Lecture 2 08/26/15. CMPSC431W: Database Management Systems. Instructor: Yu- San Lin
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1 CMPSC431W: Database Management Systems Lecture 2 08/26/15 Instructor: Yu- San Lin yusan@psu.edu Course Website: hcp:// Slides based on McGraw- Hill & Dr. Wang- Chien Lee
2 Outline RelaSonal data model Levels of abstracson Data independence Queries in a DBMS Structure of a DBMS 2
3 RelaSonal Data Model The relasonal data model is the most widely used data model today. Main concept: relason, basically a table with rows and columns. Every relason has a schema, which describes the columns, or fields. Example: Students ( sid: string, name: string, login: string, age: integer, gpa: real) 3
4 RelaSonal Data Model (cont.) An example of the Students relason: Students ( sid: string, name: string, login: string, age: integer, gpa: real) : a for describing a student sid name login age gpa Jones jones@cs Smith smith@ee Smith smith@math Madayan madayan@music Guldu guldu@music
5 Levels of AbstracSon Describes how users see the data Defines logical structures based on data models Defines the files and indexes used 5
6 Conceptual Schema Also called. Describes the stored data in terms of the data model of the DBMS. In relasonal model, describes all, including and. Example: Students(sid: string, name: string, login: string, age: integer, gpa: real) 6
7 Physical Schema Summarizes how the relasons described in the are actually stored on secondary storage devices such as disks and tapes. Example: RelaSons stored as unordered files. The second column of Students is indexed by a B- tree. 7
8 External Schema A collecson of one or more. Allows data access to be customized at the level of individual users or groups of users. Records in view are not stored explicitly, computed as needed. Example: Course_info(cid: string, enrollment: integer) 8
9 Data Independence ApplicaSons insulated from how data is structured and stored. data independence: ProtecSon from changes in logical structure of the data. data independence: ProtecSon from changes in physical structure of data. External Schema View 1 View 2 View 3 Conceptual Schema Physical Schema 9
10 Queries in a DBMS A user might ask: What is the name of the student with student ID 53688? Are there any students with gpa lower than 3.0? sid name login age gpa Jones jones@cs Smith smith@ee Smith smith@math Madayan madayan@music Guldu guldu@music QuesSons involving the data stored in a DBMS are called. 10
11 Queries in a DBMS (cont.) A is used to pose queries. ( ), which supports a rich class of queries, has contributed greatly to the success of relasonal DBMS. and are two formal query languages providing theorescal foundason for relasonal DBMS. 11
12 Example SQL Query What is the name of the student with student ID 53688? sid name login age gpa Jones Smith Smith Madayan Guldu SELECT name FROM Students WHERE sid = ; 12
13 TransacSons A transacson is any one execuson of a user program in a DBMS. Requirements for transacsons: properses 13
14 Structure of a DBMS Index files Data files System Catalog 14
15 QuesSon Time! schema: RelaSons stored as unordered files. The second column of Students is indexed by a B- tree. schema: Students(sid: string, name: string, login: string, age: integer, gpa: real) Courses(cid: string, cname: string, credits: integer) Enrolled(sid: string, cid: string, grade: string) schema: Course_info(cid: string, enrollment: integer) 15
16 QuesSon Time! L: Logical data independence P: Physical data independence Example L/P The ability to change the logical schema without having to change the external schema. Using new storage devices Change the index from Hash to B- Tree Adding new ensses Using different file organizasons or storage structures 16
17 CHAPTER 2: THE ENTITY- RELATIONSHIP MODEL 17
18 ER Model Basics : Real- world object dissnguishable from other objects. An ensty is described in DB using a set of. age sid name Students 18
19 ER Model Basics (cont.) : A collecson of similar ensses. E.g., all employees. All ensses in an ensty set have the same set of. Each ensty set has a minimal set of acributes whose value uniquely idensfy an ensty. 19
20 Don t Forget Sign up the two accounts: GitHub Asana Submit your team informason, along with account informason, by this Friday (8/28) Reading: 1.5, 1.6,
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