CMSC424: Review

1. CMSC424: Review

2. Database Management Systems Manage data • Store data • Update data • Answerquestions about the data

3. What kind of data ? • Enterprise data • Banking • Supermarkets, Sales • Airlines • Universities • Manufacturing • Human resources • More recent: • Semi-structured Data (XML) • Scientific data • Biological data • Sensor network data etc etc…

4. Naïve solutions • Don’t offer: • Consistency • Atomicity, durability etc • Concurrency • Declarative data retrieval • Control of redundancy • Dynamic data evolution

5. DBMS • Database Management Systems provide • Data abstraction • Key in evolving systems • Probably the most important purpose of a DBMS • Goal: Hiding low-level details from the users of the system • Guarantees about data integrity • In presence of concurrent access, failures… • Speed !!

6. View Level … View 1 View 2 View n Data Abstraction What data users and application programs see ? Logical Level What data is stored ? describe data properties such as data semantics, data relationships Physical Level How data is actually stored ? e.g. are we using disks ? Which file system ?

7. DBMS at a Glance • Data Modeling • Data Retrieval • Data Storage • Data Integrity

8. Data Modeling • A data model is a collection of concepts for describing data properties and domain knowledge: • Data relationships • Data semantics • Data constraints • We discussed two models: • Entity-relationship Model • Diagrammatic representation • Easier to work with • Syntax not important, but remember the “meaning” • Remember what you can model • Relational Model • Only one abstract concept • Closer to the physical representation on disk • Normalization

9. Data Retrieval • Query = Declarative data retrieval program • describes what data to acquire, not how to acquire it • Non-declarative: • scan the accounts file • look for number 55 in the 2nd field • subtract $50 from the 3rd field • Declarative (posed against the tables abstraction): update accounts set balance = balance - 50 where acct_no = 55 • Why ? • Easier to write • More efficient to execute • Database system can decide how to execute it

10. Data Storage • Where and how to store data ? • Main memory ? • What if the database larger than memory size ? • Disks • We discussed properties of disks • RAID • How to move data between memory and disk ? • Buffer Management • LRU, MRU, Clock • Indexes • Closely tied to data retrieval • B+-trees, Hashing

11. Data Integrity Manage concurrency and crashes • Transaction: A sequence of database actions enclosed within special tags • Properties: • Atomicity: Entire transaction or nothing • Consistency: Transaction, executed completely, take database from one consistent state to another • Isolation: Concurrent transactions appear to run in isolation • Durability: Effects of committed transactions are not lost • Consistency: Transaction programmer needs to guarantee that • DBMS can do a few things, e.g., enforce constraints on the data • Rest: DBMS guarantees • Haven’t covered in class yet

12. Data Integrity • Semantic constraints • Typically specified at the logical level • E.g. balance > 0 • Assert statements • Functional dependencies • kinda

13. DBMS at a glance • Data Models • Conceptual representation of the data • Data Retrieval • How to ask questions of the database • How to answer those questions • Data Storage • How/where to store data, how to access it • Data Integrity • Manage crashes, concurrency • Manage semantic inconsistencies • Not fully disjoint categorization !!

14. SQL Assignment Report the home run champs in the last three years (2002 to 2004). select h.year, firstname, lastname, h.hrs from playerinfo p, hitting h where p.playerid = h.playerid and h.hrs = ( select max(hrs) from hitting h2 where h.year = h2.year);

15. SQL Assignment Report the last name of the batter who would be reported first in alphabetical order. select firstname, lastname from playerinfo where firstname <= all (select firstname from playerinfo) and lastname <= all ( select lastname from playerinfo p2 where p2.firstname = playerinfo.firstname);

16. SQL Assignment 20 Create the dream NL batting team (that will have the most total RBI) from 2004 statistics. Remember, a NL team consists of 1 LF, 1CF, 1RF, 1 SS, 1 2B, 1 3B, 1 1B, 1 Catcher, and 1 Pitcher. Only consider the position at which the hitter played the maximum number of games; so a player will only qualify at one fielding position. Break Ties arbitrarily.

17. create table rbistable as select p.firstname, p.lastname, p.playerid, h.rbis, f.pos from playerinfo p, hitting h, fielding f where p.playerid = h.playerid and f.playerid = h.playerid and f.year = 2004 and h.year = 2004 and f.numgames = (select max(f2.numgames) from fielding f2 where f2.playerid = f.playerid and f2.year = f.year); create table rbistable2 as select firstname, lastname, pos, rbis, playerid from rbistable r1 where r1.rbis = (select max(r2.rbis) from rbistable r2 where r2.pos = r1.pos); select firstname, lastname, pos, rbis from rbistable2 r where playerid <= all (select playerid from rbistable2 r2 where r2.pos = r.pos);

18. 22 Rank the 2004 teams by their number of wins. The output should contains a table with two columns: Team Name, and Rank (between 1 and 30), and it should be sorted by Rank. Two teams with same number of wins will be ranked the same, and the next rank will be skipped in that case. select t1.teamname, t1.wins, 31 - count(t2.teamname) as rank from teams t1, teams t2 where t1.year = 2004 and t1.year = t2.year and t1.losses <= t2.losses group by t1.teamname, t1.wins order by rank;