Exam Details
Subject | big data technologies | |
Paper | ||
Exam / Course | mca | |
Department | ||
Organization | apj abdul kalam technological university | |
Position | ||
Exam Date | April, 2018 | |
City, State | kerala, thiruvananthapuram |
Question Paper
B BC402 Pages: 1
Page 1 of 1
Reg.
APJ ABDUL KALAM TECHNOLOGICAL UNIVERSITY
SECOND SEMESTER (Second Year Direct)
FOURTH SEMESTER (Regular) MCA DEGREE EXAMINATION, APRIL 2018
Course Code: RLMCA 204
Course Name: BIG DATA TECHNOLOGIES
Max. Marks: 60 Duration: 3 Hours
PART A
Answer all questions. Each question carries 3 marks
1. What do the four denote? Discuss.
2. How distributed file systems helps Big Data storage?
3. On what concept the Hadoop framework works?
4. What are the main components of a Hadoop Application?
5. Summarize the uses of Map Reduce.
6. How in memory data grid helps in Big Data?
7. Discuss about RDBMS.
8. Compare and contrast correlation and regression.
PART B
Answer any one from each question. Each question carries 6 marks
9. a. How analytical approaches work in Big Data?
OR
b. Classify the types of data.
10. a. Differentiate between Sharding and replication.
OR
b. Contrast CAP, BASE and ACID theorem.
11. a. Write a short note on HBase.
OR
b. Exemplify Hadoop Ecosystem.
12. a. Explore the techniques that optimize the working of MapReduce.
OR
b. Execute the working of MapReduce Algorithm.
13. a. Interpret the NoSQL databases.
OR
b. Specify the cases where in memory storage devices are appropriate.
14. a. Recognize the types of semantic analysis.
OR
b. Classify the statistical analysis methods.
Page 1 of 1
Reg.
APJ ABDUL KALAM TECHNOLOGICAL UNIVERSITY
SECOND SEMESTER (Second Year Direct)
FOURTH SEMESTER (Regular) MCA DEGREE EXAMINATION, APRIL 2018
Course Code: RLMCA 204
Course Name: BIG DATA TECHNOLOGIES
Max. Marks: 60 Duration: 3 Hours
PART A
Answer all questions. Each question carries 3 marks
1. What do the four denote? Discuss.
2. How distributed file systems helps Big Data storage?
3. On what concept the Hadoop framework works?
4. What are the main components of a Hadoop Application?
5. Summarize the uses of Map Reduce.
6. How in memory data grid helps in Big Data?
7. Discuss about RDBMS.
8. Compare and contrast correlation and regression.
PART B
Answer any one from each question. Each question carries 6 marks
9. a. How analytical approaches work in Big Data?
OR
b. Classify the types of data.
10. a. Differentiate between Sharding and replication.
OR
b. Contrast CAP, BASE and ACID theorem.
11. a. Write a short note on HBase.
OR
b. Exemplify Hadoop Ecosystem.
12. a. Explore the techniques that optimize the working of MapReduce.
OR
b. Execute the working of MapReduce Algorithm.
13. a. Interpret the NoSQL databases.
OR
b. Specify the cases where in memory storage devices are appropriate.
14. a. Recognize the types of semantic analysis.
OR
b. Classify the statistical analysis methods.
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