INSTITUTE OF AERONAUTICAL ENGINEERING (Autonomous) Dundigal, Hyderabad

Similar documents
INSTITUTE OF AERONAUTICAL ENGINEERING (AUTONOMOUS)

INSTITUTE OF AERONAUTICAL ENGINEERING

INSTITUTE OF AERONAUTICAL ENGINEERING

INSTITUTE OF AERONAUTICAL ENGINEERING (Autonomous) Dundigal, Hyderabad

INSTITUTE OF AERONAUTICAL ENGINEERING (Autonomous) Dundigal, Hyderabad

INSTITUTE OF AERONAUTICAL ENGINEERING (Autonomous) Dundigal, Hyderabad

INSTITUTE OF AERONAUTICAL ENGINEERING (Autonomous) Dundigal, Hyderabad

INSTITUTE OF AERONAUTICAL ENGINEERING (Autonomous) Dundigal, Hyderabad

INSTITUTE OF AERONAUTICAL ENGINEERING (Autonomous) Dundigal, Hyderabad

INSTITUTE OF AERONAUTICAL ENGINEERING (Autonomous) Dundigal, Hyderabad

ST.MARTIN'S ENGINEERING COLLEGE Dhulapally,Secunderabad-014

INSTITUTE OF AERONAUTICAL ENGINEERING

INSTITUTE OF AERONAUTICAL ENGINEERING Dundigal, Hyderabad COMPUTER SCIENCE AND ENGINEERING QUESTION BANK OPERATING SYSTEMS

INSTITUTE OF AERONAUTICAL ENGINEERING (Autonomous) Dundigal, Hyderabad

MLR INSTITUTE OF TECHNOLOGY DUNDIGAL , HYDERABAD QUESTION BANK

INSTITUTE OF AERONAUTICAL ENGINEERING (Autonomous) Dundigal, Hyderabad

Distributed DBMS. Concepts. Concepts. Distributed DBMS. Concepts. Concepts 9/8/2014

TUTORIAL QUESTION BANK

St. MARTIN S ENGINEERING COLLEGE Dhulapally,Secunderabad DEPARTMENT OF INFORMATION TECHNOLOGY Academic year

FACULTY OF ENGINEERING B.E. 4/4 (CSE) II Semester (Old) Examination, June Subject : Information Retrieval Systems (Elective III) Estelar

B.C.A DATA BASE MANAGEMENT SYSTEM MODULE SPECIFICATION SHEET. Course Outline

INSTITUTE OF AERONAUTICAL ENGINEERING

Semi-Structured Data Management (CSE 511)

GUJARAT TECHNOLOGICAL UNIVERSITY

VALLIAMMAI ENGINEERING COLLEGE

Data Processing at Scale (CSE 511)

Mobile and Heterogeneous databases Distributed Database System Query Processing. A.R. Hurson Computer Science Missouri Science & Technology

Data about data is database Select correct option: True False Partially True None of the Above

Schema And Draw The Dependency Diagram

Note: Select one full question from each unit

Specific Objectives Contents Teaching Hours 4 the basic concepts 1.1 Concepts of Relational Databases

Questions about the contents of the final section of the course of Advanced Databases. Version 0.3 of 28/05/2018.

INSTITUTE OF AERONAUTICAL ENGINEERING

Northern India Engineering College, New Delhi Question Bank Database Management System. B. Tech. Mechanical & Automation Engineering V Semester

INSTITUTE OF AERONAUTICAL ENGINEERING

INSTITUTE OF AERONAUTICAL ENGINEERING Autonomous Dundigal, Hyderabad

INSTITUTE OF AERONAUTICAL ENGINEERING (Autonomous) Dundigal, Hyderabad

COURSE OUTCOMES OF M.Sc(IT)

Database Architectures

CS317 File and Database Systems

Babu Banarasi Das National Institute of Technology and Management

INSTITUTE OF AERONAUTICAL ENGINEERING (Autonomous) Dundigal, Hyderabad

Mahathma Gandhi University

DATABASE DEVELOPMENT (H4)

Outline. q Database integration & querying. q Peer-to-Peer data management q Stream data management q MapReduce-based distributed data management

SYED AMMAL ENGINEERING COLLEGE

Relational Database Management Systems Mar/Apr I. Section-A: 5 X 4 =20 Marks

Part A (Compulsory) (Marks : 10) Answer all ten questions (20 words each). Each question carries equal marks.

