Database System Concepts and Architecture

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1 Database System Concepts and Architecture Different Database Models: The relational database model is the most widespread and used of all the database models. In relational databases, data is stored in tables (rows and columns) and data is extracted from them by selecting columns and rows that satisfy user-specified conditions. Other major and older database models are: Hierarchical Model: Data is stored hierarchically with parent-child relationships between data items. A hierarchical database consists of sets of records called record types organized as nodes of a tree. Record types and records correspond to tables and rows in relational databases Example of simple databases that stored information about customers, their orders and their preferences: Customers Orders Customers Preferences Customers is a record type that stores customer information in records, one record per customer. Each customer record is associated with records of two

2 types Orders and Preferences. Each customer can have multiple orders and preferences. Each record in Orders is associated with an order of the associated customer and each record in Preferences corresponds to a preference of the associated customer. Consider the example of a student/course/grade data as described in: Mr. Eric Tachibana 123 Kensington Chemistry 102 C+ Name Address Course Grade Mr. Eric Tachibana 123 Kensington Chemistry 102 C+ Mr. Eric Tachibana 123 Kensington Chinese 3 A Mr. Eric Tachibana 123 Kensington Data Structures B Mr. Eric Tachibana 123 Kensington English 101 A Ms. Tonya Lippert 88 West 1st St. Psychology 101 A Mrs. Tonya Ducovney Ms. Tonya Lippert 100 Capitol Ln. Psychology 101 A 88 West 1st St. Human Cultures A Ms. Tonya Lippert 88 West 1st St. Chemistry 102 A Represent the following information using a hierarchical model? What problem do you see?

3 How can we create a record for Ms Sharon Wood 23 East Avenue, who has not enrolled for any courses yet? Types of relationships: Redundancy would occur because hierarchical databases handle one-to-many relationships well but do not handle many-to-many relationships well. This is because a child may only have one parent. However, in many cases you will want to have the child be related to more than one parent. For instance, the relationship between student and class is a "many-to-many". Not only can a student take many subjects but a subject may also be taken by many students. How would you model this relationship simply and efficiently using a hierarchical database? The answer is that you wouldn't. Network Databases: The network database model is based on set theory. A network database consists of a family of sets and each set consists of data called records. Sets and records correspond to the tables and rows in a relational model. A record can belong to more than one set and this defines a relationship. The network formed by these relationships is what gives this database model its name. The network model is very similar to the hierarchical model actually. In fact, the hierarchical model is a subset of the network model. However, instead of using a single-parent tree hierarchy, the network model uses set theory to provide a treelike hierarchy with the exception that child tables were allowed to have more than one parent. This allowed the network model to support many-to-many relationships, but it also made it more difficult to implement and maintain. But they increase the complexity of the database. Object Databases The object database paradigm allows users to structure retrieve and update data in terms of objects in the application domain. The object database model, based

4 on C++ or Java, does not have the simplicity or theoretical underpinning of the relation database model. XML databases: The Extensible Markup Language (XML) is a text markup language designed for specifying the syntax of data and electronic documents. XML is particularly useful in describing semi-structured data. However, XML has proved to be so versatile that it is being used extensively in a wide variety of domains such as e-commerce, and other online applications. Relational Model: Representational models are the most widely used data models are the relational models. This model is also a record-based data model based on relations (Tables) in which data is represented as records. We will focus on this model from now on. Data Models, Schemas, and Instances DBMS provides some level of data abstraction by hiding details of data storage that are not needed by most database users. A data model a collection of concepts that can be used to describe the structure of a database. It provides the necessary means to achieve this abstraction. Structure of the database means the data types, relationships and constraints that should hold on the data. Most data models also include a set if basic operations for specifying retrievals and updates on the database. It is also common to define a set of valid user-defined operations that are allowed on the database objects. Categories of Data Models: Data Models are categorized according to the types of concepts they use to describe. High-level or conceptual data models provide concepts that are close to the way many users perceive data.

5 Low-level or physical data models provide concepts that describe the details of how data is stored in the computer. These concepts are generally meant for computer specialists. Representational (implementation) data models: This model is between the two, in that it can hide some details of storage but can be implemented on a computer system in a direct way. Conceptual data Models: use concepts such as entities, attributes and relationships. An entity represents a real-world object, such as employee, student, project, etc... An attribute represents some property of interest that describes the entity, such as the employee s name or salary. A relationship among two or more entities represents an interaction between entities, for example workson is a relationship between an employee and a project. Physical data models describe how data is stored in the computer by representing information such as record formats, record orderings and access paths. An access path is a structure that makes the search of particular database records efficient. Schemas, Instances and Database State: It is important to distinguish between the description of the database and the database itself. The description of a database is called the database schema, which is specified during database design and is not expected to change frequently. A diagram schema: is a way to display the database schema. Consider the following example of a database that stores student records and their grades.

