1. Matthew P. Johnson, OCL3, CISDD CUNY, June 20051 OCL3 Oracle 10g: SQL & PL/SQL Session #1 Matthew P. Johnson CISDD, CUNY June, 2005

2. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 2 Personnel Instructor: Matthew P. Johnson  mpjohnson-at-gmail.com mpjohnson-at-gmail.com TA: Ratna Priya Moganti  rmoganti7-at-yahoo.com rmoganti7-at-yahoo.com Admin: Dawn Kleinberger  dkleinberger-at-gc.cuny.edu dkleinberger-at-gc.cuny.edu

3. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 3 Communications Web page:  http://pages.stern.nyu.edu/~mjohnson/oracle/ http://pages.stern.nyu.edu/~mjohnson/oracle/  syllabus  course policies  reading assignments  etc.

4. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 4 Acknowledgements Thanks to Ramesh at NYU, Ullman, et al., Raghu and Johannes, Dan Suciu, Arthur Keller, David Kuijt for course materials See classpage for other related, antecedent DBMS courses

5. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 5 What is a Database? A very large, integrated collection of data. Models real-world enterprise.  Entities students, courses, instructors, TAs  Relationships George is currently taking OCL Dick is currently teaching OCL Condi is currently TA-ing OCL but took it last semester Database Management System (DBMS): large software package designed to store and manage databases

6. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 6 Databases are everywhere: ordering a pizza Databases involved? 1. Pizza Hut’s DB stores previous orders by customer stores previous credit cards used 2. Credit card records huge databases of (attempted) purchases location, date, amount, parties 3. Got approved by credit-report companies 4. phone company’s records Local Usage Details (“Pull his LUDs, Lenny.”) 5. Caller ID ensures reported address matches destination

7. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 7 Your wallet is full of DB records Driver’s license Credit cards Medical insurance card Social security card Gym membership Individual checks Dollar bills (w/serial numbers) Maybe even photos (ids on back)

8. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 8 Databases are everywhere Q: Websites backed by DBMSs?  retail: Amazon, etc. data-mining: “Page You Made”  search engines: Google, etc.  directories: Internic, etc.  searchable DBs: IMDB, tvguide.com, etc. Q: Non-web examples of DBMSs?  airline bookings  criminal/terrorist: TIA  NYPD’s CompStat all serious crime stats by precinct  Retailers: Wal-Mart, etc. when to re-order, purchase patterns, data-mining  Genomics!

9. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 9 Example of a Traditional DB App Suppose we are building a system to store the information about: checking accounts savings accounts account holders state of each of each person’s accounts

10. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 10 Can we do it without a DBMS? Sure we can! Start by storing the data in files: checking.txt savings.txt customers.txt Now write C or Java programs to implement specific tasks

11. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 11 Doing it without a DBMS... Transfer $100 from George’s savings to checking: Read savings.txt Find&update the record “George” balance -= 100 Write savings.txt Read checking.txt Find&update the record “George” balance += 100 Write checking.txt Read savings.txt Find&update the record “George” balance -= 100 Write savings.txt Read checking.txt Find&update the record “George” balance += 100 Write checking.txt Write a C program to do the following:

12. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 12 Problems without an DBMS... 1.System crashes:  Q: What is the problem ?  A: George lost his $100  Same problem even if reordered 2.Simultaneous access by many users  George and Dick visit ATMs at same  Lock checking.txt before each use–what is the problem? Read savings.txt Find&update the rec “George.” Write savings.txt Read checking.txt Find&update the rec “George” Write checking.txt Read savings.txt Find&update the rec “George.” Write savings.txt Read checking.txt Find&update the rec “George” Write checking.txt CRASH !

13. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 13 Problems without an DBMS... 3.Large data sets (say 100s of GB or TBs)  Why is this a problem? No indices  Finding “George” in huge flatfile is expensive Modifications intractable without better data structures  “George”  “Georgie” is very expensive  Deletions are very expensive

14. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 14 Problems without a DBMS... 5.Security?  File system may be insecure  File system security may be coarse 6.Application programming interface (API)?  suppose need other apps to access DB 7.How to interact with other DBMSs?

15. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 15 General problems to solve In building our own system, many Qs arise:  how do we store the data? (file organization, etc.)  how do we query the data? (write programs…)  make sure that updates don’t mess things up? leave the DB “consistent”  provide different views on the data? e.g., ATM user’s view v. bank teller’s view  how do we deal with crashes? Too hard! Go buy Oracle! Q: How does a DBMS solve these problems? A: Long story; see other courses/books

16. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 16 Big issue: Transaction processing Grouping of several queries (or other database actions) into one transaction ACID properties  Atomicity all or nothing  Consistency constraints on relationships  Isolation concurrency control Simulated solipsism  Durability Crash recovery

17. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 17 Atomicity & Durability Saw how George lost $100 with makeshift software A DBMS prevents this outcome  xacts are all or nothing One idea: Keep a log (history) of all actions in set of xacts  Durability: Use log to redo or undo certain ops in crash recovery  Atomicity: don’t really commit changes until end Then, all at once

18. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 18 Isolation Concurrent execution is essential for performance.  Frequent, slow disk accesses   don’t waste CPU – keep running Interleaving actions of different user programs  can lead to inconsistency:  e.g., two programs simultaneously withdraw from the same account DBMS ensures such problems don’t arise:  users can pretend they are using a single-user system

19. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 19 Isolation Contrast with a file in two Notepads  Strategy: ignore multiple users  whichever saves last wins  first save is overwritten Contrast with a file in two Words  Strategy: blunt isolation  One can edit  To the other it’s read-only

20. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 20 Consistency Each xant (on a consistent DB) must leave it in a consistent state  can define integrity constraints  checks the defined claims about the data remain true

21. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 21 Data Models Every DBMS uses some data model: collection of concepts for describing data Schema: description of partic set of data, using some data model Relational data model: most widely used (by far) data model  Oracle, DB2, SQLServer, other SQL DBMSs  main concept: relation ~ table of rows & columns  a rel’s schema defines its fields

22. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 22 Example: university database Conceptual schema:  Students(ssn: string, name: string, login: string, age: int, gpa: real)  Courses(cid: string, cname: string, credits: int)  Enrolled(sid:string, cid:string, grade: string) Physical schema:  Relations stored as unordered text files.  Indices on first column of each rel External Schema (View):  Course_info(ssn: string, name: string)  My_courses(cname: string, grade: string)

23. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 23 How the programmer sees the DBMS Start with DDL to create tables: Continue with DML to populate tables: CREATE TABLE Students ( Name CHAR(30), SSN CHAR(9) PRIMARY KEY NOT NULL, Category CHAR(20) ); CREATE TABLE Students ( Name CHAR(30), SSN CHAR(9) PRIMARY KEY NOT NULL, Category CHAR(20) ); INSERT INTO Students VALUES('Howard', '123456789', 'undergraduate'); INSERT INTO Students VALUES('Howard', '123456789', 'undergraduate');

24. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 24 How the programmer sees the DBMS Tables: Still implemented as files, but behind the scenes can be quite complex Students: Courses: “data independence” = separate logical view from physical implementation Takes:

25. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 25 Querying: Structured Query Language Find all the students who have taken OCL2:  Find all the students who OCL2 last fall:  Find the students’ names:  Query processor does this efficiently SELECT SSN FROM Takes WHERE CID='OCL2'; SELECT SSN FROM Takes WHERE CID='OCL2'; SELECT SSN FROM Takes WHERE CID='OCL2' AND Semester='Fall, 2003' SELECT SSN FROM Takes WHERE CID='OCL2' AND Semester='Fall, 2003' SELECT Name FROM Students, Takes WHERE Students.SSN=Takes.SSN AND CID='OCL2' AND Semester='Fall, 2003'; SELECT Name FROM Students, Takes WHERE Students.SSN=Takes.SSN AND CID='OCL2' AND Semester='Fall, 2003';

26. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 26 Database Industry Relational databases are a great success of theoretical ideas  based on most “theoretical” type of math there is: set theory DBMS companies are among the largest software companies in the world Oracle, IBM (with DB2), Microsoft (SQL Server, Microsoft Access), Sybase Also opensource: MySQL, PostgreSQL, etc. $20B+ industry XML (“semi-structured data”) also important  New lingua franca for exchanging data

27. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 27 Databases are used by DB app programmers  desktop app programmers  web developers Database administrators (DBAs)  design schemas  security/authorization  crash recovery  tuning  better paid than programmers! Everyone else (perhaps indirectly) “You may not be interested in databases, but databases are interested in you.” - Trotsky

28. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 28 The Study of DBMS Several aspects:  Modeling and design of databases  DBMS programming: querying and update  DBMS implementation This course covers the first two Also will look at some more advanced areas  XML, data-warehousing, regexps

29. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 29 Course outline Two biggest topics:  SQL  PL/SQL But also: Database design:  Entity/Relationship models  Modeling constraints The relational model:  Relational algebra  Transforming E/R models to relational schemas

30. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 30 Outline (Continued) SQL views and triggers Connecting to a Oracle from programming languages Web apps Data warehousing XML May change as course progresses  partly in response to audience

31. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 31 Textbook Oracle Database 10g PL/SQL 101  by Christopher Allen  Hardcover: 416 pages  Publisher: McGraw-Hill/ Osborne Media  ISBN: 0072255404  1st edition (August 10, 2004)  Distributed in class

32. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 32 SQL Readings Optional reference: Oracle PL/SQL Programming Online (free) SQL tutorials include:  A Gentle Introduction to SQL (http://sqlzoo.net/)http://sqlzoo.net/  SQL for Web Nerds (http://philip.greenspun.com/sql/)http://philip.greenspun.com/sql/

33. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 33 On-going Feedback Don’t wait until the class is over to give feedback on improving it  too late for you then! Send mail if you have questions or concerns “We’re in touch, so you be in touch.”

34. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 34 So what is this course about, really? A bit of everything! Languages: SQL, XPath, XQuery Data modeling Some theory!  Functional dependencies, normal forms  e.g., how to find most efficient schema for data Writing lots of SQL queries Lots of coding in PL/SQL Business DBMS examples/cases Most importantly: how to meet real-world needs

35. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 35 For right now: additional written survey Email to mpjohnson-at-gmail.com: name email previous cs/is/math/logic courses/background previous programming experience  Perl?  PHP?  HTML? Job: programmer, DBA, etc. why taking class

36. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 36 Agenda Last time: intro, RDBMS, ACID test This time: E/R model 1. Identify entity sets, relations and attributes 2. One-one, one-many, many-many relations 3. Simple ER diagrams to model a situation 4. 3-way relationships; Converting to binary 5. Entities with multiple roles 6. Subclasses Design issues 1. Principles of faithfulness & simplicity in ER diagrams 2. Redundancy 3. Whether an element should be an attribute or entity set 4. Replacing a relationships with entity sets

37. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 37 DB development path the World E/R design Relational schema Relational DB

38. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 38 Entity/Relationship (E/R) Model A popular data model – useful to database designers Graphical representation of miniworld Helps design the database, not implement it E/R design is translated to a relational design  relational design then implemented in an RDBMS Elements of model  Entities  Entity Sets  Attributes  Relationships (!= relations!)

39. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 39 Elements of E/R Model: Entity Sets Entity: like an object  e.g. President Bush  Particular instance of a concept Entity set: set of one sort of entities or a concept  e.g. World leaders  Generally, same set of attributes Represented by a rectangle A “good” entity set – you decide  Common properties  Correspond to class of phys. or bus. objects (People, products, accounts, grades, etc.) World Leader

40. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 40 Elements of E/R Model: Attributes Properties of entities in entity set  Like fields in a struct  Like columns in a table/spreadsheet  Like data members in an object Values in some domain (e.g., ints, strings) Represented by ovals: Assumed atomic  But could have limited structure  Ints, strings, etc. ID Name Student

41. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 41 Elements of E/R Model: Relationships Connect two or more entity sets  e.g. students enroll in courses  Binary relationships: connect two entity sets – most common  Multiway relationships: connect several entity sets Represented by diamonds StudentsEnrollCourses

42. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 42 Elms of E/R Model: Rel’ships (cont’d) Students Enroll in courses Courses are Held in rooms The E/R data model: StudentsEnrollCourses Held Rooms Name ID

43. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 43 A little set theory A mathematical set =a collection of members A set is defined by its members  “Are you in or are you out?”  No other structure, no order, no duplicates allowed Sets can be specified by listing:  {1, 2, 3, …} = N  {1, 2, George Bush} (few applications, but valid) Or by “set-builder” notation:  { x in N: 2 divides x} = ?  { x in Presidents | reelected(x)} = ?  {2x: x in N} = ?

44. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 44 A little set theory One set can be a subset of another (which is then a superset of it)  ReelectedPresidents is a subset of Presidents  Also, RP is a proper subset of Pres – some lost reelection Given two sets X and Y, the cross product or Cartesian product is X x Y = {(x,y): x in X, y in Y} = the set of all ordered pairs in which the first comes from X and the second comes from Y Important: (x,y) != {x,y} In an order pair or tuple  Order matters  Duplicates are allowed

45. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 45 A little set theory Mathematically, a relation(ship) between X and Y is just a subset of X x Y = all those pairs (x,y) s.t. x is related to y Example: owner-of O on People, Cats  O(MPJ, Gödel) holds The equals relation E on N, N:  E(3,3) holds because 3 = 3  E(3,4) does not hold  E is still a set: E = {(1,1), (2,2), (3,3), …} Father of relation F on People, People:  F(GHWB, GWB) holds  F(GWB, GHWB) does not hold   Relations aren’t necessarily symmetric

46. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 46 Many-many Multiplicity of Relation(ship)s Many-one One-one Representation of relationships No arrow: many-to-many Sharp arrow: many-to-one Rounded arrow: “exactly one”  “key constraint” One-one:

47. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 47 Multiplicity of Relation(ship)s StudentsEnrollsCourses Many-to-many: Student Live Residence hall Many to one: a student lives in <= 1 residence hall Many to exactly one: a student must live in a residence hall Student Live Residence hall

48. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 48 Multiplicity, set-theoretically Assume no vars below are equal Many-one means:  if (x1,y1) in R then (x1,y2) cannot be in R One-many means:  if (x1, y1) in R then (x2,y1) cannot be in R One-one means:  if (x1,y1) in R, then neither (x2,y1) nor (x1,y2) can be in R Notice: one-one is stronger than many-one One-one implies both many-one and one-many

49. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 49 E/R Diagram e.g. StudentsCourses Enrolls ID Name ID Name Assisting TA ID Name

50. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 50 E/R Diagrams Works if each TA is a TA of all students  Student and TA connected only through Course But what if students were divided among multiple TAs?  Then a student in OCL3 would be related to only one of the TA's for OCL3—which one?  Schema doesn’t store enough info 3-way relationship is helpful here

51. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 51 Multiway Relationships Students Courses TAs Enrolls StudentsCoursesTAs Condi C20.0046 Donald George C20.0046 Dick Alberto C20.0046 Colin ……… Enrolls entries: NB: Enrolls determines TA: (student, course)  at most one TA

52. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 52 Converting multiway relships to binary Some models limit relationships to binary Multiway relationship – equivalent collection of binary, many to one relationships Replace relationship with connecting entity set Students Courses TAs Enrolls Student-of Course-of TA- of NB: Enrolls has no attributes!

53. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 53 Second multiway e.g.: renting movies Scenario: a Customer Rents a Movie from a VideoStore on a certain date Q: Which entity does date belong to? A: To the fact of the renting Relationships can have attributes  always (implicitly) many-one Rental VideoStore Customer Movie date

54. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 54 Second multiway e.g.: renting movies But they don’t have to Relationship attributes can be replaced with (trivial) new entities Rental VideoStore Customer Movie date Date

55. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 55 Where can we draw arrows? (store, video, customer)  date ? (store, video, date)  customer ? (store, date, customer)  video ? (video, date, customer)  store ? Second multiway e.g.: renting movies Rental VideoStore Customer Movie date

56. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 56 Q: (Why) does it matter? Round arrow benefit:  Obvious: One item takes less space than many  Less obvious: easier to access one item x than set of one item {x} In programming: an int v. a linked list with just one int Regular arrow benefit:  Mapping to a set of either one elm or none seems bad  But not implemented this way  Always one element, but that value may be NULL Lesson: it pays to identify your relship’s multiplicity

57. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 57 Second multiway e.g.: renting movies Convert to binary? Rental VideoStore Customer Movie date Rental Customer Store Movie StoreOf MovieOf BuyerOf date

58. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 58 Roles in relationships Entity set appears more than once in a relship  Generally distinct entities Each appearance is in a different role Edges labeled by roles Pre-req Prereq Successor Course Course (Pre-req) Course (Successor) AccountingFinance-I Derivatives Finance-IFinance-II CalculusDerivatives

59. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 59 Subclasses in the E/R model Some entities are special cases of others Conversely: some are generalizations  Humans are specialized mammals  Grad students are specialized students And, in turn, specialized mammals Subclass A isa B  Represented by a triangle  Always one-to-one, though arrows omitted  Root is more general  Multiple inheritance is allowed!  A single entity may consist of all components (sets of fields) in arbitrary ESs and their ancestors

60. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 60 Subclasses Movies Cartoons Murder- Mysteries isa Voices Weapon stars length title year Lion King Component “Lion King”: atts of Movies; relship Voices “Roger Rabbit”: atts of Movies; relship Voices; att weapon Roger Rabbit TX Chainsaw Massacre

61. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 61 E/R inheritance v. OO inheritance In a OOP class hierarchy, children also inherit “attributes” from parents  But an object is an instance of one class In E/R, an entity may be composed of components from multiple, not-directly-related ESs  Roger Rabbit is composed of components from Cartoons, Murder Mysteries, and Movies  We could create a Cartoon Murder Mysteries ES if there were any atts specific to them So the real difference: In E/R, can have implicit multiple inheritance between any set of IS-A- connected nodes (sharing a root)

62. Matthew P. Johnson, OCL3, CISDD CUNY, June 2005 62 Next Lab 1 online