Introduction to Database Systems. Motivation. Werner Nutt

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Transcription:

Introduction to Database Systems Motivation Werner Nutt 1

Databases Are Everywhere Database = a large (?) collection of related data Classically, a DB models a real-world organisation (e.g., enterprise, university) Entities(e.g., students, courses) Relationships (e.g., Martin is taking IDS in 2010/11 ) Changes in the organisation = changes in the database Examples: personnel records banking airline reservations 2

Scientific Databases (Examples) Biology: e.g., DNA sequences of genes, amino-acid sequences of proteins, genes expressed in tissues (up to several Gigabytes) Astronomy: e.g., location and spectra of astronomic objects (up to several Terabytes) Physics: e.g., sensor measurements in particle physics experiments (up to several Petabytes) 3

DB Tendencies Sensors record data DBs grow in size DBs become more widespread date may be less reliable, i.e., uncertain Multimedia data Requirements for larger storage New query operations (e.g., find a song by humming the melody, find pictures with a given face) Data on the Web Accessed/changed by many people (Facebook, ) Speed up access, loosen consistency (NoSQL) 4

Operations with Databases Design Define structure and types of data Construction Create data structures of DB, populate DB with data Manipulation of Data Insert, delete, update Query: Which department pays the highest salary? Create reports: List monthly salaries of employees, organised by department, with average salary and total sum of salaries for each dept 5

An Ideal DB Implementation Should Support: Structure data types data behaviour Persistence store data on secondary storage Retrieval a declarative query language a procedural database programming language Performance retrieve and store data quickly Data Integrity Sharing concurrency Reliability and resilience Large data volumes 6

Database Management System (DBMS) A DBMS is a software package designed to store and manage databases A DBMS provides generic functionality (see previous slide) that otherwise would have to be implemented over and over again Reduced application development time Several brands, e.g., Oracle Xi/Yg (Oracle), DB2 (IBM), SQL Server, Access (Microsoft), MySQL, PostgreSQL, HSQLDB, SQLite (open source) 7

Database Actors Database Designers Application Programmers on the scenes Database Administrator (DBA) Database End Users sophisticated casual parametric or canned transactions DBMS developers Tool Developers Operators and Maintenance Personnel behind the scenes Database Management System 8

File System: A Physical Interface Student Data Student Admin Year Lists Course Data Scheduler Timetable Lecturer Data Payroll Money Transfer 9

Sharing Data: Replication Redundancy Student Admin Lab Timetable Tutorials Student Data Course Data Lecturer Data Scheduler Teaching Schedule Payroll 10

Sharing Data and Operations Student Data Student Admin Lab Timetable Course Data Tutorials Scheduler Lecturer Data Teaching Schedule Payroll 11

DBMS: A Logical Interface University Database Data Lab Timetable course student lecturer Database Management System Teaching Schedule Data Dictionary or System Catalog University Database Metadata Tutorials?QUERIES 12

File System Approach Uncontrolled redundancy Inconsistent data Inflexibility Limited data sharing Poor enforcement of standards Low programmer productivity Excessive program maintenance Excessive data maintenance 13

DBMS Approach Controlled redundancy consistency of data & integrity constraints Integration of data self-contained represents semantics of application Data and operation sharing multiple interfaces Services & controls security & privacy controls backup & recovery enforcement of standards Flexibility data independence data accessibility reduced program maintenance Ease of application development 14

However... Summary: If an application is simple stringent real-time single user static, files are the option of choice DBMS downside: more expensive more complex general In a file system, data is physically accessed and not integrated In a DBMS, data is logically accessed and integrated: query language data dictionary 15