Advanced Database Management System - Tutorials and Notes: Advanced Databases Pune University BE(IT) 2013 Question

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Sunday, 17 August 2014

Advanced Databases Pune University BE(IT) 2013 Question

Pune University BE(IT) 2013 Question Papers / Previous year BE(Information Technology) question papers of Pune University / BE IT Advanced Databases Question Paper / Pune University Questions with Answers - Regulation 2008

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UNIVERSITY OF PUNE
[4364]-794
B. E. (IT) Examination - 2013
ADVANCED DATABASE MANAGEMENT
(JUNE 2008 Course)
[Time : 3 Hours]                                                                [Max. Marks : 100]
[Total No. of Questions : 12]                                     [Total No. of Printed Pages :3]
Instructions :
(1) Answers to the section should be written in separate books
(2) Neat diagrams must be drawn wherever necessary.
(3) Assume suitable data, if necessary.
(4) Section I :Q1or Q2, Q3 or Q4, Q5 or Q6
(5) Section II: Q7 or Q8, Q9 or Q10, Q11 or Q12

SECTION-I
Q1. a) Explain parallel query evaluation using data partitioning technique (06)
Q1. c) Describe the benefits and drawbacks of Partitioned parallelism. (05)
OR
Q2. a) Explain parallelizing individual operations using bulk loading and scanning, sorting. (06)
Q2.b) Explain parallel evaluation of a relational query in a DBMS with shared nothing architecture. (06)
Q2.c) Write a short Note of parallel Query optimization (05)

Q3. a) Explain 2PC and 3PC commit protocols (06)
Q3. b) Explain distributed catalog management in distributed databases. (06)
Q3. c) Write a short note on LDAP (05)
OR
Q4. a) Explain any two availability approaches in distribute databases (06)
Q4. b) Suppose that the employee relation is stored in Madison and the tuples with salary < 100000 are replicated at New York. Consider the following three options for lock management : all locks managed at a single site, say ABC; primary copy with Madison being the primary for employees; and fully distributed. For each of the lock management options, explain what locks are set for all following queries. Also state from which site the page is read
i. A query at Austin wants to read a page of employees tuples with salary <= 50000
ii. A query at Madison wants to read a page of employees tuples with salary <= 50000
iii. A query at New York wants to read a page of employees tuples with salary <= 50000 (06)
Q4. c) Write a short Note on Query Transformation (05)

Q5. a) Consider the following nested relational schema (10)
Emp= (ename, childrenset setoff(children), skillset setoff(skills)
Children = (name, birthday), Birthday= (day, month, year)
Skills = (type, Examset setoff(Exams)), Exams = (year, city)
Answer the following
i. Write DTD and XML file
ii. Write a query in XPath to list all skill types in Emp.
iii. Find the name of all the employees who have a child who has a birthday in March.
iv. Find the those employee who took an examination for the skill Type “typing” in the city “Pune”
v. List all skill types in Emp.
Q5. b) Compare and contrast the two-tier and three-tier architecture for Web-DBMS. Describe design issues for a web- DBMS based E-learning application which includes text, audio and video data. (06)
OR
Q6. a) Describe the various issues for efficient evaluation of XML Queries (06)
Q6. b) Write a short Note on (10)
1. XML facets
2. Web services and SOAP

SECTION II
Q7. a) Design basic conceptual schemas of conceptual modeling of data warehouse for Inventory application. (06)
Q7. b) Explain Load manager in data warehouse. (06)
Q7. c) Explain guidelines for designing fact tables (05)
OR
Q8. a) Explain Indexing techniques in data warehouse (06)
Q8. b) Explain Kimball’s nine steps design methodology (06)
Q8. c) Write a short notes on OLAP (05)

Q9. a) Describe Incremental mining algorithm for computing Frequent Itemsets with suitable example. (06)
Q9. b) Explain the splitting criteria and pruning process for decision tree construction with suitable example (06)
Q9. c) Write a short Note on Web Mining (05)
OR
Q10.a) Explain different types of clustering in data mining with suitable example (06)
Q10.b) Design a classification model using Naïve Bayesian classifier with suitable example (06)
Q10.c) Write a short note on Text Mining (05)

Q11. a) Explain the following terms in Information Retrieval with suitable example
i) Synonyms ii) Homonyms iii) Proximity iv) TF-IDF (06)
Q11. b) Write short notes on
i) Bit-sliced Signature File
ii) Precision and Recall  (10)
Q12. a) Define Information Retrieval System. Describe Web search engine architecture (06)
Q12. b) Write short notes on iii) Document Ranking iv) Link based searching approach (10)
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