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The Hadoop framework transparently provides both reliability and data motion to applications. Hadoop implements a computational paradigm named Map Reduce, where the application is divided into many small fragments of work, each of which may be executed or re-executed on any node in the cluster. It provides a distributed file system that stores data on the compute nodes, providing very high aggregate bandwidth across the cluster. Both map/reduce and the distributed file systems are designed so that node failures are automatically handled by the framework. It enables applications to work with thousands of computation-independent computers and peta bytes of data. The entire Apache Hadoop platform is commonly considered to consist of the Hadoop kernel, Map Reduce and Hadoop Distributed File System (HDFS), and number of related projects including Apache Hive, Apache HBase, Apache Pig, Zookeeper etc.
Wanna to learn more on Big Data, Hadoop?
Hadoop trained by Certified Corporate Professional. Duration of Training is 40 hours. Special Add ones of Training: Training based on Cloudera Certification is also provided.
Core Hadoop conists of: - Introduction to Hadoop, Hadoop Eco Systems, The Hadoop Distributed File System (HDFS), Map Reduce, Map/Reduce Programming – Java/pig/hive.Core Hadoop Architects Consits of:- Introduction to Distributed systems & Big Data for Architects, Introduction to Hadoop, Hadoop Eco Systems, The Hadoop Distributed File System (HDFS), Map Reduce, Map/Reduce Programming – Java/pig/hive
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