1. Christoph F. Eick Introduction Data Management This Week 1. Introduction to Databases 2. Course Information 3. Grading and Other Things 4. Questionnaire 5. The E/R Data Model

2. Christoph F. Eick Introduction Data Management Textbooks for COSC 6340  Required Text: Raghu Ramakrishnan and Johannes Gehrke, Data Management Systems, McGraw Hill, Third Edition, 2002 (complication: the chapter numbers in the new edition are different!!)  Recommended: Jiawei Han and Micheline Kamber, Data Mining: Concepts and Techniques, Morgan Kaufman Publishers, 2001, ISBN 1-55860-489-8 (4 chapters will be covered)  Other books with relevant material: Ramez Elmasri and Shamkant Navathe, Fundamentals of Database Systems, Third Edition Addison Wesley ISBN: 0-8053- 1755-4

3. Christoph F. Eick Introduction Data Management Lectures in COSC 6340  I: Basic Database Management Concepts --- Review of basic database concepts, techniques, and languages (9 classes, Chapters 1-5, 8-11, and 16 of the textbook).  III: Introduction to KDD and Data Warehousing centering on data warehouses, OLAP, and data mining; moreover, more detailed coverage of querying and mining data streams and database clustering (5 classes; Chapters 1, 2, 6, and 7 of the Han/Kamber book & chapter 25 of our textbook and additional material)  III: Relational Database Design (2 classes, chapters 19)  IV: Implementation of Relational Operators, Query Optimization, and Physical Database Design (Chapters 12+14+20, 3-4 classes)  V: Internet Databases and XML (1 class, chapter 27 of the textbook)  VI: Other: discussion of home works and exams, student presentations; discussion of course projects (3 classes)

4. Christoph F. Eick Introduction Data Management Tentative Schedule COSC 6340  Jan. 18: Introduction to COSC 6340  Fast Review of Undergraduate Material (Jan. 20-Feb. 15)  Jan. 20: Entity-Relationship Data Model  more detailed than textbook  Jan. 25: Entity-Relationship Data Model  Jan. 27: Relational Data Model  Feb. 1: Mapping E/R Diagrams to Relations  Feb. 8/10/15: Index & storage structures, B+-trees, and hashing, PDBD  Feb. 15/17: Relational Algebra  Feb. 22: Writing SQL Queries (somewhat short)  Feb. 24: Leftovers / Review  March 1: Exam0 (Undergraduate Review Exam)

5. Christoph F. Eick Introduction Data Management Tentative Schedule COSC 6340 Part2  II: KDD and Data Warehousing (approx. 5.5 classes)  March 3: Introduction to KDD  March 8: Similarity Assessment  March 10: Clustering  March 22: Association Rule Mining  March 29: Spatial Databases  March 31: Data Warehouses and OLAP  April 8 (30 minutes): Spatial Data Mining  April 5+7+[8]: III: Relational Database Design (2.5 classes)  April 14: Midterm Exam (30 minutes review on April 12, 2005)  April 19+26+[28]: Student Presentations  IV: Physical Database Design and Query Optimization (3 classes)  April 8(makeup): Implementation of Relational Operators  April 8(makeup)/12: Introduction to Query Optimization  April 12/19: Physical Database Design II  V: Internet Databases (1 class)  April 21: Introduction to XML and Semi-Structured Data  April 28: Course Summary + Teaching Evaluation + Leftovers

6. Christoph F. Eick Introduction Data Management Exams and Homeworks COSC 6340  Tu., March 1: Undergraduate Material Review Exam  Th., April 14: Midterm Exam  3 graded homeworks: deadlines: Feb. 17, April 11, April 28  Ungraded Homeworks  Final Exam: Tu/TH., May 10, 11a-1:30p  Qualifying Exam Part2: Fr., May 13, 10-11:30a

