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Apache Hadoop is an open source and Scalable framework written in Java. In this data resides in a distributed file system which is called a Hadoop Distributed File system. Applications built using HADOOP are run on large data sets distributed across clusters of commodity computers.
Components of Hadoop includes
This is used for writing applications which are run on Hadoop. These MapReduce programs are capable of processing enormous data in parallel on large clusters of computation nodes.
Hadoop Distributed File System
HDFS takes care of the storage part of Hadoop applications. MapReduce applications consume data from HDFS. HDFS creates multiple replicas of data blocks and distributes them on compute nodes in the cluster.
There are mainly five building blocks inside this runtime environment.cluster is the set of host machines (nodes). Nodes may be partitioned in racks. This is the hardware part of the infrastructure.YARN Infrastructure (Yet Another Resource Negotiator) is the framework responsible for providing the computational resources needed for application executions. Two important elements are the Resource Manager and Node Manager.
The client submits an application to the Resource Manager. The Resource Manager allocates a container and contacts the related Node Manager. The Node Manager launches the container. The Container executes the Application Master.
The HDFS Federation is the framework responsible for providing permanent, reliable and distributed storage. This is typically used for storing inputs and output. The Application Master is responsible for the execution of a single application. It asks for containers from the Resource Manager and executes specific programs on the obtained containers. The Application Master knows the application logic and thus it is framework-specific.
Some of the important features of Hadoop are
Suitable for Big Data Analysis
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