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Apache Hadoop is one of the most popular tools for big data processing. It has been successfully deployed in production by many companies for several years. Though Hadoop is considered a reliable, scalable, and cost-effective solution, it is constantly being improved by a large community of developers. As a result, the 2.0 version offers several revolutionary features, including Yet Another Resource Negotiator (YARN), HDFS Federation, and a highly available NameNode, which make the Hadoop cluster much more efficient, powerful, and reliable. 

Apache Hadoop 2.0 includes YARN, which separates the resource management and processing components. The YARN-based architecture is not constrained to MapReduce.
New developmens in Hadoop 2.0 Architecture with YARN:
  1. ResourceManager instead of a cluster manager
  2. ApplicationMaster instead of a dedicated and short-lived JobTracker
  3. NodeManager instead of TaskTracker
  4. A distributed application instead of a MapReduce job
Basic changes in Hadoop 2.0 architecture are:

The ResourceManager, the NodeManager, and a container are not concerned about the type of application or task.

All application framework-specific code is simply moved to its ApplicationMaster so that any distributed framework can be supported by YARN — as long as someone implements an appropriate ApplicationMaster for it.

Thanks to this generic approach, the dream of a Hadoop YARN cluster running many various workloads comes true. Imagine: a single Hadoop cluster in your data center that can run MapReduce, Giraph, Storm, Spark, Tez/Impala, MPI, and more.


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