7. Christoph F. Eick Introduction Data Management Why are integrated databases popular?  Avoidance of uncontrolled redundancy  Making knowledge accessible that would otherwise not be accessible  Standardization --- uniform representation of data facilitating import and export  Reduction of software development (though the availability of data management systems) Integrated Database Bookkeeping Device Car Salesman

8. Christoph F. Eick Introduction Data Management Popular Topics in Databases  Efficient algorithms for data collections that reside on disks (or which are distributed over multiple disk drives, multiple computers or over the internet).  Study of data models (knowledge representation, mappings, theoretical properties)  Algorithms to run a large number of transactions on a database in parallel; finding efficient implementation for queries that access large databases; database backup and recovery,…  Database design  How to use database management systems as an application programmer / end user.  How to use database management systems as database administrator  How to implement database management systems  Data summarization, knowledge discovery, and data mining  Special purpose databases (genomic, geographical, internet,…)

9. Christoph F. Eick Introduction Data Management Data Model Schema (defines a set of database states) Current Database State is used to define

10. Christoph F. Eick Introduction Data Management Schema for the Library Example using the E/R Data Model Many-to-Many1-to-11-to ManyMany-to-1 title author B# when phone name ssn Check_out Person Book (0,35)(0,1)

11. Christoph F. Eick Introduction Data Management Relational Schema for Library Example in SQL/92 CREATE TABLE Book (B# INTEGER, title CHAR(30), author CHAR(20), PRIMARY KEY (B#)); CREATE TABLE Person (ssn CHAR(9), name CHAR(30), phone INTEGER, PRIMARY KEY (ssn)); CREATE TABLE Checkout( book INTEGER, person CHAR(9), since DATE, PRIMARY KEY (book), FOREIGN KEY (book) REFERENCES Book, FOREIGN KEY (person) REFERENCES Person));

12. Christoph F. Eick Introduction Data Management Referential Integrity in SQL/92  SQL/92 supports all 4 options on deletes and updates.  Default is NO ACTION (delete/update is rejected)  CASCADE (also delete all tuples that refer to deleted tuple)  SET NULL / SET DEFAULT (sets foreign key value of referencing tuple) CREATE TABLE Enrolled (sid CHAR (20), cid CHAR(20), grade CHAR (2), PRIMARY KEY (sid,cid), FOREIGN KEY (sid) REFERENCES Students ON DELETE CASCADE ON UPDATE SET DEFAULT )

13. Christoph F. Eick Introduction Data Management Example of an Internal Schema for the Library Example INTERNAL Schema Library12 references Library. Book is stored sequentially, index on B# using hashing, index on Author using hashing. Person is stored using hashing on ssn. Check_out is stored sequentially, index on since using B+-tree.

14. Christoph F. Eick Introduction Data Management Example: Stored Database Relation Book (11, Y,W) (30, Z, B) (20, Y,W) (51, C, B) (1, C,W) 1 11 51 Index on B# Block#= B# mod 10 0 1 20 30 (101,…) Relation Person Block#= sss mod 10 0 1 (200,…) (500,…) W, … Index on Author Relation Checkout Index on since

15. Modern Relational DBMS Modern DBMS Modern DBMS Support for Web-Interfaces, XML, and Data Exchange Efficient Implementation of Queries (Query Optimization, Join & Selection & Indexing techniques) Transaction Concepts; capability of running many transactions in parallel; support for backup and recovery. Support for special Data-types: long fields, images, html-links, DNA-sequences, spatial information,… Support for higher level user interfaces: graphical, natural language, form-based,… Support for OLAP and Data Warehousing Support for Data Mining operations Support for OO; capability to store operations Support for data- driven computing

16. Christoph F. Eick Introduction Data Management Disks and Files  DBMS stores information on (“hard”) disks.  This has major implications for DBMS design!  READ: transfer data from disk to main memory (RAM).  WRITE: transfer data from RAM to disk.  Both are high-cost operations, relative to in-memory operations, so must be planned carefully!