Assignment Session : July-March

MLR INSTITUTE OF TECHNOLOGY DUNDIGAL , HYDERABAD

Database Architectures

COMP Instructor: Dimitris Papadias WWW page:

Chapter (4) Enhanced Entity-Relationship and Object Modeling

Department of Computer Science and Engineering (CSE) Course Outline

Query optimization. Elena Baralis, Silvia Chiusano Politecnico di Torino. DBMS Architecture D B M G. Database Management Systems. Pag.

Basant Group of Institution

Module 2 : Entity-Relationship Model 15

CS 411a/433a/538a Databases II Midterm, Oct. 18, Minutes. Answer all questions on the exam page. No aids; no electronic devices.

MaanavaN.Com DEPARTMENT OF COMPUTER SCIENCE & ENGINEERING QUESTION BANK

Example Examination. Allocated Time: 100 minutes Maximum Points: 250

INSTITUTE OF AERONAUTICAL ENGINEERING (Autonomous) Dundigal, Hyderabad

Introduction to Data Management. Lecture #2 (Big Picture, Cont.) Instructor: Chen Li

. : B.Sc. (H) Computer Science. Section A is compulsory. Attempt all parts together. Section A. Specialization lattice and Specialization hierarchy

Datenbanksysteme II: Caching and File Structures. Ulf Leser

Fundamental of I.T. (c) Application of computer *************

Copyright 2007 Ramez Elmasri and Shamkant B. Navathe Slide 25-1

Sample Question Paper

CSIT5300: Advanced Database Systems

Database Ph.D. Qualifying Exam Spring 2006

What happens. 376a. Database Design. Execution strategy. Query conversion. Next. Two types of techniques

INSTITUTE OF AERONAUTICAL ENGINEERING

Fundamentals of Database Systems V7. Course Outline. Fundamentals of Database Systems V Jul 2018

SRM UNIVERSITY FACULTY OF ENGINEERING AND TECHNOLOGY SCHOOL OF COMPUTING DEPARTMENT OF CSE COURSE PLAN

Chapter 18: Parallel Databases

VIEW OTHER QUESTION PAPERS

Wentworth Institute of Technology COMP570 Database Applications Fall 2014 Derbinsky. Physical Tuning. Lecture 10. Physical Tuning

Chapter 3. Database Architecture and the Web

List of Practical for Master in Computer Application (5 Year Integrated) (Through Distance Education)

Relational Algebra Part I. CS 377: Database Systems

COSC 304 Introduction to Database Systems. Views and Security. Dr. Ramon Lawrence University of British Columbia Okanagan

Database Administration. Database Administration CSCU9Q5. The Data Dictionary. 31Q5/IT31 Database P&A November 7, Overview:

KRISHNA KANTA HANDIQUI STATE OPEN UNIVERSITY Hiranya Kumar Bhuyan School of Science and Technology

MIDTERM EXAMINATION Spring 2010 CS403- Database Management Systems (Session - 4) Ref No: Time: 60 min Marks: 38

INSTITUTE OF AERONAUTICAL ENGINEERING

SIR C.R.REDDY COLLEGE OF ENGINEERING, ELURU DEPARTMENT OF INFORMATION TECHNOLOGY LESSON PLAN

COWLEY COLLEGE & Area Vocational Technical School

Name :. Roll No. :... Invigilator s Signature : DATABASE MANAGEMENT SYSTEM

Distributed Databases Systems

Information Management (IM)

SYLLABUS CIST0252. Departmental Syllabus. Departmental Syllabus. Departmental Syllabus. Departmental Syllabus. CIST-0226 SQL Server

Parallel DBMS. Parallel Database Systems. PDBS vs Distributed DBS. Types of Parallelism. Goals and Metrics Speedup. Types of Parallelism

Course Outline Faculty of Computing and Information Technology

UNIT 3 DATABASE DESIGN

2011 DATABASE MANAGEMENT SYSTEM

Post-Graduate Diploma in Computer Application Examination,2008 ELECTRONIC DATA PROCESSING

3. Object-Oriented Databases

Total No. of Questions :09] [Total No. of Pages : 02. II/IV B.Tech. DEGREE EXAMINATIONS, NOV/DEC Second Semester CSE/IT DBMS

Introduction to Query Processing and Query Optimization Techniques. Copyright 2011 Ramez Elmasri and Shamkant Navathe

