Hadoop is an open source framework for running large-scale data processing jobs across clusters of computers. It has two main components: HDFS for reliable storage and Hadoop MapReduce for distributed processing. HDFS stores large files across nodes through replication and uses a master-slave architecture. MapReduce allows users to write map and reduce functions to process large datasets in parallel and generate results. Hadoop has seen widespread adoption for processing massive datasets due to its scalability, reliability and ease of use.

1. Hadoop

3. Hadoop

5. What we need?

6. What we need?

7. What we need? Job data data data

8. What we need? data job data

9. How?

10. Hadoop is at your service!!

11. Apache Hadoop is an open source Java software framework for running data-intensive applications on large clusters of commodity hardware. Hadoop

13. Hadoop Distributed Filesystem HDFS, the Hadoop Distributed File System, is a distributed file system designed to hold very large amounts of data (terabytes or even petabytes), and provide high-throughput access to this information.

18. Hdfs NameNode Hdfs DataNode Hdfs DataNode Hdfs aware application Posix API HDFS API Hdfs view Network Stack Regular filesystem Specific drivers.. HDFS Client Block Diagram Client computer

22. Hadoop MapReduce Map Reduce is a programming model and an associated implementation for processing and generating large data sets.

30. MapReduce DataFlow Example:Word Count Hi,how are you? Iam good Hello Hello how are you? Not so good Are 1 hi 1 how 1 you 1 Are 1 Hello 1 Hello 1 how 1 you 1 Are 2 Hello 2 Hi 1 how 2 you 2 Are[1 1] Hello[1 1] Hi[1] how[1 1] you[1 1] Map Reduce Input Intermediate results Output merged Sorted

37. Hadoop Architecture

38. Hadoop is flourishing...

39. Hadoop is now a part of...

40. Hadoop users..

41. Thank you