17. Christoph F. Eick Introduction Data Management Remark: All reported disk performance/prize data are as of middle of 2003 Why Not Store Everything in Main Memory?  Costs too much. $100 will buy you either 512MB of RAM or 50GB of disk today --- that is disk storage 100 times cheaper (but it is approx. 10000 times slower).  Main memory is volatile. We want data to be saved between runs. (Obviously!)  Typical storage hierarchy:  Main memory (RAM) for currently used data.  Disk for the main database (secondary storage).  Tapes for archiving older versions of the data (tertiary storage).

18. Components of a Disk Platters v The platters spin (say, 90rps). Spindle v The arm assembly is moved in or out to position a head on a desired track. Tracks under heads make a cylinder (imaginary!). Disk head Arm movement Arm assembly v Only one head reads/writes at any one time. Tracks Sector v Block size is a multiple of sector size (which is fixed).

19. Christoph F. Eick Introduction Data Management Accessing a Disk Page  Time to access (read/write) a disk block:  seek time (moving arms to position disk head on track)  rotational delay (waiting for block to rotate under head)  transfer time (actually moving data to/from disk surface)  Seek time and rotational delay dominate.  Seek time varies from about 1 to 20msec  Rotational delay varies from 0 to 10msec  Transfer rate is about 1msec per 32KB page

20. Christoph F. Eick Introduction Data Management Review: The ACID properties  A  A tomicity: All actions in the Xact happen, or none happen.  C  C onsistency: If each Xact is consistent, and the DB starts consistent, it ends up consistent.  I  I solation: Execution of one Xact is isolated from that of other Xacts.  D  D urability: If a Xact commits, its effects persist.  The Recovery Manager guarantees Atomicity & Durability.

21. Christoph F. Eick Introduction Data Management Example  Consider two transactions (Xacts): T1:BEGIN A=A+100, B=B-100 END T2:BEGIN A=1.06*A, B=1.06*B END v Intuitively, the first transaction is transferring $100 from B’s account to A’s account. The second is crediting both accounts with a 6% interest payment. v There is no guarantee that T1 will execute before T2 or vice-versa, if both are submitted together. However, the net effect must be equivalent to these two transactions running serially in some order.

22. Christoph F. Eick Introduction Data Management Atomicity of Transactions  A transaction might commit after completing all its actions, or it could abort (or be aborted by the DBMS) after executing some actions.  A very important property guaranteed by the DBMS for all transactions is that they are atomic.  DBMS logs all actions so that it can undo the actions of aborted transactions and redo the actions of successful transactions.

23. Christoph F. Eick Introduction Data Management Concurrency in a DBMS  Users submit transactions, and can think of each transaction as executing by itself.  Concurrency is achieved by the DBMS, which interleaves actions (reads/writes of DB objects) of various transactions.  Each transaction must leave the database in a consistent state if the DB is consistent when the transaction begins.  DBMS will enforce some ICs, depending on the ICs declared in CREATE TABLE statements.  Beyond this, the DBMS does not really understand the semantics of the data. (e.g., it does not understand how the interest on a bank account is computed).  Issues: Effect of interleaving transactions, and crashes.

24. Christoph F. Eick Introduction Data Management Example (Contd.)  Consider a possible interleaving (schedule): T1: A=A+100, B=B-100 T2: A=1.06*A, B=1.06*B v This is OK. But what about: T1: A=A+100, B=B-100 T2: A=1.06*A, B=1.06*B v The DBMS’s view of the second schedule: T1: R(A), W(A), R(B), W(B) T2: R(A), W(A), R(B), W(B)

25. Christoph F. Eick Introduction Data Management Summary  Concurrency control and recovery are among the most important functions provided by a DBMS.  Users need not worry about concurrency.  System automatically inserts lock/unlock requests and schedules actions of different transactions in such a way as to ensure that the resulting execution is equivalent to executing the transactions one after the other in some order.  Write-ahead logging (WAL) is used to undo the actions of aborted transactions and to restore the system to a consistent state after a crash.