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Carnegie Mellon Univ. Dept. of Computer Science 15-415 - Database Applications

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Carnegie Mellon Univ. Dept. of Computer Science 15-415 - Database Applications. C. Faloutsos E-R diagrams. Overview. concepts Entities Relationships Attributes Specialization/Generalization Aggregation turning E-R diagrams to tables. Tools. Entitie s (‘entity sets’). N. M.

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Carnegie Mellon Univ. Dept. of Computer Science 15-415 - Database Applications
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  1. Carnegie Mellon Univ.Dept. of Computer Science15-415 - Database Applications C. Faloutsos E-R diagrams

  2. Overview • concepts • Entities • Relationships • Attributes • Specialization/Generalization • Aggregation • turning E-R diagrams to tables 15-415 - C. Faloutsos

  3. Tools Entitie s (‘entity sets’) N M Relationships (‘rel. sets’) and mapping constraints P attributes 15-415 - C. Faloutsos

  4. Example Students, taking courses, offered by instructors; a course may have multiple sections; one instructor per course nouns -> entity sets verbs -> relationships 15-415 - C. Faloutsos

  5. ... name STUDENT ssn INSTRUCTOR issn 15-415 - C. Faloutsos

  6. ... name STUDENT c-id ssn c-name COURSE INSTRUCTOR issn but: sections of course (with different instructors)? 15-415 - C. Faloutsos

  7. ssn STUDENT c-id COURSE SECTION s-id but: s-id is not unique... INSTRUCTOR issn 15-415 - C. Faloutsos

  8. ssn STUDENT N c-id takes M COURSE s-id SECTION INSTRUCTOR issn 15-415 - C. Faloutsos

  9. STUDENT N c-id takes M s-id SECTION COURSE N teaches 1 INSTRUCTOR 15-415 - C. Faloutsos

  10. Cardinalities • 1 to 1 (example?) • 1 to N • N to M 15-415 - C. Faloutsos

  11. STUDENT N c-id takes M 1 N has s-id SECTION COURSE N teaches 1 INSTRUCTOR 15-415 - C. Faloutsos

  12. More details • ‘weak’ entities: if they need to borrow a unique id from a ‘strong entity - DOUBLE box. • ‘c-id’ + ‘s-id’: unique id for SECTION • discriminator (eg., ‘s-id’) c-id 1 N s-id has SECTION COURSE 15-415 - C. Faloutsos

  13. More details • self-relationships - example? 15-415 - C. Faloutsos

  14. manages 1 EMPLOYEE N 15-415 - C. Faloutsos

  15. More details • 3-way and k-way relationships? N M EMPLOYEE TOOL uses P PROJECT 15-415 - C. Faloutsos

  16. More details - attributes • candidate key (eg., ssn; employee#) • primary key (a cand. key, chosen by DBA) • superkey (eg., (ssn, address) ) • multivalued or set-valued attributes (eg., ‘dependents’ for EMPLOYEE) • derived attributes (eg., 15% tip) 15-415 - C. Faloutsos

  17. More details: • in the text: (eg., ‘total participation’) SECTION 0:N teaches 1:1 INSTRUCTOR 15-415 - C. Faloutsos

  18. Overview • concepts • Entities • Relationships • Attributes • Specialization/Generalization • Aggregation • turning E-R diagrams to tables 15-415 - C. Faloutsos

  19. eg., students: part time (#credit-hours) and full time (major) Specialization name STUDENT ssn IS-A major FT-STUDENT PT-STUDENT #credits 15-415 - C. Faloutsos

  20. Observations • Generalization: exact reverse of ‘specialization’ • attribute inheritance • could have many levels of an IS-A hierarchy 15-415 - C. Faloutsos

  21. treat a relationship as an entity rarely used Aggregation M N MAKER HD CPU 15-415 - C. Faloutsos

  22. Overview • concepts • Entities • Relationships • Attributes • Specialization/Generalization • Aggregation • turning E-R diagrams to tables 15-415 - C. Faloutsos

  23. STUDENT N c-id grade takes M 1 N has s-id SECTION COURSE N teaches 1 INSTRUCTOR 15-415 - C. Faloutsos

  24. Strong entities just list the attributes, and underline the primary key, eg. STUDENT(ssn, name, address) 15-415 - C. Faloutsos

  25. Multivalued attributes Eg., EMPLOYEE with many dependents: • a new table, with (ssn, dependent-name) 15-415 - C. Faloutsos

  26. Relationships • get primary keys all involved entities • primary key - depends on cardinality • 1 to 1: either eg EMPLOYEE( ssn, empno, name, ...) • 1 to N: the key of the ‘N’ part eg. TEACHES( issn, c-id, s-id) • N to M: both keys - eg TAKES( ssn, c-id, s-id, grade) 15-415 - C. Faloutsos

  27. Relationships • 1 to N: no need for separate table - eg., SECTION( issn, room-num, c-id, s-id) instead of SECTION1(c-id, s-id, room-num) TEACHES(issn, c-id, s-id) • for rel. between strong and corresponding weak entity, no need for table, at all! 15-415 - C. Faloutsos

  28. Generalization/Spec. Two solutions: - one table for each or - no table for super-entity (pros and cons?) 15-415 - C. Faloutsos

  29. Generalization/Special. Eg., STUDENT(ssn, name, address) PT-STUDENT( FT-STUDENT( 15-415 - C. Faloutsos

  30. Generalization/Special. Eg., STUDENT(ssn, name, address) PT-STUDENT( ssn, num-credits) FT-STUDENT( ssn, major) 15-415 - C. Faloutsos

  31. Generalization/Special. no super-entity: [STUDENT(ssn, name, address)] PT-STUDENT( ssn, num-credits FT-STUDENT( ssn, major 15-415 - C. Faloutsos

  32. Generalization/Special. no super-entity: [STUDENT(ssn, name, address)] PT-STUDENT( ssn, num-credits, name, address) FT-STUDENT( ssn, major, name, address) 15-415 - C. Faloutsos

  33. Aggregation • make table, with primary keys of all involved entities 15-415 - C. Faloutsos

  34. Overview • concepts • Entities • Relationships • Attributes • Specialization/Generalization • Aggregation • turning E-R diagrams to tables 15-415 - C. Faloutsos

  35. Summary • E-R Diagrams: a powerful, user-friendly tool for data modeling: • Entities (strong, weak) • Attributes (primary keys, discriminators, derived, multivalued) • Relationships (1:1, 1:N, N:M; multi-way) • Generalization/Specialization; Aggregation 15-415 - C. Faloutsos

  36. attribute (strong) entity set weak entity set relationship set identifying rel. set for weak entity Summary - cont’d multivalued attribute derived attribute 15-415 - C. Faloutsos

  37. A primary key discriminator IS-A A total generalization M l’:h’ N l:h cardinalities cardinalities with limits Summary - cont’d (e.t.c. - see book for alternative notations) 15-415 - C. Faloutsos

  38. Conclusions • E-R Diagrams: a powerful, user-friendly tool for data modeling. 15-415 - C. Faloutsos