Exam Details
Subject | optimization techniques | |
Paper | paper 5 | |
Exam / Course | m.sc. data science | |
Department | ||
Organization | rayalaseema university | |
Position | ||
Exam Date | May, 2018 | |
City, State | andhra pradesh, kurnool |
Question Paper
M.Sc. DEGREE EXAMINATION, APRIL/MAY 2018.
Second Semester
Data Science
Paper III BIG DATA ANALYTICS
2 21423
Time 3 Hours Max. Marks 70
SECTION — A
Answer any FIVE questions. 6 30 Marks)
Each questions carries 6 marks.
1. Explain about features of distributed file system.
2. Explain about structured, unstructured and semi-structured data.
3. How big data analytics can help in detecting fraud? Explain with industry
application.
4. What are the advantages of Hadoop? Explain Hadoop Architecture and its
Components with proper diagram.
5. Write short notes on serialization.
6. Explain following commands of HDFS with syntax and at least one example of
each.
get
cp
chown.
7. Write about MRv1 and MRv2.
8. Explain about the entities of YARN.
SECTION — B
Answer ALL questions. 10 40 Marks)
UNIT I
9. What is Big data? Discuss it in terms of four dimensions, volume, velocity, variety
and veracity.
Or
10. Illustrate Matrix vector multiplication using Map reduce frame work.
UNIT II
11. Write Map Reduce code for counting occurrences of specific words in the input text
file. Also write the commands to compile and run the code.
Or
12. Explain how to move data in and out of Hadoop.
UNIT III
13. With necessary diagram explain the Anatomy of Map Reduce Job run?
Or
14. Discuss about common HDFS shell commands.
UNIT IV
15. What is Hadoop Eco system? Discuss about components of Hadoop Ecosystem.
Or
16. Explain with neat diagram, how Hadoop runs a map reduce job using YARN.
———————
Second Semester
Data Science
Paper III BIG DATA ANALYTICS
2 21423
Time 3 Hours Max. Marks 70
SECTION — A
Answer any FIVE questions. 6 30 Marks)
Each questions carries 6 marks.
1. Explain about features of distributed file system.
2. Explain about structured, unstructured and semi-structured data.
3. How big data analytics can help in detecting fraud? Explain with industry
application.
4. What are the advantages of Hadoop? Explain Hadoop Architecture and its
Components with proper diagram.
5. Write short notes on serialization.
6. Explain following commands of HDFS with syntax and at least one example of
each.
get
cp
chown.
7. Write about MRv1 and MRv2.
8. Explain about the entities of YARN.
SECTION — B
Answer ALL questions. 10 40 Marks)
UNIT I
9. What is Big data? Discuss it in terms of four dimensions, volume, velocity, variety
and veracity.
Or
10. Illustrate Matrix vector multiplication using Map reduce frame work.
UNIT II
11. Write Map Reduce code for counting occurrences of specific words in the input text
file. Also write the commands to compile and run the code.
Or
12. Explain how to move data in and out of Hadoop.
UNIT III
13. With necessary diagram explain the Anatomy of Map Reduce Job run?
Or
14. Discuss about common HDFS shell commands.
UNIT IV
15. What is Hadoop Eco system? Discuss about components of Hadoop Ecosystem.
Or
16. Explain with neat diagram, how Hadoop runs a map reduce job using YARN.
———————
Other Question Papers
Subjects
- big data analytics
- cloud computing
- data mining
- data warehousing and mining
- electronics instruments and measurements
- information security
- machine learning for big data
- optimization techniques
- python programming
- r programming
- software engineering