COSC Dr. Ramon Lawrence. Emp Relation

P.G.D.C.M. (Semester I) Examination, : ELEMENTS OF INFORMATION TECHNOLOGY AND OFFICE AUTOMATION (2008 Pattern)

Transcription:

Name Code Class Branch INSTITUTE OF AERONAUTICAL ENGINEERING (Autonomous) Dundigal, Hyderabad - 500 043 COMPUTER SCIENCE AND ENGINEERING QUESTION BANK Advanced Data Base Management System BCS005 I M. Tech II Sem Year 2017 2018 Team of Instructors Computer Science Engineering Mr. C Raghavendra, Assistant Professor, CSE. OBJECTIVES To meet the challenge of ensuring excellence in engineering education, the issue of quality needs to be addressed, debated and taken forward in a systematic manner. Accreditation is the principal means of quality assurance in higher education. The major emphasis of accreditation process is to measure the outcomes of the program that is being accredited. In line with this, faculty of Institute of Aeronautical Engineering, Hyderabad has taken a lead in incorporating philosophy of outcome based education in the process of problem solving and career development. So, all students of the institute should understand the depth and approach of course to be taught through this question bank, which will enhance learner s learning process. S. No QUESTIONS taxonomy level outcome UNIT I INTRODUCTION 1. List the advantages of DBMS? Knowledge 1 2. List the database Applications? Knowledge 2 3. Define (i) Database (ii) DBMS Knowledge 2 4. Give a brief note on Database storage structure? Understand 2 5. Discuss about wild card operators. Understand 2 6. What is the Query Processor? Understand 2 7. Define the terms i) Entity ii) Entity set Knowledge 1 8. Define weak and strong entity sets? Knowledge 2 9. Write about stored and derived attributes? Understand 2 10. Discuss how can you change the data in the table? Understand 1 11. List various types of Integrity Constraints? Knowledge 2 12. Discuss How can you alter and destroy tables? Understand 1 13. Define database Languages? Understand 2 14. List the disadvantages of file processing system? Knowledge 2 15. Give the levels of data abstraction? Understand 2 16. Define instance and schema? Knowledge 1 1 P a g e

PART B (LONG ANSWER QUESTIONS) UNIT I INTRODUCTION 1. Discuss additional features of the ER-Models. Understand 1 2. Explain the Concept Design with the ER Model? Understand 1 3. Write about views and updates on views? Knowledge 2 4. Explain Integrity constraint over relations? Understand 1 5. List and explain DDL commands with examples? Understand 2 6. Discuss about the logical database Design? Understand 2 7. Distinguish strong entity set with weak entity set? Draw an ER diagram to Apply 2 illustrate weak entity set? 8. Explain Group by and Order by queries with suitable example. Understand 1 9. Describe Inheritance. Illustrate with example? Apply 2 10. Describe various operations on structured data? Understand 1 UNIT I INTRODUCTION 1. Let E1 and E2 be two entities in an E/R diagram with simple single-valued attributes. R1 and R2 are two relationships between E1 and E2, where R1 is one- to-many and R2 is many-to-many. R1 and R2 do not have any attributes of their own. Calculate the minimum number of tables required to represent this situation in the relational model? 2. Analyze and find whether View exists if the table is dropped from the database? 3. We can convert any weak entity set to strong entity set by simply adding appropriate attributes. Analyze why, then, do we have weak entity sets? Apply 2 Analyze 2 Analyze 1 UNIT II ORDBMS 1. Define Parallel database System? Knowledge 3 2. What is distributed database System? Knowledge 3 3. What are the Issues that motivate Data distribution? Knowledge 3 4. Define Parallel Query Optimization? Knowledge 3 5. What is Relational Query Execution Plan? Knowledge 3 6. How Data Partitioned in Parallel Evaluation? Knowledge 3 7. Describe Data Partitioning? Understand 3 8. Give a brief note on architectures to build parallel DBMS? Understand 3 9. Define the terms Speed up, Scale up? Understand 3 10. What is pipelined Parallelism? Understand 3 2 P a g e

