1 CS 430 Database Theory Winter 2005 Lecture 2: General Concepts

2 Example of a Database Picture of a Database  See Figure 1.2 of Text Book Two Views of the Data  See Figure 1.4 of Text Book

3 Data Models A Model for Describing Data Examples:  Relational  Legacy: Network, Hierarchical  Object, Object-Relational  Entity/Relationship (ER) Typically used for “data modeling” Typically includes:  Definition: What kind of structures can be defined  Basic Data Manipulation Except for ER Model

4 Relational Data Model Data is organized into Tables  Rows = Records  Columns = Fields Tables are related by data values Data related by shared data values Data manipulation:  Insert a record  Update and delete records  Select records a collection of fields from one or more records

5 Network and Hierarchical Models Data organized into Programming Language records  Programming language = COBOL! Records organized into Sets  Each set has an owner Hierarchical: Record is member of one set  Methods provided to link records Network: Record can be member of multiple sets Data Manipulation:  Traverse sets  Insert, Modify, Delete records  Change set memberships

6 Object and Object/Relational Data Models Object:  C++ (typical) style objects stored in database Manipulated by manipulating records in memory  Objects can have methods as well as data Object/Relational  Relational at core  Rows treated as objects  Supports object concepts such as inheritance, methods, etc.

7 Entity/Relationship (ER) Used for data modeling Data organized into Entities which have attributes Entities are connected via named relationships Tools available which can convert from ER model to Relational Schema

8 Data Modeling Data modeling builds data models  Yes, we have duplicated terminology Data modeling:  Develop a model for the data that will be stored and manipulated by a database applications

9 Categories of Data Models Conceptual or High-Level  Model the data as seen by the user  Typically incomplete  Answers question: Do we have all the data requirements? Logical or Representational  Model the data as seen by the application developer  Should have all the Entities, Attributes and Relationships (ER) or Tables, Columns, DataTypes (Relational) identified Physical or Low-Level  The data as seen by the database administrator  All the physical information available Where data is stored, indices, etc.

10 Schema, States The database schema is the description of the database  The schema is the Intension of the database As the database is modified it moves from state to state  The DBMS is responsible for guaranteeing that each state is consistent (in accord with the schema) A database state is the Extension of the schema

11 Three Schema Architecture See figure 2.2 in Text Book Internal Schema  The actual schema of the database Conceptual Schema  How the data is organized External Schemas  Individual user and/or application views of the data

12 Three Schema Architecture and Data Independence Logical Data Independence  Can change Conceptual Schema without changing External Schemas  Always true to some extent: Add new Records or Tables Add new columns? new Relationships? Change representation of data items (e.g. numbers)? Physical Data Independence  Can change internal Schema without changing Conceptual Schema  Also always true to some extent Where records are stored on disk Add new access paths?

13 Data Languages Data Definition Language (DDL)  Define the schema, create the catalog Data Manipulation Language (DML)  Query the database and change the state of the database  Can be non-procedural (SQL) or procedural (OO) View Definition Language (VDL)  Define external views Storage Definition Language (SDL)  How data is stored on disk

14 Data Languages (continued) An ordinary programming language (e.g. C, Java) is a host language DML embedded in a host language is a data sublanguage  May require a preprocessor  May be an Application Programming Interface (API) Queries, e.g. may be Character Strings DML outside of a host language is a “Query Language”  Even if it can update the database

15 Three Schema Architecture Bottom Line Nice idea Reality:  The three levels are not cleanly separated  Applications (external) are reasonably well insulated from internal changes Except, of course, for performance Example:SQL  There is no separate VDL, this is part of DDL  DDL can include physical information,e.g. indices  Conceptual schema is simply table definitions with the physical portion removed

16 Database Components See Figure 2.3, Text Book Applications can use either precompiled interface or “ad hoc” interface  Ad hoc interface is the same one used by Interactive Query tools Stored Data Manager can include Buffer Management  Or this may be left to Operating System

17 Database Utilities “Bulk loading” of data into the database  Convert from an external text format for data to the DBMS internal format  Integrated with the DBMS for efficiency Backup and Restore  May include incremental backup  Knows DBMS structure, so can save consistent picture of the database Reorganization  Schema changes and/or performance improvement Performance monitoring  Help to improve database performance

18 Application Development Data Dictionary  Description of all the data  All the ancillary information, e.g. units of measure Host language API  For almost any host language  ODBC (Open Database Connectivity) Host language precompilers  Convert embedded DML (typically) into host language API Application Development Environments  Can be extremely sophisticated

19 Two-Tier and Three-Tier Database Applications Two-tier Three-tier Client Application and/or Web Server Database Client Database

20 Classification of DBMS Data Model Single or Multi-User  Multi-User typical General or special purpose Centralized or Distributed  Distributed: Homogeneous or Federated Transaction processing (OLTP) versus Decision Support (OLAP)