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Introduction to Database

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S
Siti Ismail

This document defines database and DBMS, describes their advantages over file-based systems like data independence and integrity. It explains database system components and architecture including physical and logical data models. Key aspects covered are data definition language to create schemas, data manipulation language to query data, and transaction management to handle concurrent access and recovery. It also provides a brief history of database systems and discusses database users and the critical role of database administrators.

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Chapter 1 ICT 2073 Prepare by : Ms. Siti Hajar Binti Ismail
Learning Objective  Define Database Management System (DBMS) and database  Describe the advantages and disadvantages of DBMS to file based system.  Analyses structure models in Database
Definitions Database:  A very large, integrated collection of data.  Models real-world enterprise.  Entities (e.g., students, courses)  Relationships (e.g., Madonna is taking CS564) Database Management System (DBMS)  a software package designed to store and manage databases.  Examples of Database Applications: • Banking: all transactions • Airlines: reservations, schedules • Universities: registration, grades
Purpose of Database Systems  In the early days, database applications were built directly on top of file systems  Drawbacks of using file systems to store data:  Data redundancy and inconsistency  Multiple file formats, duplication of information in different files  Difficulty in accessing data  Need to write a new program to carry out each new task  Data isolation — multiple files and formats
 Drawbacks of using file systems (cont.)  Integrity problems  Integrity constraints (e.g. account balance > 0) become “buried” in program code rather than being stated explicitly  Hard to add new constraints or change existing ones  Atomicity of updates  Failures may leave database in an inconsistent state with partial updates carried out  E.g. transfer of funds from one account to another should either complete or not happen at all
 Concurrent access by multiple users  Concurrent accessed needed for performance  Uncontrolled concurrent accesses can lead to inconsistencies  E.g. two people reading a balance and updating it at the same time  Security problems  Database systems offer solutions to all the above problems
Why Use a DBMS?  Separation of the Data definition and the Program  Abstraction into a simple model  Data independence and efficient access.  Reduced application development time – ad-hoc queries  Data integrity and security.  Uniform data administration.  Concurrent access, recovery from crashes.  Support for multiple different views
Why Study Databases??  Shift from computation to information  at the “low end”: scramble to webspace (a mess!)  at the “high end”: scientific applications  Datasets increasing in diversity and volume.  Digital libraries, interactive video, Human Genome project, EOS project  ... need for DBMS exploding  DBMS encompasses most of CS  OS, languages, theory, “AI”, multimedia, logic ?
Levels of Abstraction  Many views, single conceptual (logical) schema and physical schema.  Views describe how users see the data.  Conceptual schema defines logical structure. Sometime we separate between conceptual level and logical level  Physical schema describes the files and indexes used. * Schemas are defined using DDL (Data Definition Language) *data is modified/queried using DML (Data Manipulation Language) Physical Schema Conceptual Schema View 1 View 2 View 3
Levels of Abstraction  Physical level: describes how a record (e.g., customer) is stored.  Logical level: describes data stored in database, and the relationships among the data. type customer = record customer_id : string; customer_name : string; customer_street : string; customer_city : string; end;  View level: application programs hide details of data types. Views can also hide information (such as an employee’s salary) for security purposes.
Instances and Schemas  Schema – the logical structure of the database  Example: The database consists of information about a set of customers and accounts and the relationship between them)  Analogous to type information of a variable in a program  Physical schema: database design at the physical level  Logical schema: database design at the logical level  Instance – the actual content of the database at a particular point in time  Analogous to the value of a variable
 Physical Data Independence – the ability to modify the physical schema without changing the logical schema  Applications depend on the logical schema  In general, the interfaces between the various levels and components should be well defined so that changes in some parts do not seriously influence others.
