CSE 444 - Calendar

CSE 444: Daily Schedule

Note that this schedule will be altered during the quarter. Please make sure to check it every week.

You can find the consolidated list of readings at the end of the page.

Week of	Monday	Tuesday	Wednesday	Thursday	Friday
March 26	Introduction lecture 1		Review of relational model and SQL lecture 2	Intro to SimpleDB and JUnit section 1	DBMS architecture and deployments lecture 3
April 2	Data storage and buffer management lecture 4 Lab1 (part1) due		Indexing lectures 5-6 Webquiz 1 due	Data storage and SQL section 2	Indexing lectures 5-6
April 9	Query execution lecture 7		Operator algorithms lectures 8-9 and example Webquiz 2 due Lab1 due	Indexing section 3	Operator algorithms lectures 8-9 and example
April 16	Query optimization lecture 10 Webquiz 3 due		Query optimization lectures 11-12 Lab2 (part1) due	Operator Algorithms section 4	Query optimization lectures 11-12 and example (see page 8)
April 23	Database tuning lecture 13		Transactions: Concurrency control lecture 14 Lab2 due	Query optimization section 5	Transactions: Concurrency control lecture 15 Webquiz 4 due
April 30	Transactions: Concurrency control lecture 16		Transactions: Recovery lecture 17 Lab4 (part1) due	Transactions section 6 [pptx, txt]	Transactions: Recovery lecture 18
May 7	Transactions: Recovery lecture 19 Webquiz 5 due	Lab4 due	Distributed query processing and optimization lecture 20	Transactions section 7	Distributed transactions lecture 21
May 14	Replication lecture 22		NO LECTURE Webquiz 6 due	Replication and distribution section 8	Parallel DBMSs lectures 23 and 24
May 21	Parallel DBMSs lectures 23 and 24 Lab3 due		NO LECTURE	Parallel processing section 9	MapReduce lectures 25
May 28	Memorial Day		NoSQL lectures 26	Review section 10	Course Wrap-up lectures 27 Lab5 due or Lab6 due
June 4				Final Exam 8:30am-10:20am in class

Readings

Please note that I will refine the list of readings as we go along:

Lecture 2: Review of relational model and SQL

The Relational Model of Data (Chapter 2)
Relational Algebra (Sections 5.1, 5.2, and 5.4)
SQL (Chapter 6 except for Section 6.6)

Lecture 3: DBMS architecture and deployments

Overview of a DBMS (Section 1.2)
SQL in a Server Environment (Sections 9.1 and 9.2)

Lectures 4-6: Data storage and indexing

Views and Indexes in SQL (Chapter 8)
Data storage (Sections 13.5 and following except for 13.6.3 and 13.6.4)
Buffer management (Section 15.7)
Indexes (Sections 14.1 through 14.4)

Lectures 7-9: Query execution and operator algorithms

Query Execution and Operator Algorithms (Chapter 15)

Lectures 10-13: Query optimization and DBMS tuning

Query Optimization (Chapter 16)
Optional: P. Selinger, M. Astrahan, D. Chamberlin, R. Lorie, and T. Price. Access Path Selection in a Relational Database Management System. Proceedings of ACM SIGMOD, 1979. Pages 22-34. Also in the Red Book (3rd ed and 4th ed) [pdf]
- This paper is very hard to read
- But the example on page 30 (i.e., page 8 in the pdf) in the section called: "Example of tree" is readable and corresponds to the example that we went through in class.

Lectures 14-19: Transactions

Transactions in SQL (Section 6.6)
Transactions and concurrency control (Chapters 18 and 19)
Transactions and recovery (Chapter 17 and 19)
Michael J. Franklin. Concurrency Control and Recovery. The Handbook of Computer Science and Engineering, A. Tucker, ed., CRC Press, Boca Raton, 1997. [pdf]

Lectures 20-22: Distribution and Replication

Distributed query processing (Sections 20.3 through 20.6)

Lectures 23-25: Parallel data processing

Definition and basic concepts in parallel databases (Section 20.1)
Map-reduce (Section 20.2); Chapter 2 (Sections 1,2,3 only) of Mining of Massive Datasets, by Rajaraman and Ullman.
MapReduce: Simplified Data Processing on Large Clusters. Jeffrey Dean and Sanjay Ghemawat. OSDI'04: Sixth Symposium on Operating System Design and Implementation.

Lectures 26-27: DBMS-as-a-service + NoSQL

Scalable SQL and NoSQL Data Stores by Rick Cattell, SIGMOD Record, December 2010 (Author keeps revising this survey).
SQL Databases v.s. NoSQL Databases by Mike Stonebraker, CACM Blog.
Bigtable: A Distributed Storage System for Structured Data. ByFay Chang, Jeffrey Dean, Sanjay Ghemawat, Wilson C. Hsieh, Deborah A. Wallach, Mike Burrows, Tushar Chandra, Andrew Fikes, and Robert E. Gruber. OSDI 2006.
VoltDB: http://voltdb.com/
Browse the documentation for various DBMS-as-a-service systems (this is not an exhaustive list):
- Amazon Relational Database Service (Amazon RDS) (part of Amazon Web services).
- Amazon SimpleDB (part of the Amazon Web services).
- Google App Engine Datastore (part of the Google App Engine).
- Microsoft SQL Azure (part of Windows Azure).