6 STUDENT Name Student Number Class Major Smith 17 1 CS Brown 8 2 CS COURSE CourseName CourseNumber CreditHours Department Intro to Computer CS CS Science Data structures CS CS Discrete Mathematics MATH MATH Database CS CS SECTION SectionIdentifier CourseNumber Semester Year Instructor 85 Math2410 Fall 98 King 92 CS1310 Fall 98 Anderson 102 CS3320 Spring 99 Knuth 112 MATH2410 Fall 99 Chang 119 CS1310 Fall 99 Anderson 135 CS3380 Fall 99 Stone GRADE- REPORT StudentNumber SectionIdentifier Grade B C 8 85 A 8 92 A B A PREREQUISITE CourseNumber PrerequisiteNumber CS3380 CS3320 CS3380 MATH2410 CS3320 CS1310

7 Corresponding schema diagram: STUDENT Name Student Number Class Major COURSE CourseName CourseNumber CreditHours Department PREREQUISITE CourseNumber PrerequisiteNumber SECTION SectionIdentifier CourseNumber Semester Year Instructor GRADE_REPORT StudentNumber SectionIdentifier Grade A schema diagram displays only some aspects of a schema, such as the names of record types and data items and some type of constraints. Other aspects, such as the data type of each data item or constraints such as a student majoring in computer science must take CS1310 before the end of their sophomore year are not represented. The actual data in the database may change quite frequently, each time we add a student or enter a grade.

8 Database State: The data in the database at a particular moment is called database state or snapshot. It is also called the current set of occurrences or instances in the database. When we define a new database, we specify its database schema only to the DBMS. At this point the corresponding database state is the empty state with no data. We get the initial state of the database when the database is first populated or loaded with the initial data. A valid state of the database is a state that satisfies the structure and constraints specified in the schema. The DBMS stores the description of the schema constructs or constraints- metadata- in the DBMS catalog. DBMS Architecture and Data Independence: The three schema Architecture: The goal of this architecture is to separate the user applications from the physical database. Schemas are defined at the following three levels: 1- The internal level has an internal schema, which describes the physical storage structure of the database and access paths for the database. 2- The conceptual level has a conceptual schema, which describes the structure of the whole database for a community of users. The conceptual schema hides the details of the physical storage structures and focuses on describing entities, data types, relationships, user operations and constraints. 3- The external or view level includes a number of external schemas or user views. Each external schema describes the part of the database that a particular user group is interested in and hides the rest of the database from that user group. A high-level data model or implementation data model can be used at this level.

9 TRANSCRIPT StudentName Student Transcript CourseNumber Grade Semester Year SectionID CS1310 B Fall Smith MATH2410 C Fall MATH2410 A Fall Brown CS1310 A Fall CS3320 B Spring CS3380 A Fall Transcript view PREREQUISITE CourseNumber PrerequisiteNumber CS3380 CS3320 CS3380 MATH2410 CS3320 CS1310 Prerequisite view Data Independence: Logical Data Independence: is the capacity to change the conceptual schema without changing the external schema or application programs. That is we can change the conceptual schema to expand the database (by adding a record type or a data item) or to reduce the database (by removing a record type). GRADE- REPORT StudentNumber StudentName SectionIdentifier CourseNumber Grade 17 Smith 112 MATH2410 B 17 Smith 119 CS1310 C 8 Brown 85 MATH2410 A 8 Brown 92 CS1310 A 8 Brown 102 CS3320 B 8 Brown 136 CS3380 A

10 Only the view definition and the mapping need be changed in a DBMS. Application programs that reference the external schema constructs must work as before, after the conceptual schema undergoes a logical reorganization. Physical Data independence: is the capacity to change the internal schema without having to change the conceptual (or external) schemas. Internal schemas or the physical data might be needed to re-organize the data to improve access time for updates or other. These multiple-level databases also require that the catalog be expanded to include information on how to map requests and data among different levels. Database Languages and Interfaces: Data Definition Language (DDL): Used to define both the conceptual and internal schemas. Data Manipulation Language (DML): used to query the database for retrieval, insertion, deletion, and modification of the data. DBMS Interfaces: Menu based Interfaces for Browsing: Present the user with lists of options, called menus that lead the user through the formulation of a request. Menus do away with the need to memorize the specific commands or syntax of query languages. Form Based Interfaces: Displays a form to users. Users fill out all the form entries to insert new data.

MIT Database Management Systems Lesson 01: Introduction

MIT Database Management Systems Lesson 01: Introduction MIT 22033 Database Management Systems Lesson 01: Introduction By S. Sabraz Nawaz Senior Lecturer in MIT, FMC, SEUSL Learning Outcomes At the end of the module the student will be able to: Describe the