Introduction to Database
Data Models  A collection of tools for describing  Data  Data relationships  Data semantics  Data constraints  Relational model  Entity-Relationship data model (mainly for database design)  Object-based data models (Object-oriented and Object-relational)  Semistructured data model (XML)  Other older models:  Network model  Hierarchical model
Data Manipulation Language (DML)  Language for accessing and manipulating the data organized by the appropriate data model  DML also known as query language  Two classes of languages  Procedural – user specifies what data is required and how to get those data  Declarative (nonprocedural) – user specifies what data is required without specifying how to get those data  SQL is the most widely used query language
Data Definition Language (DDL)  Specification notation for defining the database schema Example: create table account ( account_number char(10), branch_name char(10), balance integer)  DDL compiler generates a set of tables stored in a data dictionary
 Data dictionary contains metadata (i.e., data about data)  Database schema  Data storage and definition language  Specifies the storage structure and access methods used  Integrity constraints  Domain constraints  Referential integrity (e.g. branch_name must correspond to a valid branch in the branch table)  Authorization
SQL  SQL: widely used non-procedural language  Example: Find the name of the customer with customer-id 192-83-7465 select customer.customer_name from customer where customer.customer_id = ‘192-83-7465’  Application programs generally access databases through one of  Language extensions to allow embedded SQL  Application program interface (e.g., ODBC/JDBC) which allow SQL queries to be sent to a database
Database Design The process of designing the general structure of the database:  Logical Design – Deciding on the database schema. Database design requires that we find a “good” collection of relation schemas.  Business decision – What attributes should we record in the database?  Computer Science decision – What relation schemas should we have and how should the attributes be distributed among the various relation schemas?  Physical Design – Deciding on the physical layout of the database
The Entity-Relationship Model  Models an enterprise as a collection of entities and relationships  Entity: a “thing” or “object” in the enterprise that is distinguishable from other objects  Described by a set of attributes  Relationship: an association among several entities  Represented diagrammatically by an entity-relationship diagram:
Other Data Models  Object-oriented data model  Object-relational data model
Database Users  Users are differentiated by the way they expect to interact with the system  Application programmers – interact with system through DML calls  Sophisticated users – form requests in a database query language  Specialized users – write specialized database applications that do not fit into the traditional data processing framework  Naïve users – invoke one of the permanent application programs that have been written previously  E.g. people accessing database over the web, bank tellers, clerical staff
Database Administrator  Coordinates all the activities of the database system; the database administrator has a good understanding of the enterprise’s information resources and needs.
 Database administrator's duties include:  Schema definition  Storage structure and access method definition  Schema and physical organization modification  Granting user authority to access the database  Specifying integrity constraints  Acting as liaison with users  Monitoring performance and responding to changes in requirements
Database Management System Internals  Storage management  Query processing  Transaction processing
Storage Management  Storage manager is a program module that provides the interface between the low-level data stored in the database and the application programs and queries submitted to the system.  The storage manager is responsible to the following tasks:  interaction with the file manager  efficient storing, retrieving and updating of data
Concurrency Control  Concurrent execution of user programs is essential for good DBMS performance.  Because disk accesses are frequent, and relatively slow, it is important to keep the cpu humming by working on several user programs concurrently.  Interleaving actions of different user programs can lead to inconsistency: e.g., check is cleared while account balance is being computed.  DBMS ensures such problems don’t arise: users can pretend they are using a single-user system.
Transaction Management  A transaction is a collection of operations that performs a single logical function in a database application  Transaction-management component ensures that the database remains in a consistent (correct) state despite system failures (e.g., power failures and operating system crashes) and transaction failures.  Concurrency-control manager controls the interaction among the concurrent transactions, to ensure the consistency of the database.
History of Database Systems  1950s and early 1960s:  Data processing using magnetic tapes for storage  Tapes provide only sequential access  Punched cards for input  Late 1960s and 1970s:  Hard disks allow direct access to data  Network and hierarchical data models in widespread use  Ted Codd defines the relational data model  Would win the ACM Turing Award for this work  IBM Research begins System R prototype  UC Berkeley begins Ingres prototype  High-performance (for the era) transaction processing