PART B (LONG ANSWER QUESTIONS) UNIT II ORDBMS 1. Explain Parallel Evaluation of Relational Query in DBMS? Understand 3 2. Explain Round-Robin Partitioning? Understand 3 3. Explain Bulk Loading and Scanning? Understand 3 4. Differentiate between RDBMS and ORDBMS? Knowledge 3 5. What are the storage distinctions between reference and non-reference Knowledge 3 types? 6. Explain implementation challenges of ORDBMS? Understand 3 7. Define Query Optimization? Knowledge 7 8. Explain Object Data Language and Object Query Language? Understand 3 9. Differentiate between ORDBMS and OODBMS? Knowledge 3 10. Discuss how a DBMS exploits encapsulation in implementing support for ADT Knowledge 3 UNIT II ORDBMS 1. You are given a two-dimensional, n x n array of objects. Assume that you can fit 100 objects on a disk page. Describe a way to layout (Chunk) the array into pages so that retrievals of square m x m sub regions of the array are efficient. 2. For the relations Emp(name, fname, address, dno) Dept(deptno, dname, address) And the query P fname, ename, address (s dname= Research AND d,deptno=e. dno(emp_dept)) (i) Draw the initial query tree. (ii) Optimize the query write(x) operation and X resides on the 1 page. 3. Describe data partitioning and parallelizing sequential operator evaluation code with relevant examples. State parallel databases and design the architecture of parallel databases. 4. Explain how to run parallel databases for big data? Apply 3 Apply 3 Analyze 3 Analyze 3 3 P a g e UNIT III DISTRIBUTED DATABASES 1. Define Distributed Database? Knowledge 4 2. List Out features of Distributed Database? Knowledge 5 3. List Out software components which are required for building a Distributed Database? Knowledge 5 4. Define Global Schema and Fragmentation Schema? Knowledge 4 5. What are types of Data Fragmentation? Understand 5 6. Define Replication Transparency? Understand 4

7. Define fragmentation Understand 4 8. List Out the rules for defining fragments? Knowledge 5 9. Define Mixed Fragmentation? Knowledge 4 10. What is Location Transparency? Understand 4 PART B (LONG ANSWER QUESTIONS) UNIT III DISTRIBUTED DATABASES 1. Explain Distributed Database on geographically dispersed network? Knowledge 4 2. Differentiate between Distributed Database and Centralized Database? Knowledge 5 3. Explain features of Distributed Database? Knowledge 4 4. Why Distributed Databases? Explain? Knowledge 5 5. Explain Distributed Database Management Systems? Understand 4 6. Explain services supported by DDBMS? Understand 4 7. Explain Architecture for Distributed Databases? Understand 5 8. Explain Different Types of Data Fragmentation? Understand 4 9. Explain Objectives which motivate architecture of Distributed Database? Knowledge 5 10. Explain Different levels of Distribution Transparency? Understand 4 UNIT III DISTRIBUTED DATABASES 1. Explain heterogeneous distributed database without transparency with an example? 2. Explain distribution transparency for update applications with example? Analyze 4 Analyze 5 3. Consider the global relations: Apply 4 PATIENT (NUMBER,NAME,SSN,AMOUNT DUE,SEPT,DOCTOR,MED-TRETMENT) DEPARTMENT(DEPT,LOCATION,DIRECTOR) STAFF(STAFF NUM,DIRECTOR,TASK) Define their fragmentation as follows: a) DEPARTMNET has a horizontal fragmentation by LOCATION, with two locations ;each department is conducted by one DIRECTOR b) There are several staff members for each department led by department director. STAFF has horizontal fragmentation derived from that of DEPARTMENT and a semi join on the DIRECTOR attribute.which assumption is required in order to assure completeness? 4. Explain Integrity Constraints in Distributed Database? Apply 5 4 P a g e UNIT IV DISTRIBUTED DATABASE DESIGN 1. List out the Objectives of Design of Data Distribution? Knowledge 6

