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CS157A Lecture 2 DB Mangement Systems

CS157A Lecture 2 DB Mangement Systems. Prof. Sin-Min Lee Department of Computer Science San Jose State University. Objectives. In this Lecture you will learn:. Purpose of Database Systems View of Data Data Models Data Definition Language Data Manipulation Language

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CS157A Lecture 2 DB Mangement Systems

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  1. CS157A Lecture 2 DB Mangement Systems Prof. Sin-Min Lee Department of Computer Science San Jose State University

  2. Objectives In this Lecture you will learn: • Purpose of Database Systems • View of Data • Data Models • Data Definition Language • Data Manipulation Language • Transaction Management • Storage Management • Database Administrator • Database Users • Overall System Structure

  3. 1. Database Theory Why use database? Data is a valuable corporate resource which needs adequate, accuracy, consistency and security controls. The centralised control of data means that for many applications the data will already exist, and facilitate quicker development. Data will no longer be related by application programs, but by the structure defined in the database. Easier to maintain systems

  4. First generation database systems • The network and hierarchical databases of the 1970’s • The first systems to offer DBMS function in a unified system • e.g. CODASYL, IMS

  5. Second generation database systems • relational databases of the 1980’s • data independence and non procedural data manipulation language • e.g. DB2, INGRES, NON-STOP SQL, ORACLE, Rdb/VMS • Focused on business data processing

  6. Third generation database systems • Problems with 2nd generation DBS • inadequate for a broader class of applications (than business data processing) • e.g. CAD, CASE, Hypertext, • storing text segments, graphics, etc is usually difficult in 2nd gen. systems • Does not support complex data (folders) • Most vendors are working on functional enhancements on their 2nd gen. systems • Surprising degree of consensus on these features • 3rd gen systems includes the desired capabilities of next generation database systems

  7. DATABASE AND DBMS CONCEPTS Database – is a collection of data, typically describing the activities of one or more related organizations. A Database Management System DBMS) is software designed to assist in maintaining and utilization large collections of data. The SQL (Structured Query Language), developed by IBM is now the standard query language.

  8. ADVANTAGES OF A DBMS • Data independence • Application programs should not, ideally, be exposed to details of data representation and storage. • Efficient Data access • A DBMS uses several powerful functions to store and retrieve data efficiently. • Data Integrity and Security • The DBMS enforces integrity constraints to get a kind of protection against prohibited access to data.

  9. ADVANTAGES OF A DBMS • Data Administration • When any users share the data, centralizing the administration of data can offer significant improvements. • Concurrent Access and Crash Recovery • A DBMS schedules concurrent access to the data in such manner that users can think of the data as being accessed by only one user at a time. DBMS also protects users from the effects of system failures. • Reduced Application Development Time • DBMS includes several important functions that are common to many applications accessing data in the DBMS. In conjunction with the high-level interface to the data, facilitates quick application development.

  10. DATA MODEL CONCEPT • A data model is a collection of high-leveldatadescriptionconstructs that hide many low-level storage details. • Most database management systems today are based on the Relationaldata model.

  11. THE RELATIONAL MODEL • The central data description construct is this model is a Relation, which can be thought of a set of records. • A Schema for a relation specifies: • Name of relation (e.g. Students) • Name of each field (or attribute or column) • Type of each field. • Schema Sudents (sid:string,age:integer)

  12. Example of an Instance of Students Students Schema ------> Students (sid : String, Age : Integer)

  13. Characteristics • Each row in the Students relation is a record that describes any student. • Integrity constraints are conditions that the records must satisfy. E.g. sid is unique. • Oracle uses relational( and also object) data model.

  14. Levels of Abstraction in a DBMS • Conceptual Schema : or logical schema describes all relations that are stored in the database. • In the university example, these relations contain information about entities, such as students and faculty, and about relationships, such as students’ enrollment in courses.

  15. Conceptual Schema For university, a conceptual schema is: • Students(sid:string,Age:integer) • Faculty (fid: string, salary: real) • Courses (cid: string, cname: string, credits:integer)

  16. Physical Schema • Physical Schema : specifies additional storage details. • It summarizes how the relations described in the conceptual schema are stored on secondary storage devices such as disks and tapes. • Creation of data structures called indexes, to speed up data retrieval operations

  17. Physical Schema A sample physical schema for the university: • Store all relations as unsorted files of records • Create indexes on the first column of Students, Faculty, and Courses relations.

  18. External Schema • Each external schema consists of a collection of one or more views and relations from the conceptual schema. • A view is conceptually a relation, but the records in a view are not stored in the DBMS. • A user creates any view from data already stored.

  19. External Schema • For example: we might want to allow students to find out the names of faculty members teaching courses. • This is the view associated: Courseinfo (cid:string, fname:string) • A user can treat a view just like a relation and ask questions about the records in the view, even though the records in the view are not stored explicitly.

  20. Database Management System (DBMS) • A software package such as Oracle or MS-Access. • Manages data and relationships in the database. • Creates a Data Dictionary to store Metadata – data about data. • Manages all day-to-day transactions. • Provides user with data independence at application level. • Transforms logical data requests to match physical data structures. • Secures access through passwords, restricted user access, and encryption. • Provides backup and recovery mechanisms. • Provides export and import utilities. • Allows sharing of data with locking capabilities.