History (cont.)  1980s:  Research relational prototypes evolve into commercial systems  SQL becomes industry standard  Parallel and distributed database systems  Object-oriented database systems  1990s:  Large decision support and data-mining applications  Large multi-terabyte data warehouses  Emergence of Web commerce  2000s:  XML and XQuery standards  Automated database administration  Increasing use of highly parallel database systems  Web-scale distributed data storage systems
Learning outcome  Differentiate between Database Management System (DBMS) and database  Briefly explain advantages and disadvantages of DBMS to file based system.  Discuss Database Models
Summary  DBMS used to maintain, query large datasets.  Benefits include recovery from system crashes, concurrent access, quick application development, data integrity and security.  Levels of abstraction give data independence.  A DBMS typically has a layered architecture.  DBAs hold responsible jobs and are well-paid!  DBMS R&D is one of the broadest, most exciting areas in CS.  Advanced databases course at the graduate level

More Related Content

Introduction to Database

  • 1. Chapter 1 ICT 2073 Prepare by : Ms. Siti Hajar Binti Ismail
  • 2. Learning Objective  Define Database Management System (DBMS) and database  Describe the advantages and disadvantages of DBMS to file based system.  Analyses structure models in Database
  • 3. Definitions Database:  A very large, integrated collection of data.  Models real-world enterprise.  Entities (e.g., students, courses)  Relationships (e.g., Madonna is taking CS564) Database Management System (DBMS)  a software package designed to store and manage databases.  Examples of Database Applications: • Banking: all transactions • Airlines: reservations, schedules • Universities: registration, grades
  • 4. Purpose of Database Systems  In the early days, database applications were built directly on top of file systems  Drawbacks of using file systems to store data:  Data redundancy and inconsistency  Multiple file formats, duplication of information in different files  Difficulty in accessing data  Need to write a new program to carry out each new task  Data isolation — multiple files and formats
  • 5.  Drawbacks of using file systems (cont.)  Integrity problems  Integrity constraints (e.g. account balance > 0) become “buried” in program code rather than being stated explicitly  Hard to add new constraints or change existing ones  Atomicity of updates  Failures may leave database in an inconsistent state with partial updates carried out  E.g. transfer of funds from one account to another should either complete or not happen at all
  • 6.  Concurrent access by multiple users  Concurrent accessed needed for performance  Uncontrolled concurrent accesses can lead to inconsistencies  E.g. two people reading a balance and updating it at the same time  Security problems  Database systems offer solutions to all the above problems
  • 7. Why Use a DBMS?  Separation of the Data definition and the Program  Abstraction into a simple model  Data independence and efficient access.  Reduced application development time – ad-hoc queries  Data integrity and security.  Uniform data administration.  Concurrent access, recovery from crashes.  Support for multiple different views
  • 8. Why Study Databases??  Shift from computation to information  at the “low end”: scramble to webspace (a mess!)  at the “high end”: scientific applications  Datasets increasing in diversity and volume.  Digital libraries, interactive video, Human Genome project, EOS project  ... need for DBMS exploding  DBMS encompasses most of CS  OS, languages, theory, “AI”, multimedia, logic ?
  • 9. Levels of Abstraction  Many views, single conceptual (logical) schema and physical schema.  Views describe how users see the data.  Conceptual schema defines logical structure. Sometime we separate between conceptual level and logical level  Physical schema describes the files and indexes used. * Schemas are defined using DDL (Data Definition Language) *data is modified/queried using DML (Data Manipulation Language) Physical Schema Conceptual Schema View 1 View 2 View 3
  • 10. Levels of Abstraction  Physical level: describes how a record (e.g., customer) is stored.  Logical level: describes data stored in database, and the relationships among the data. type customer = record customer_id : string; customer_name : string; customer_street : string; customer_city : string; end;  View level: application programs hide details of data types. Views can also hide information (such as an employee’s salary) for security purposes.
  • 11. Instances and Schemas  Schema – the logical structure of the database  Example: The database consists of information about a set of customers and accounts and the relationship between them)  Analogous to type information of a variable in a program  Physical schema: database design at the physical level  Logical schema: database design at the logical level  Instance – the actual content of the database at a particular point in time  Analogous to the value of a variable
  • 12.  Physical Data Independence – the ability to modify the physical schema without changing the logical schema  Applications depend on the logical schema  In general, the interfaces between the various levels and components should be well defined so that changes in some parts do not seriously influence others.