2. What are the approaches for designing Data Distribution? Understand 6 3. List out requirements to design a Distributed Database? Knowledge 6 4. Define Distributed Join? Understand 6 5. Define Vertical Fragmentation? Understand 6 6. What is Equivalence Transformation for Queries? Understand 6 7. What is Distributed Grouping? Knowledge 6 8. What is Aggregate Function Evaluation? Knowledge 6 9. Define Canonical Expression? Understand 6 10. What are the Properties of Group By Operation? Knowledge 6 PART B (LONG ANSWER QUESTIONS) UNIT IV DISTRIBUTED DATABASE DESIGN 1. Explain Objectives of the Design of Data Distribution? Understand 6 2. Explain Top Down and Bottom Up Approaches for Designing of Data Understand 6 Distribution? 3. Explain how to design Database fragmentation? Apply 6 4. Explain general criteria for fragment allocation? Understand 6 5. What are the measures of costs and benefits of fragment allocation? Understand 6 6. Explain operator tree of a query with an example? Understand 6 7. Explain how to transform global queries into fragment queries? Understand 6 8. Explain the rules to define relational algebra to Qualified Relations? Understand 6 9. Explain simplification of joins between horizontally fragmented relations? Understand 6 10. Explain Read only application SUPINQUIRT at different levels of distribution transparency? Understand 6 UNIT IV DISTRIBUTED DATABASE DESIGN 1. Give an example of bank application, accessing a database which is distributed over the branches of the bank, in which the relevant predicates for data distribution or not in the text of the application program. 2. Give an example of global schema, fragmentation schema and additional semantic knowledge such that all this information can be used for deducing the simplification of a query? 3. Consider the following two allocations of fragments 1:R1 at site 1;R2 at site 2 ;R3 at site 3 2:R1 and R2 at site1;r2 and R3 at site 3 With the following applications(all with the same frequency of activation): A1,issued at site 1,reads 5 records of R1 and 5 records of R2 A2,issued at site 3,reads 5 records of R3 and 5 records of R2 A3 issued at site 2,reads 10 records of R2 (a).if we take locality of reference as objective which solution is best? (b).if we take complete locality of applications as objective, which solution is the best? (c).assume now that A3 updates 10 records of R2.Taking the locality of reference as objective, which solution is the best? 4. Determine the common sub expression the following global queries. Do step by step transformations indicating which rule is applied at each step. Apply criteria 1 and 2 to simplify the global queries. a)pj NAME, TAX ((EMP JN DEPTNUM = DEPTNUM SL AREA = NORTH DEPT) 5 P a g e Analyze 6 Apply 6 Apply 6 Apply 6

DF(EMP JN DEPTNUM = DEPTNUM SL DEPTNUM<10 DEPT)) b)(sl DEPTNUM= 10DEPT NJN(SL PNUM= P1 SUPPLY DF SL PNUM= P2 SUPPLY)) UN( SL DEPTNUM= 10 DEPTNJNSL PNUM= P1 SUPPLY) UNIT V QUERY OPTIMIZATION 1. Define Information Retrieval Understand 7 2. List out problems in Query Optimization? Understand 7 3. What is Vector Space Model? Knowledge 8 4. Difference between ranked query and Boolean query Understand 7 5. What is Length Normalization? Knowledge 8 6. Define Inverted Index? Understand 8 7. Define query Optimization? Understand 7 8. Define Join Queries? Understand 8 9. What is a Signature File? Knowledge 7 10. List out issues for evaluating queries efficiency? Knowledge 8 PART B (LONG ANSWER QUESTIONS) UNIT V QUERY OPTIMIZATION 1. Explain problems in Query Optimization? Understand 7 2. Objectives in Query Processing Optimization? Knowledge 8 3. Explain the importance of query optimization in Distributed Database? Understand 8 4. Explain uses of semi join programs for join queries Understand 7 5. Difference between Database Management Systems and Knowledge 8 Information Retrieval Systems? 6. Explain Term Frequency and Inverse Document Frequency? Understand 7 7. Explain the criteria to evaluate IRS? Understand 8 8. Explain Two indexing Techniques that support evaluation of Boolean and Understand 7 Ranked queries? 9. What is Path Expressions? Knowledge 8 10. Explain FLWR expressions? How can we order output of query? Understand 7 UNIT V QUERY OPTIMIZATION 1. Explain the effects of commuting Joins and Unions? Analyze 7 2. Construct a reducer for R using using semi-join programs having the join Apply 8 graph in the figure: With R={(0,1),(3,4),(6,7),(7,1)} S={(1,2),(4,5),(6,6),(7,7)} U={(2,3),(5,0),(6,6),(7,7)} 6 P a g e

Discuss the good or bad properties of your reducer program. R(A,B) A=A B=B U(C,A) C=C S(B,C) 3. Explain the relational of semi-join reduction in distributed databases. Analyze 8 4. Describe how XML can be stored in a relational DBMS.How do we map Analyze 7 XML data to relations? Can we use query processing infrastructure of the relational DBMS? How do we publish relational data as XML? 5. How do we index collections of XML documents? What is the difference between indexing on structure versus indexing on Value? What is the path index? Apply 8 Prepared by: Mr. C Raghavendra, Assistant Professor, CSE HOD, CSE 7 P a g e