Database System Concepts and Architecture. Relational Model Concepts relational model represents the...

Database System Concepts and Architecture

Relational Model Concepts

relational model represents the database as a collection of relations.

Each relation resembles a table of values or, to some extent, a flat file of records.

Each row in the table represents a collection of related data values.

A row represents a fact that typically corresponds to a real-world entity or relationship

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Relational Model Concepts

The table name and column names are used to help to interpret the meaning of the values in each row.

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Domains, Attributes, Tuples, and Relations

A domain D is a set of atomic values. each value in the domain is indivisible as far as the

formal relational model is concerned. specifying a data type from which the data values

forming the domain. Examples :

Names: The set of character strings that represent names of persons.

Employee_ages: Possible ages of employees in a company; each must be an integer value between 15 and 80.

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Relation Schema

A relation schema R, denoted by R(A1, A2, ...,An), is made up of a relation name R and a list of attributes, A1, A2, ..., An.

D is called the domain of Ai and is denoted by dom(Ai).

The degree (or arity) of a relation is the number of attributes n of its relation schema.

Example: A relation of degree seven.

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Relation Schema

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Cartesian product (denoted by ×)Total number of possible instances or tuples is :

Characteristics of Relations

Ordering of Tuples in a Relation A relation is not sensitive to the ordering of tuples. In a file, records are physically stored on disk (or in

memory), so there always is an order among the records.

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Ordering of Values within a Tuple and an Alternative Definition of a Relation.

An n-tuple is an ordered list of n values, so the ordering of values in a tuple—and hence of attributes in a relation schema—is important.

At a more abstract level, the order of attributes and their values is not that important as long as the correspondence between attributes and values is maintained.

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Values and NULLs in the Tuples. Each value in a tuple is an atomic value; No composite values are allowed NULL represent the values that may be unknown

or may not apply to a tuple.

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Interpretation (Meaning) of a Relation The relation schema can be interpreted as a

declaration or a type of assertion or predict . For example,

The schema of the STUDENT relation asserts that, in general, a student entity has a Name, Ssn, Home_phone, Address, Office_phone, Age, and Gpa.

The predicate STUDENT (Name, Ssn, ...) is true for the five tuples in relation STUDENT

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Data Models

Recall: a major characteristic of DB approach is Data Abstraction.

Data Abstraction: Suppression of details of data organization and

storage and the highlighting of the essential features to better understand data.

Different users will perceive data at their preferred level of detail.

A Data Model enables Data Abstraction

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Data Models

Data Model: A set of concepts to describe

The structure of a database The operations for manipulating these structures The constraints that the database should obey

Data Model Structure and Constraints: Constructs are used to define the database structure Constructs typically include

elements (and their data types) groups of elements (e.g. entity, record, table) relationships among such groups

Constraints specify some restrictions on valid data; these constraints must be enforced at all times

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Data Models (continued)

Data Model Operations: These operations are used for specifying database

retrievals and updates by referring to the constructs of the data model.

Operations on the data model may include basic model operations

(e.g. generic insert, delete, update) user-defined operations

(e.g. compute_student_gpa, update_inventory)

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Categories of Data Models

Conceptual (high-level, semantic) data models: Provide concepts that are close to the way many users

perceive data. (Also called entity-based or object-based data models.)

Physical (low-level, internal) data models: Provide concepts that describe details of how data is stored

in the computer. Implementation (representational) data models:

Provide concepts that fall between the above two, used by many commercial DBMS implementations (e.g. relational data models used in many commercial systems).

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DATABASE SYSTEM

Application Program/Queries

DBMS SOFTWARE

Software to Process Queries/Programs

Software to Access Stored Data

Stored Database Definition

Stored Database

Users/Programmers

Meta-data/ Schema

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Schemas versus Instances

Database Schema: The description of a database. Includes descriptions of the database structure,

data types, and the constraints on the database. Schema Diagram:

An illustrative display of (most aspects of) a database schema.

Schema Construct: A component of the schema or an object within

the schema, e.g., STUDENT, COURSE.

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Schemas versus Instances

Database State: The actual data stored in a database at a

particular moment in time. This includes the collection of all the data in the database.

Also called Database Instance (or Occurrence or Snapshot).

The term instance is also applied to individual database components, e.g. record instance, table instance, entity instance

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Database Schema vs. Database State

Database State: Refers to the content of a database at a moment

in time. Initial Database State:

Refers to the database state when it is initially loaded into the system.

Valid State: A state that satisfies the structure and constraints

of the database.

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Database Schema vs. Database State (continued)

Distinction The database schema changes very infrequently. The database state changes every time the

database is updated.

Schema is also called Intension.

State is also called Extension.

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Example of a Database Schema

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Example of a Database State

Name Student_number Class Major

Smith 17 1 CS

Brown 8 2 CS

STUDENT

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Three-Schema Architecture

Proposed to support DBMS characteristics of: Program-data independence. Support of multiple views of the data.

Not explicitly used in commercial DBMS products, but has been useful in explaining database system organization

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Defines DBMS schemas at three levels: Internal schema at the internal level to describe physical

storage structures and access paths (e.g indexes). Typically uses a physical data model.

