Hadoop Distributed System


        Hadoop Distributed System


Hadoop is an open-source framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It’s designed to scale from single servers to thousands of machines, each offering local computation and storage.

The core components of Hadoop include:

1. Hadoop Distributed File System (HDFS): It’s a distributed file system that stores data on commodity machines, providing high aggregate bandwidth across the cluster.

2. Hadoop YARN: This component is responsible for managing and monitoring resources in the cluster and managing the scheduling of user applications.

3. Hadoop MapReduce: It’s a programming model for processing and generating large datasets. Users can write applications in various languages like Java, C++, and Python.

4. Hadoop Common: These are Java libraries and utilities required by other Hadoop modules. They provide filesystem and OS-level abstractions and contain Java files and scripts to start Hadoop.

Hadoop allows for processing large data sets in parallel, providing fault tolerance and scalability. It’s a preferred tool for handling big data and analytics.

Hadoop Training Demo Day 1 Video:

You can find more information about Hadoop Training in this Hadoop Docs Link



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