Big Data and Analytics Unit 2 Notes AKTU (BCDS601)

AKTU · BTECH · Semester 6 · Big Data and Analytics · Unit 2 · Notes

AKTU Big Data and Analytics (BCDS601) Unit 2 notes for B.Tech Semester 6 – Hadoop and MapReduce. Topics: Apache Hadoop, Hadoop Ecosystem, MapReduce…

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Unit 2: Hadoop and MapReduce – AKTU syllabus topics

Apache Hadoop: History of Hadoop, Hadoop Distributed File System, Components of Hadoop
Hadoop Ecosystem: Hadoop Streaming and Pipes, Scaling Out and Data Format
MapReduce Framework: MapReduce Basics and Working, Developing MapReduce Application, Anatomy of MapReduce Job Run
Advanced MapReduce: Shuffle Sort and Task Execution, MapReduce Types Input Output Formats, Real World MapReduce

Q4b. Discuss the process of developing a MapReduce application. What are the key steps involved in writing, testing, and deploying a MapReduce program? (10 marks, 2023-24)
Q4b. Discuss the Working of Map Reduce and its Characteristics (10 marks, 2023-24)
Q2b. Illustrate the architecture of Map-Reduce. (10 marks, 2021-22)
Q4a. Explain the detailed architecture of Map-Reduce (10 marks, 2021-22)
Q4a. Explain the Anatomy of MapReduce job run. (10 marks, 2017-18)
Q4b. Discuss the different types and formats of Map Reduce with examples. (10 marks, 2017-18)
Q3a. How does Hadoop system analyze data? Explain your answer with example. (10 marks, 2017-18)
Q4a. Discuss the process of job scheduling and task execution in Hadoop. How does Hadoop ensure fault tolerance during task execution? (7 marks, 2024-25)
Q2c. Discuss the detailed architecture of Map-Reduce. (7 marks, 2024-25)
Q1c. What do you mean by MapReduce? List its main phases. (2 marks, 2024-25)