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SYLLABUS

UNIT-I

Distributed Programming Using Java: Quick Recap and Advanced Java Programming: Generics, Threads, Sockets, Simple Client Server Programming Using JAVA, Difficulties in Developing Distributed Programs for Large Scale Clusters and Introduction to Cloud Computing.

UNIT-II

Distributed File Systems Leading to Hadoop File System: Introduction, Using HDFS, Hadoop Architecture, Internals of Hadoop File Systems.

UNIT-III

Map-Reduce Programming: Developing Distributed Programs and Issues, Why Map-Reduce and Conceptual Understanding of Map-Reduce Programming, Developing Map-Reduce Programs in Java, Setting Up the Cluster with HDFS and Understanding How Map-Reduce Works on HDFS, Running Simple Word Count Map-Reduce Program on the Cluster, Additional Examples of M-R Programming.

UNIT-IV

Anatomy of Map-Reduce Jobs: Understanding How Map-Reduce Program Works, Tuning MapReduce Jobs, Understanding Different Logs Produced by Map-Reduce Jobs and Debugging the MapReduce Jobs.

UNIT-V

Case Studies of Big Data Analytics Using MapReduce Programming: K-Means Clustering, Using Big Data Analytics Libraries Using Mahout.