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Advanced Database Applications: CS562 -- Fall 2011

Advanced Database Applications: CS562 -- Fall 2011. George Kollios Boston University. Prof. George Kollios Office: MCS 288 Office Hours: Monday 2:30pm-4:00pm Thursday 11:00am-12:30pm Web: http://www.cs.bu.edu/faculty/gkollios/ada11. History of Database Technology.

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Advanced Database Applications: CS562 -- Fall 2011

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  1. Advanced Database Applications:CS562 -- Fall 2011 George Kollios Boston University

  2. Prof. George Kollios Office: MCS 288 Office Hours: Monday 2:30pm-4:00pm Thursday 11:00am-12:30pm Web: http://www.cs.bu.edu/faculty/gkollios/ada11

  3. History of Database Technology • 1960s: Data collection, database creation, IMS and network DBMS • 1970s: Relational data model, relational DBMS implementation • 1980s: RDBMS, advanced data models (extended-relational, OO, deductive, etc.) and application-oriented DBMS (spatial, scientific, engineering, etc.) • 1990s—2000s: Data mining and data warehousing, multimedia databases. • 2010s-: Data on the cloud, privacy, security. Social network data (facebook, twitter, etc), Web 3.0 and more

  4. Query Optimization and Execution Relational Operators Files and Access Methods Buffer Management Disk Space Management DB Modern Database Systems Extend these layers Structure of a RDBMS • A DBMS is an OS for data! • A typical RDBMS has a layered architecture.

  5. Index Methods for RDBMS • Hashing Methods: • Linear Hashing, Extensible Hashing • B-tree family: • B+-trees and variations • Both of them are one-dimensional

  6. Overview of the course • Spatial Database Systems • GIS, CAD/CAM, EOSDIS project NASA • Manages points, lines and regions • Temporal Database Systems • Billing, medical records • Spatio-temporal Databases • Moving objects, changing regions, etc

  7. Overview of the course • Multimedia databases • A multimedia system can store and retrieve objects/documents with text, voice, images, video clips, etc • Time series databases • Stock market, ECG, trajectories, etc

  8. Multimedia databases • Applications: • Digital libraries, entertainment, office automation • Medical imaging: digitized X-rays and MRI images (2 and 3-dimensional) • Query by content: (or QBE) • Efficient • ‘Complete’ (no false dismissals)

  9. Database Outsourcing Owner(s): publish database Servers: host database and provide query services Clients: query the owner’s database through servers Clients Owner Server Security Issues: untrusted or compromised servers H. Hacigumus, B. R. Iyer, and S. Mehrotra, ICDE02

  10. Security Issues • Query authentication and verification • Data privacy and confidentiality • Access control

  11. Databases on the Cloud • Cloud computing is a new trend • Data are stored “in the cloud”, accessed from everywhere • System should maximize utility, minimize response time • Use of large clusters (data centers) • MapReduce

  12. Semantic Web: A lot of data on the web… • There is a lot of data on the web… • Need to make them more accessible and useful • Machine should understand some of the semantics of the web data • Semantic Web: "a web of data that can be processed directly and indirectly by machines.“Tim Berners-Lee

  13. Semantic Web • From document sharing to data sharing • Issues/Challenges: • Vastness:More than 24B pages • Vagueness and Uncertainty: meaning of “young”, “cheap”, “close”, etc. • Inconsistency: contradictions on data and semantics • Deceit: a user may want to mislead, deceive

  14. Probabilistic (or Uncertain) Databases • Another approach to model many real world applications. • Data records are probabilistic or uncertain • Need to formally model and query (correctly and efficiently)=> Prob DBs

  15. What is a Probabilistic Database ? • “An item belongs to the database” is a probabilistic event • Tuple-existence uncertainty • Attribute-value uncertainty • “A tuple is an answer to the query” is a probabilistic event

  16. Two Types of Probabilistic Data • Database is deterministicQuery answers are probabilistic • E.g., IR-style/”fuzzy-match” queries • Approximate query answers • Database is probabilisticQuery answers are probabilistic

  17. Prob DB Models • The database is a probability distribution over possible instances of (deterministic) databases

  18. Example: x-relations [Trio] Each x-tuple represents a discrete probability distribution of tuples x-tuples are mutually independent, and disjoint

  19. Back to reality… • Grading: • 4 Homeworks : 0.2 • 1 Term Project: 0.3 • You need to talk to me and get a problem • Project proposal due in a couple of weeks • Midterm: probably on Oct 26, in class: 0.2 • Final: Dec 20 at 12:30pm (?): 0.3

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