Course CMSC 424 Database design Instructor Mihai Pop Times TuTh 11 00 12 15 Location CSIC 1121 Office hours Wed 11 12 AVW 3223 and by appointment alternate office 3120F Biomol Sci Bldg TA Sharath Srinivas TA office hours TBA Class website http www cbcb umd edu confcour CMSC424 shtml Textbook Database systems concepts Silberschatz Korth Sudarshan McGraw Hill ISBN 978 0 07 295886 7 Note Lectures trump book 200 000 000 200 000 000 13 000 000 year Both owned by Larry Ellison CEO of Oracle It pays to know databases Workload Exams 2 midterms 1 final Projects 1 group programming project build a database that does something cool TBA Homeworks 4 homeworks throughout the semester some include SQL programming Grading homeworks 10 midterms 25 final 25 project 40 Policies Attendance follow University policy you must claim excused absences in writing written documentation of illness is required from Dr not yourselves if possible inform me prior to the class you will skip Disabilities must inform me during the first 2 weeks of the semester if special accommodations necessary request letter from Office of Disability Support Services General communication is key talk to me about any issues whether covered or not by University policies Academic Honesty http www studenthonorcouncil umd edu code html No cheating on homeworks projects exams No making up data results No copying of other people s code You can work together on homeworks projects but WRITE THE ANSWER BY YOURSELF I pledge on my honor that I have not given or received any unauthorized assistance on this examination Addl Rules NO EXCUSE FOR CHEATING NO LAPTOPS IN CLASS Why go through all this Database administrators are paid well Databases are everywhere i e lots of job opportunities E g Google at the doctor s office payroll systems on Wall Street government e g CIA scientific data Database research offers many exciting opportunities Internet technologies handling huge amounts of data etc Databases in the wild Database assembles US warnings of Saddam threat Reuters 1 23 2008 can search by keywords summarizes statistics assembled from a number of sources manual curation entry Google database of searches google trends database of emails gmail database of publications google scholar privacy issues Bio medical databases doctor s office lab providers hospitals research institutes insurance companies who how when how much information shared Motivation Data Overload Much more is produced every day Wal mart 583 terabytes of sales and inventory data Adds a billion rows every day we know how many 2 4 ounces of tubes of toothpastes sold yesterday and what was sold with them Yes we can do it is there any point to it library of congress 20 TBs Motivation Data Overload Much more is produced every day Neilsen Media Research 20 GB a day total 80 100 TB From where 12000 households or personal meters Extending to iPods and TiVos in recent years Is there a point beyond telling you what great TV shows you are missing Motivation Data Overload Scientific data is literally astronomical on scale Sanger Center 22 TB doubling every 10 months GenBank 252 GB Trace Archive 1 8 billion records 2 TB New technologies btwn 1TB and 100TB day Shameless plug CMSC 423 bioinformatic algorithms databases and tools Fall 2008 Sloan Digital Sky Survey 15 TB Motivation Data Overload Automatically generated data through instrumentation Britain to log vehicle movements through cameras 35 million reads per day Wireless sensor networks are becoming ubiquitous RFID Possible to track every single piece of product throughout its life Gillette boycott Motivation Data Overload How do we do anything with this data Where and how do we store it Disks are doubling every 18 months or so not enough How do we search through it Text search how much time from here to pittsburgh if I start at 2pm Data is there more will be soon live traffic data Motivation Data Overload What if the disks crash Very common especially if we are talking about 1000 s of disks storing a single system Speed Imagine a bank and millions of ATMs How much time does it take you to do a withdrawl The data is not local How do we ensure correctness Can t have money disappearing Harder than you might think DBMS to the Rescue Provide a systematic way to answer most of these questions Aim is to allow easy management of data Store it Update it Query it Massively successful for structured data What do I mean by that Structured vs Unstructured A lot of the data we encounter is structured Some have very simple structures E g Data that can be represented in tabular forms Signficantly easier to deal with We will actually focus on such data for much of the class Customer Account bname acct no balance cname cstreet ccity Downtown Mianus Perry R H A 101 A 215 A 102 A 305 500 700 400 350 Jones Smith Hayes Curry Lindsay Main North Main North Park Harrison Rye Harrison Rye Pittsfield Structured vs Unstructured Some data has a little more complicated structure E g graph structures Map data social networks data the web link structure etc In many cases can convert to tabular forms for storing Slightly harder to deal with Queries require dealing with the graph structure Collaborations Graph Query Find my Erdos Number Structured vs Unstructured Increasing amount of data in a semi structured format XML Self describing tags Complicates a lot of things We will discuss this toward the end Structured vs Unstructured A huge amount of data is unfortunately unstructured Books WWW Amenable to pretty much only text search Information Retreival deals with this topic What about Google Google is actually successful because it uses the structure DBMS to the Rescue Provide a systematic way to answer most of these questions for structured data increasing for semi structured data XML database systems have been coming up Solving the same problems for truly unstructured data remains an open problem Much research in Information Retrieval community think YouTube what does a query for train retrieve DBMS to the Rescue They are everywhere Enterprises Banks airlines universities Internet Searchsystems net lists 35568 public records DBs Amazon Ebay IMDB Blogs social networks Your computer emails especially Out of scope How do we guarantee the data will be there 10 years from now Much harder than you might think Privacy and security Every other day we see some database leaked on the web New kinds of data Scientific biological Image Audio Video Sensor data etc Interesting
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