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The most well known technology used for Big Data is Hadoop.
It is actually a large scale batch data processing system

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  1. 1. Technical Seminar on HADOOP TECHNOLOGY Under the Guidance of P.V.R.K.MURTHY, M.Tech Assistant Professor
  2. 2. What is hadoop Technology?? Why hadoop? Developers of hadoop Technology Famous hadoop users Hadoop Features Hadoop Architectures Core-Components of Hadoop Hadoop High Level Architechture Hadoop cluster CONTENTS
  3. 3. What is HDFS HDFS – Name Node features: HDFS-name node architecture HDFS-data node Hadoop MAPREDUCE Benefits of Hadoop… Conclusion Reference CONTENTS…
  4. 4. HADOOP TECHNOLOGY What is Hadoop Technology?? •The most well known technology used for Big Data is Hadoop. •It is actually a large scale batch data processing system
  5. 5. Why Hadoop ?? •Distributed cluster system •Platform for massively scalable applications •Enables parallel data processing
  6. 6. Developers of Hadoop Technology: Michael j. cafarella Doug cutting
  7. 7. Famous Hadoop users
  8. 8. Hadoop Features •Hadoop provides access to the file systems • The Hadoop Common package contains the necessary JAR files and scripts •The package also provides source code, documentation and a contribution section that includes projects from the Hadoop Community.
  10. 10. Core-Components of Hadoop: Hadoop distributive file system. Map reduce.
  11. 11. What is HDFS ? •Distributed file system •Traditional hierarchical file organization •Single namespace for the entire cluster •Write-once-read-many access model •Aware of the network topology
  12. 12. Hadoop High Level Architechture
  13. 13. Hadoop cluster •A Small Hadoop Cluster Include a single master & multiple worker nodes Master node: Data Node Job Tracker Task Tracker Name Node Slave node: Data Node Task Tracke
  14. 14. HDFS – Name Node Features Metadata in main memory: •List of files •List of blocks for each file •List of Data Nodes for each block •File attributes •Creation time •Records every change in the metadata
  15. 15. HDFS-name node architecture Secondary name node 3.Store to HDD Primary name-node RAM HDD RAM HDD 1. Pull transaction log 4.Push 2. Merge changes
  16. 16. HDFS-Data node •Block Server Stores data in the local file system •Periodic validation of checksums •Periodically sends a report of all existing blocks to the Name Node
  17. 17. Hadoop MAPREDUCE Job Tracker: Splitting into map and reduce tasks Scheduling tasks on a cluster node Task Tracker: Runs Map Reduce tasks periodically Map reduce implementation:
  18. 18. Benefits of Hadoop… •Cost Saving and efficient and reliable data processing •Provides an economically scalable solution •Storing and processing of large amount of data •Data grid operating system •It is deployed on industry standard servers rather than expensive specialized data storage systems. • Parallel processing of huge amounts of data across inexpensive, industry-standard servers.
  19. 19. Why commodity hw ? because cheaper designed to tolerate faults Why HDFS ? network bandwidth vs seek latency Why Map reduce programming model? parallel programming large data sets moving computation to data single compute + data cluster CONCLUSION
  20. 20. REFERENCES •Apache Hadoop! (http://hadoop.apache.org) •Hadoop on Wikipedia (http://en.wikipedia.org/wiki/Hadoop) •Cloudera - Apache Hadoop for the Enterprise (http://www.cloudera.com