  • 14. Data Models  A collection of tools for describing  Data  Data relationships  Data semantics  Data constraints  Relational model  Entity-Relationship data model (mainly for database design)  Object-based data models (Object-oriented and Object-relational)  Semistructured data model (XML)  Other older models:  Network model  Hierarchical model
  • 15. Data Manipulation Language (DML)  Language for accessing and manipulating the data organized by the appropriate data model  DML also known as query language  Two classes of languages  Procedural – user specifies what data is required and how to get those data  Declarative (nonprocedural) – user specifies what data is required without specifying how to get those data  SQL is the most widely used query language
  • 16. Data Definition Language (DDL)  Specification notation for defining the database schema Example: create table account ( account_number char(10), branch_name char(10), balance integer)  DDL compiler generates a set of tables stored in a data dictionary
  • 17.  Data dictionary contains metadata (i.e., data about data)  Database schema  Data storage and definition language  Specifies the storage structure and access methods used  Integrity constraints  Domain constraints  Referential integrity (e.g. branch_name must correspond to a valid branch in the branch table)  Authorization
  • 18. SQL  SQL: widely used non-procedural language  Example: Find the name of the customer with customer-id 192-83-7465 select customer.customer_name from customer where customer.customer_id = ‘192-83-7465’  Application programs generally access databases through one of  Language extensions to allow embedded SQL  Application program interface (e.g., ODBC/JDBC) which allow SQL queries to be sent to a database
  • 19. Database Design The process of designing the general structure of the database:  Logical Design – Deciding on the database schema. Database design requires that we find a “good” collection of relation schemas.  Business decision – What attributes should we record in the database?  Computer Science decision – What relation schemas should we have and how should the attributes be distributed among the various relation schemas?  Physical Design – Deciding on the physical layout of the database
  • 20. The Entity-Relationship Model  Models an enterprise as a collection of entities and relationships  Entity: a “thing” or “object” in the enterprise that is distinguishable from other objects  Described by a set of attributes  Relationship: an association among several entities  Represented diagrammatically by an entity-relationship diagram:
  • 21. Other Data Models  Object-oriented data model  Object-relational data model
  • 22. Database Users  Users are differentiated by the way they expect to interact with the system  Application programmers – interact with system through DML calls  Sophisticated users – form requests in a database query language  Specialized users – write specialized database applications that do not fit into the traditional data processing framework  Naïve users – invoke one of the permanent application programs that have been written previously  E.g. people accessing database over the web, bank tellers, clerical staff
  • 23. Database Administrator  Coordinates all the activities of the database system; the database administrator has a good understanding of the enterprise’s information resources and needs.
  • 24.  Database administrator's duties include:  Schema definition  Storage structure and access method definition  Schema and physical organization modification  Granting user authority to access the database  Specifying integrity constraints  Acting as liaison with users  Monitoring performance and responding to changes in requirements
  • 25. Database Management System Internals  Storage management  Query processing  Transaction processing
  • 26. Storage Management  Storage manager is a program module that provides the interface between the low-level data stored in the database and the application programs and queries submitted to the system.  The storage manager is responsible to the following tasks:  interaction with the file manager  efficient storing, retrieving and updating of data
  • 27. Concurrency Control  Concurrent execution of user programs is essential for good DBMS performance.  Because disk accesses are frequent, and relatively slow, it is important to keep the cpu humming by working on several user programs concurrently.  Interleaving actions of different user programs can lead to inconsistency: e.g., check is cleared while account balance is being computed.  DBMS ensures such problems don’t arise: users can pretend they are using a single-user system.
  • 28. Transaction Management  A transaction is a collection of operations that performs a single logical function in a database application  Transaction-management component ensures that the database remains in a consistent (correct) state despite system failures (e.g., power failures and operating system crashes) and transaction failures.  Concurrency-control manager controls the interaction among the concurrent transactions, to ensure the consistency of the database.
  • 29. History of Database Systems  1950s and early 1960s:  Data processing using magnetic tapes for storage  Tapes provide only sequential access  Punched cards for input  Late 1960s and 1970s:  Hard disks allow direct access to data  Network and hierarchical data models in widespread use  Ted Codd defines the relational data model  Would win the ACM Turing Award for this work  IBM Research begins System R prototype  UC Berkeley begins Ingres prototype  High-performance (for the era) transaction processing
  • 30. History (cont.)  1980s:  Research relational prototypes evolve into commercial systems  SQL becomes industry standard  Parallel and distributed database systems  Object-oriented database systems  1990s:  Large decision support and data-mining applications  Large multi-terabyte data warehouses  Emergence of Web commerce  2000s:  XML and XQuery standards  Automated database administration  Increasing use of highly parallel database systems  Web-scale distributed data storage systems
  • 31. Learning outcome  Differentiate between Database Management System (DBMS) and database  Briefly explain advantages and disadvantages of DBMS to file based system.  Discuss Database Models
  • 32. Summary  DBMS used to maintain, query large datasets.  Benefits include recovery from system crashes, concurrent access, quick application development, data integrity and security.  Levels of abstraction give data independence.  A DBMS typically has a layered architecture.  DBAs hold responsible jobs and are well-paid!  DBMS R&D is one of the broadest, most exciting areas in CS.  Advanced databases course at the graduate level