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CS511 Advanced Database Systems
Fall 2009, Prof. Chang
Department of Computer Science
University of Illinois at Urbana-Champaign
Midterm Examination 1
October 2, 2009
Time Limit: 75 minutes
• Print your name and NetID below. In addition, print your NetID in the upper right
corner of every page.
Name: NetID:
• Including this cover page, this exam booklet contains 8 pages. Check if you have
missing pages.
• The exam is open book and open notes (any and all books/notes). Scientific calculators
of any kinds are allowed. No other electronic devices are permitted. Any form of
cheating on the examination will result in a zero grade.
• Please write your solutions in the spaces provided on the exam. You may use the blank
areas and backs of the exam pages for additional space or scratch work.
• Please make your answers clear and succinct; you will lose credit for verbose, convo-
luted, or confusing answers. Simplicity does count!
• Each problem has different weight. You should look through the entire exam before
getting started, to plan your strategy.
• Problems that are related to homework or study-guide problems (e.g., in terms of
concepts covered) are marked with [HW ].
Problem 1 2 3 Total
Points 60 20 20 100
Score
Grader
Problem 1 (60 points) Misc. Concepts
For each of the following statements, indicate whether it is TRUE or FALSE by circling your choice. You will get 3 point for each correct answer, -1.5 point for each incorrect answer, and 0 point for each answer left blank.
In some questions, we also ask you to explain why. For such questions, you are required to provide an explanation to justify your choice, and there is no penalty (of negative points) for wrong answers.
(1) T rue F alse [HW ] System R experimented with predicate locking, which has the advantage of locking a desired group of tuples without having to lock each tuple individually.
(2) T rue F alse [HW ] In the implementation of System R, B-tree provided an access path that maps a query value to its disk address, which is important for processing declarative querying like SQL.
(3) T rue F alse System R was implemented faithfully according to the vision and design as Codd sketched.
(4) T rue F alse [HW ] The Phase 0 of System R, because it was a single-user environment, did not handle challenging issues such as views and authorization.
(5) T rue F alse [HW ] The cost-based optimizer of System R was able to predict the costs of different query plans accurately and order them correctly according to their costs.
(6) T rue F alse [HW ] It is possible to support object identity efficiently in a relational DBMS ⇒ Explain:
(7) T rue F alse [HW ] The Query Graph Model of Starburst helps in the extensibility of the system. ⇒ Explain:
(8) T rue F alse [HW ] Denormalization is used widely in Starburst to support complex objects.
(9) T rue F alse [HW ] It is possible that a parallel system can have linear speedup but non-linear scale up. ⇒ Explain:
(20) T rue F alse The Version 9 of PostgreSQL was just released in September 2009.
Problem 2 (20 points) Complex Objects [HW ]
In Postgres, composite types are supported by the concept of ’path expression’, i.e., the nested dot notation as we used in OOPL, by which we can access the attributes of an object.
Part 1(4 points) Write an example query with such path expressions. Prepare your example, so that you can use it to answer Parts 2 and 3.
Part 2(8 points) How are path expressions similar to or different from joins in relational DBMS? Give two similarities, and two differences.
Problem 3 (20 points) Data Partitioning for Parallelism [HW ]
We studied three alternative data partition schemes in the Gamma paper.
Part 1(3 points)
Why did Gamma need to consider data partition schemes at all?
Part 2(9 points)
For each scheme, give one example query scenario that the scheme works best. Describe the scenarios clearly, and explain why.
Part 3(8 points)
Since Gamma considered data partition in the context of the relational data model, we wonder how the issues would become for the object-oriented model—that is, how does the OO data model complicates data partition? We ask you to identify two new issues that arise for OODBMS. Explain clearly and concisely.