Conceptual schema at the conceptual level to describe the structure and constraints for the whole database for a community of users.

Uses a conceptual or an implementation data model. External schemas at the external level to describe the

various user views. Usually uses the same data model as the conceptual schema.

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The three-schema architecture

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Mappings among schema levels are needed to transform requests and data. Programs refer to an external schema, and are

mapped by the DBMS to the internal schema for execution.

Data extracted from the internal DBMS level is reformatted to match the user’s external view (e.g. formatting the results of an SQL query for display in a Web page)

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Data Independence

Logical Data Independence: The capacity to change the conceptual schema

without having to change the external schemas and their associated application programs.

Physical Data Independence: The capacity to change the internal schema

without having to change the conceptual schema. For example, the internal schema may be changed

when certain file structures are reorganized or new indexes are created to improve database performance

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Data Independence (continued)

When a schema at a lower level is changed, only the mappings between this schema and higher-level schemas need to be changed in a DBMS that fully supports data independence.

The higher-level schemas themselves are unchanged. Hence, the application programs need not be

changed since they refer to the external schemas.

Just Smile

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DBMS Languages

Data Definition Language (DDL)

Data Manipulation Language (DML)

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DBMS Languages

Data Definition Language (DDL): Used by the DBA and database designers to

specify the conceptual schema of a database. In many DBMSs, the DDL is also used to define

internal and external schemas (views). In some DBMSs, separate storage definition

language (SDL) and view definition language (VDL) are used to define internal and external schemas.

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DBMS Languages

Data Manipulation Language (DML): Used to specify database retrievals and updates Stand-alone DML commands can be applied

directly (called a query language). DML commands (data sublanguage) can be

embedded in a general-purpose programming language (host language), such as COBOL, C, C++, or Java.

A library of functions can also be provided to access the DBMS from a programming language

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Types of DML

High Level or Non-procedural Language: May be used in a standalone way or may be embedded in a

programming language Are “set”-oriented and specify what data to retrieve rather

than how to retrieve it. Also called declarative languages. E.g. SQL relational language

Low Level or Procedural Language: These MUST be embedded in a programming language Retrieve data one record-at-a-time; Constructs such as looping are needed to retrieve multiple

records, along with positioning pointers. E.g. DL/1 (developed for Hierarchical Model)

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DBMS Interfaces

Stand-alone query language interfaces Example: Entering SQL queries at the DBMS

interactive SQL interface (e.g. SQL*Plus in ORACLE)

Programmer interfaces for embedding DML in programming languages

User-friendly interfaces Menu-based, forms-based, graphics-based, etc.

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DBMS Programming Language Interfaces

Programmer interfaces for embedding DML in a programming languages: Embedded Approach: e.g embedded SQL (for C,

C++, etc.), SQLJ (for Java) Procedure Call Approach: e.g. JDBC for Java,

ODBC for other programming languages Database Programming Language Approach:

e.g. ORACLE has PL/SQL, a programming language based on SQL; language incorporates SQL and its data types as integral components

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Database System Utilities

To perform certain functions such as: Loading data stored in files into a database. Includes data

conversion tools. Backing up the database periodically on tape. Reorganizing database file structures. Report generation utilities. Performance monitoring utilities. Other functions, such as sorting, user monitoring, data

compression, etc. Data dictionary / repository:

Used to store schema descriptions and other information such as design decisions, application program descriptions, user information, usage standards, etc

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Typical DBMS Component Modules

Low level I/O & buffer mgmt

operations

Schemas, mappings,

Constraints,File sizes,

Statistics .. etc

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DBMS Architectures

Centralized DBMS

Client/Server DBMS 2-tier 3-tier

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Centralized DBMS Architectures

Combines everything into single system including: DBMS software hardware application programs & user interface processing software

User can still connect through a remote terminal However, all processing is done at centralized site.

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A Physical Centralized Architecture

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Client/Server

Client Provides appropriate interfaces through a client software module to

access and utilize the various server resources. Applications running on clients utilize an Application Program

Interface (API) to access server databases via standard interface such as:

ODBC: Open Database Connectivity standard JDBC: for Java programming access

Server Provides database query and transaction services to the clients Relational DBMS servers are often called SQL servers, query

servers, or transaction servers Client and server must install appropriate client module and server

module software for ODBC or JDBC

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Logical two-tier client server architecture

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Three Tier Client-Server Architecture

Common for Web applications Intermediate Layer called Application Server or Web

Server: Stores the web connectivity software and the business logic

part of the application used to access the corresponding data from the database server

Acts like a conduit for sending partially processed data between the database server and the client.

Three-tier Architecture Can Enhance Security: Database server only accessible via middle tier Clients cannot directly access database server

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Three-tier client-server architecture

Integrity, Referential Integrity,and Foreign Keys

The entity integrity constraint states that no primary key value can be NULL.

A tuple in one relation that refers to another relation must refer to an existing tuple in that relation. Dno of EMPLOYEE gives the department number

for which each employee works; hence, its value in every EMPLOYEE tuple must match the Dnumber value of some tuple in the DEPARTMENT relation.

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Primary and Foreign Keys

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