1. Introduction to
MapReduce

2.  Hadoop
 What is MapReduce
 an example
 MapReduce Process
 Job Tracker & Task Tracker
 Anatomy of File Write
 Anatomy of File Read
 Replication & Rack awareness

3. Hadoop is a framework that allows
for distributed processing of large
data sets across clusters of
commodity computers using a
simple programming model

4. Hadoop was designed to enable applications to make most out of cluster
architecture by addressing two key points:
1. Layout of data across the cluster ensuring data is evenly distributed
2. Design of applications to benefit from data locality
It brings us two main mechanism of hadoop hdfs and hadoop MapReduce

5. What is MapReduce

6. example : election

7. MapReduce process

8. Job Tracker

9. Job Tracker (contd.)

10. Job Tracker (contd.)

12. Anatomy of File Write

13. Anatomy of File Read

14. Replication and Rack Awareness