaj RM/SQL Lecture 1 ©Akhilesh Bajaj, 2000, 2002, 2003, 2004. All."— Presentation transcript:

1 MIS 3053 Database Design & Applications The University of Tulsa Professor: Akhilesh Bajaj RM/SQL Lecture 1 ©Akhilesh Bajaj, 2000, 2002, 2003, 2004. All rights reserved.

2 Goals for Today Learn the basics of the relational model Learn the notions of superkeys, candidate keys and primary keys Get started with relational algebra - Basics of relational algebra - The select operation -The project operation -The assignment operation

3 What is a Data Model? It is a collection of conceptual tools for describing data, data relationships, data semantics and consistency constraints. Essentially answers the following questions: - What is data? - How are the data related to each other? - How can we query the data and change it? - How do we ensure that the data represents a correct view of the real world (data integrity)? Examples of data models include the relational model, the ER model, the network model and the hierarchical model. The network and hierarchical models are found on older mainframe systems (usually in large organizations).

4 Basics of the Relational Model Primary model used today for data-processing applications Database systems like Oracle, Sybase, Informix, etc. support this model. Has strong theory associated with it. Proposed in 1970-71 and became mainstream in the early 1980-s onwards. Still the most robust model out there, many experts predict it will be around for tens of years more.

5 Basics of the Relational Model A database represents information about the enterprise. Information is structured, so as to be easy to store, retrieve and modify. In the relational model, the information is structured by means of a relational schema. A relational schema consists of the table names (also called relation names), the column names (or attribute names), the primary keys of each table and a few more objects we will study. In the ER module, we learnt how to capture user requirements in the ER model, and to map this to a simple relational schema.

6 Basics of the Relational Model Example of a relational schema: PROFESSORS(fac_id, f_name, research_interest) COURSES(c_num, c_name, num_credits) TEACH(fac_id, c-num) Once we have a schema, the actual information is stored in the form of rows (tuples). Each row represents a “piece” or record of information that represents a part of the real world. Example of rows: PROFESSORS Fac_idF_nameResearch_interest 1Akhilesh Bajaj Information Systems 2 Sudha RamDatabase Modeling Rows or records or tuples Important A table can never have duplicate rows.

7 Basics of the Relational Model Each attribute in a table has a domain. The domain is the set of values that the attribute can take. This is analogous to domains in the ER model. An attribute can have only one value at a time in a row, and the value is atomic (cannot be further broken up). It is possible for attributes to have a null value, provided they are not part of the primary key of the table. Null can mean one of two things, we don’t know which. E.g., a dependent value being null could mean that there are no dependents, OR that there are dependents but we don’t have information on them.

8 Superkeys, Candidate Keys, Primary Keys A superkey is any set of attributes in a table, such that no 2 rows can have the same values when we consider all the attributes in the superkey together. E.g., (s_id, name, address, GPA, age), (s_id, name), (s_id, address), (s_id, GPA) are all sets of attributes that are examples of superkeys for the table STUDENTS. A candidate key is a superkey of a table such that no subset of these attributes is also a superkey. E.g., (s_id) is a candidate key of STUDENTS. A table can have several superkeys and more than one of these may be candidate keys. A primary key is selected from these candidate keys. Usually, if the table represents real-world objects, we designate an id as a primary key.

9 Superkeys, Candidate Keys, Primary Keys All possible attribute sets of a table T All possible superkeys of a table T All possible candidate keys of a table T One set of attributes that make up the primary key of table T

10 Basics of Relational Algebra Relational algebra is the query language of the relational model. Recall that in a data model, we need to be able to ask questions of the data also. We did not cover this in the ER model. Query languages are procedural or non-procedural. In a procedural language, the user instructs the database system to perform a series of steps. Relational Algebra is procedural. In a non-procedural language, the user describes the information desired, without giving a specific procedure for obtaining that information. SQL is non procedural.

11 Basics of Relational Algebra The fundamental operations in relational algebra are: - Select -Project -Assign -Union - Set Difference - Cartesian Product - Rename [There are other operations as well.] In relational algebra, the input to an operation is one or two relations (or tables), and the output of an operation is one relation. Select, project, rename are unary operators (input is one table) Union, set difference, cartesian product are binary operators (input is two tables).

12 The Select Operation Operator: SELECT or Works on: One table Semantics: End result is the set of rows from the table that satisfy a given condition. Condition: based on some attribute values and >,<, =, <>, >=, <=, AND, OR, NOT. E.g., name=“Akhilesh” AND research_interest = “MIS” is a condition. Syntax: SELECT CONDITION ( INPUT_TABLE) The above expression yields an output table whose rows satisfy the condition. The columns remain the same. E.g., PROFESSORS

13 The Project Operation Operator: PROJECT or Works on: One table Semantics: End result is the set of columns from the table that are specified. Column Specification: column-name1, column-name2, …. Syntax: PROJECT COLUMN_NAMES ( INPUT_TABLE) The above expression yields an output table that contains only the columns that are specified. E.g., PROJECT f_name (PROFESSORS) yields as output a table with only one column: f_name. Has 3 columns 

14 The Assignment Operation Operator: ASSIGN or Works on: Two tables Semantics: The relational algebra expression on the right is assigned to the table on the left (usually a temporary table). This allows us to write an expression as a sequence of assignments. Syntax: temp_table1 Relational Algebra Expression E.g., temp1 PROJECT f_name (PROFESSORS) assigns the expression on the right to temp1.


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