  21. Traditional File Systems In the the past as new applications were written they used existing files, or created a new file for their use. Sometimes several existing files need to be sorted and merged to obtain the new file.Thus, it is probable that several files will contain the same information stored in different ways. In other words, there will be redundant and possibly inconsistent data. Consider the files for an insurance company POLICY# POLICYHOLDER PREMIUMS data ADDRESS PREMIUM-PA PREMIUM-TOTAL POLICY# POLICYHOLDER AGENCY data ADDRESS AGENT-CODE RENEWAL-DATE RENEWAL-AMT

  22. Traditional File Systems Applications were often considered in relative isolation. Data that should have been together was not. The potential for flexible enquiry and reporting was limited. All validations were in the programs. Procedures were required to for backup and recovery. All programmers had access to all records. There was limited concurrent access.

  23. Basic Definitions Database: A collection of related data Data: Known facts that can be recorded Schema: Some part of the real world about which data is stored in the database. Database Management System(DBMS): A software package to facilitate the creation and maintenance of a computerised database.

  24. Degrees of Data Independence • Device Characteristics • Blocking Factors • Data Access Organisation • Physical Record Location • Logical Views (Local) • Virtual Data Items · Virtual Records • Data Value Characteristics • Data Element Name Only

  25. Logical vs Physical Data Independence GLOBAL LOGICAL DATABASE DESCRIPTION Application Program Local Views Physical Files Logical Data Independence Physical Data Independence

  26. Three Schema Architecture ANSI & ISO suggest that DBMS should have three schemas • CONCEPTUAL SCHEMA - the global logical model of the data and processing of the enterprise. i.e community user view. • EXTERNAL SCHEMA(S) - the logical application views of the CS. i.e individual user views. • INTERNAL SCHEMA - internal level storage view.

  27. Three Schema Architecture External Schema 1 External Schema 2 External Schema n Conceptual Schema Internal Schema

  28. The External Level • Each user has a language through which they access or see the database. • For the programmer - COBOL etc, for the end-user a query language or special purpose language. • All languages will contain a data sub-language which may be tightly or loosely coupled to the host language.

  29. DSLs generally contain a data definition language DDL and data manipulation language DML.

  30. The Conceptual Level • A representation of the entire information content of the database. • Defined with a Conceptual Schema Language which does not represent any storage or access details. • Should include all security and integrity rules and some suggest the CS should describe the total enterprise including all allowable processing.

  31. The Internal Level • Low level representation of entire database. • Deals with stored records rather than conceptual or external records. • Stored records may differ in structure from conceptual records and external records. • The Internal Schema is still one level away from physical records which are often called pages or blocks

  32. Inter-Related Data CLAIMS D B M S RENEWALS RENEWALS AGENCY CLAIMS AGENCY Data related by structure Flexible enquiry easier QUERY

  33. Multiple Applications DATABASE LOCAL VIEWS AGENCY CLAIMS RENEWALS

  34. Database Management System (DBMS) • Collection of interrelated data • Set of programs to access the data • DBMS contains information about a particular enterprise • DBMS provides an environment that is both convenient and efficient to use. • Database Applications: • Universities: registration, grades • Banking: all transactions • Sales: Airlines: reservations, schedules • customers, products, purchases • Manufacturing: production, inventory, orders, supply chain • Human resources: employee records, salaries, tax deductions • Databases touch all aspects of our lives

  35. Purpose of Database System • In the early days, database applications were built 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 • Integrity problems • Integrity constraints (e.g. account balance > 0) become part of program code • Hard to add new constraints or change existing ones

  36. Purpose of Database Systems (Cont.) • Drawbacks of using file systems (cont.) • 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

  37. 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 = recordname : string;street : string;city : integer;end; • View level: application programs hide details of data types. Views can also hide information (e.g., salary) for security purposes.

  38. View of Data An architecture for a database system

  39. Instances and Schemas • Similar to types and variables in programming languages • Schema– the logical structure of the database • e.g., 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.

  40. Data Models • A collection of tools for describing • data • data relationships • data semantics • data constraints • Entity-Relationship model • Relational model • Other models: • object-oriented model • semi-structured data models • Older models: network model and hierarchical model

  41. Entity-Relationship Model Example of schema in the entity-relationship model

  42. Entity Relationship Model (Cont.) • E-R model of real world • Entities (objects) • E.g. customers, accounts, bank branch • Relationships between entities • E.g. Account A-101 is held by customer Johnson • Relationship set depositor associates customers with accounts • Widely used for database design • Database design in E-R model usually converted to design in the relational model (coming up next) which is used for storage and processing

  43. Relational Model Attributes customer- name account- number customer- city • Example of tabular data in the relational model customer- street Customer-id 192-83-7465 019-28-3746 192-83-7465 321-12-3123 019-28-3746 Johnson Smith Johnson Jones Smith Alma North Alma Main North A-101 A-215 A-201 A-217 A-201 Palo Alto Rye Palo Alto Harrison Rye

  44. A Sample Relational Database

  45. Data Definition Language (DDL) • Specification notation for defining the database schema • E.g. create tableaccount (account-numberchar(10),balanceinteger) • 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 • language in which the storage structure and access methods used by the database system are specified • Usually an extension of the data definition language

  46. 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 • Nonprocedural – user specifies what data is required without specifying how to get those data • SQL is the most widely used query language

  47. SQL • SQL: widely used non-procedural language • E.g. find the name of the customer with customer-id 192-83-7465selectcustomer.customer-namefromcustomerwherecustomer.customer-id = ‘192-83-7465’ • E.g. find the balances of all accounts held by the customer with customer-id 192-83-7465selectaccount.balancefromdepositor, accountwheredepositor.customer-id = ‘192-83-7465’anddepositor.account-number = account.account-number • 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

  48. 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

  49. 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

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