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Advanced Databases Introduction
dr. Toon Calders prof. dr. Jan Paredaens
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Outline Motivation for the course Other DH courses
Practical organization Course topics Project Overview of changes
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Motivation for the Course
Database = a piece of software to handle data: store, maintain, and query Most ideal system situation-dependent data type: simple / semi-structured / complex / … types of queries: simple lookup / analytical / … type of usage: multi-user / single-user / distributed / … …
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Motivation for the Course
Relational databases are tuned towards: simple data simple, ad-hoc queries multiple users Other models are more suitable for other types of data Object-Oriented, Deductive, Semi-Structured Databases, Data warehouses
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Motivation for the Course
Study different data models Advantages, disadvantages Conceptual level what are the important notions? What’s underneath? In a scientific way exact, not just claims
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Motivation for the Course
Student knows: different database models Understands: why they are introduced conceptual notions Is able to: quickly master vendor-specific products
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Outline Motivation for the course Other DH courses
Practical organization Course topics Project Overview of changes
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Other DH Courses Relational database systems Other database models
(2ID05) Databases and Data Modelling (2ID35) Database Technology transations, indexing, query optimization, distributed DB Other database models (2ID45) Advanced Databases (2II15) Data Mining (2ID25) Information Retrieval (2ID99) Capita Selecta DH
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Outline Motivation for the course Other DH courses
Practical organization Course topics Project Overview of changes
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Practical Organization
In principle … Wed 8:45 10:30 Practical session M 1.46 no new material opportunity to practice, ask questions together solve exercises Fri 10:45 12:30 Lectures HG 6.09 XML : Paredaens (6 lectures) other parts: Calders
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Practical Organization
Important information Subscribe to 2ID45 on studyweb ! messages to the whole class group lecture postponed, room changes, …
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Practical Organization
Course material Book: Silberschatz, Korth, Sudarshan. Database system concepts 5th edition. McGraw-Hill International Lots of additional material on course webpage papers slides solutions to exercises …
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Practical Organization
Grades: 70% written exam 30% group project No project = no grade Grade for the project can be transfered to August, similar for grade for the exam Grades expire in August
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Outline Motivation for the course Other DH courses
Practical organization Course Topics Project Overview of changes
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Course Topics Limitations of the relational model Deductive databases
Object-Oriented Databases Data Warehousing & OLAP Semi-Structured data
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Limitations of the relational model
Not every query can be expressed Transitive closure cannot be expressed in Relational Algebra Give all cities reachable from Antwerp by plane Give all smallest components of a part Give all decendants of person X Not even if you’re very smart … proof Extension to other relational query languages
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Deductive Databases Motivation is two-fold:
add deductive capabilities to databases; the database contains: facts (intensional relations) rules to generate derived facts (extensional relations) Database is knowledge base Extend the querying datalog allows for recursion
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Deductive Databases Datalog as engine of deductive databases
similarities with Prolog has facts and rules rules define -possibly recursive- views Semantics not always clear safety negation recursion
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Deductive Databases g(a,b). g(b,c). g(a,d). reach(X,X) :- g(X,Y).
reach(X,Y) :- g(X,Y). reach(X,Z) :- reach(X,Y), reach(Y,Z). node(X) :- g(X,Y). node(Y) :- g(X,Y). unreach(X,Y) :- node(X), node(Y), not reach(X,Y).
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Deductive Databases In this topic we study:
How to handle negation and recursion in the same program How to efficiently evaluate Datalog queries
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OO Databases Many applications require the storage and manipulation of complex data design databases geometric databases … Object-Oriented programming languages manipulate complex objects classes, methods, inheritance, polymorphism
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OO Databases Very simple example:
Class book set of authors title set of keywords Extremely simple to model in OO language Hard in relational database!
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OO Databases In many applications persistency of the data is nevertheless required protection against system failure consistency of the data Mapping: object in OO language tuples of atomic values in relational database is often problematic
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OO Databases Either we ignore the multivalued dependencies
This table is in 3NF, BCNF Title Author Keyword Database System Concepts Silberschatz Database Korth Sudarshan Storage
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OO Databases Or we go to 4NF Title Author Database System Concepts
Silberschatz Korth Sudarshan Title Keyword Database System Concepts Database Storage
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OO Databases Basically OODB = persistent OO programming language
Very important concept rather uninteresting scientifically This topic will mainly be self-study Reading bookchapter + Q & A session
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Data Warehousing & OLAP
Warehouse Extract Transform Load Refresh OLAP Engine Monitor & Integrator Metadata Data Sources Front-End Tools Serve Data Marts Operational DBs other sources Data Storage OLAP Server Analysis Query/Reporting Data Mining ROLAP BI applications includes: Query and Reporting Online Analytical Processing (OLAP) Statistical Analysis Decision Support Systems Forecasting Data Mining Other Meta data is the data defining warehouse objects. It has the following kinds Description of the structure of the warehouse schema, view, dimensions, hierarchies, derived data defn, data mart locations and contents Operational meta-data data lineage (history of migrated data and transformation path), currency of data (active, archived, or purged), monitoring information (warehouse usage statistics, error reports, audit trails) The algorithms used for summarization The mapping from operational environment to the data warehouse Data related to system performance warehouse schema, view and derived data definitions Business data business terms and definitions, ownership of data, charging policies
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Data Warehousing & OLAP
Transaction processing Operational setting Up-to-date = critical Simple data Simple queries; only « touch » a small part of the database Flight reservations ticket sales do not sell a seat twice reservation, date, name Give flight details of X List flights to Y
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Data Warehousing & OLAP
Decision support Off-line setting « Historical » data Summarized data Integrate different databases Statistical queries Flight company Evaluate ROI flights Flights of last year # passengers per carrier for destination X Passengers, fuel costs, maintenance info Average % of seats sold/month/destination
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Data Warehousing & OLAP
In this topic we will study: Conceptual models for decision support Database explosion problem Efficient implementation strategies indexing, view materialization
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XML Why is XML important? XML is like HTML but
simple open non-proprietary widely accepted data exchange format XML is like HTML but no fixed set of tags X = “extensible” no fixed semantics (c.q. representation) of tags representation determined by separate ‘stylesheet’ semantics determined by application no fixed structure user-defined schemas simple: human readable, machine readable open / non-proprietary: does not belong to Microsoft / IBM etc., documentation is freely available, means also that a lot of (often free) software is already available widely accepted: W3C standard
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XML <PersonList Type="Student" Date="2004-12-12">
<Title Value="Student List"/> <Contents> <Person> <Name>Jan Vijs</Name> <Id>11</Id> <Address> <Number>123</Number> <Street>Turnstreet</Street> </Address> </Person> <Id>66</Id> <Street>Hole Rd</Street> </Contents> </PersonList>
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XML In this topic: XML XQuery, XSLT LiXQuery Taught by prof Paredaens
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Outline Motivation for the course Other DH courses
Practical organization Course Topics Project Overview of changes
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Project Pick one of the 4 topics: Formulate your own project
deductive databases / rule-based systems object-oriented databases data warehouses semi-structured databases Formulate your own project illustrating the different course concepts showing you mastered the technology
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Project Make a project proposal ( WEEK 10 ) Status report ( WEEK 15 )
examples of last year will be given fulfilling certain constraints listing technologies to be used Status report ( WEEK 15 ) Final report ( WEEK 20 ) Project presentations ( WEEKS 21 & 22 )
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Outline Motivation for the course Other DH courses
Practical organization Course Topics Project Overview of changes
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Overview of Changes First some facts and figures regarding Spring 2008
Heterogeneous group Outside NL, HBO, BSc TU/e CSE BIS
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Overview of Changes Some suggestions I decided to act upon:
1. Start with the difficult material: expressiveness of RA Gaifman locality 2. Too much time is being spent on XML (5+5) (6+3) & topic (XSLT) has been added 3. Disproportional weight given to XML in exam project no longer exclusively XML
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Overview of Changes Some suggestions I decided to act upon:
4. Some materials and instruction just too hard extra exercices will be added; more modular 5. The course was split up in lots of individual subjects, with no apparent relation to one another tried to handle that in the course motivation
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Overview of Changes Some suggestions that were ignored:
A google for 'advanced databases' returns quite some courses from other universities that look interesting to me. Perhaps the lecturers could take a look at those. When (re-)constructing the course last year other universities’ ADB courses were surveyed. Many of the interesting topics are already handled in other courses (Data Mining, Information retrieval, Database technology)
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Overview of Changes Some suggestions that were ignored:
Don't discuss prerequisite knowledge too much, it is prerequisite. Heterogeneous group. Balance the course subjects more, TC was discussed very specific while the other 3 subjects where treated in global. Time spent on TC is justified by its difficulty and its importance for database theory + motivates OODB & Deductive DB
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Overview of Changes Take-away message
(some?) lecturers do act on questionnaires filling out the questionnaires is useful
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Overview of Changes Take-away message
(some?) lecturers do act on questionnaires filling out the questionnaires is useful
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Summary Relational model has limitations
simple queries simple data OODBs allow complex data types Deductive databases, datalog complex queries Somewhere in-between: datawarehouses and OLAP special requirements, special datastructures Semi-structured data can be stored in XML Project complements theoretical lectures Instructions for clarification
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!! See you on Friday !!
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