Hadoop Architecture and HDFS

Hadoop generally preferred to as Apache Hadoop is basically an open source software specially designed for storage, management and high precise processing of huge data on hardware clusters.Hadoop Architecture's working highly depends on its building blocks and it is mainly composed of five major building blocks. They are:

Map Reduce Framework: It is the most important part if the framework. The basic software part that supports the implementation of map paradigm.
YARN Infrastructure: The computation resources required for the framework is accomplished by the Yarn Infrastructure.
HDFS Federation: This entity is responsible for giving you the permanent and reliable storage of both the input and the output data.
Storage: It is an additional support system for intermediate storage of data.
Cluster: It makes the hardware of the complete architecture.
The scope of Hadoop in the coming time is going to be big. The increase in demand of Hadoop for the management of data will lead to increase in demand of trained Hadoop professionals. You can educate yourself with Big Data Hadoop Certification Course to excel in the race of future demand of this architectural software.

Purpose:

HDFS or Hadoop Distributed File System was designed for the purpose of managing the distributed data on commodity hardware. It is the best application for managing the applications having a huge data sets.

Features:

Failure Of Hardware:
Hardware failure is very common and usual. Management of data using HDFS employs several machines and the data is segregated between them. In a case of hardware failure, it is easy to find out the error and HDFS offers the recovery automatically.

Support To Large Data Sets:
The data sets having the file size varying between gigabytes to terabytes can be accessed easily using HDFS. It provides support to millions of files in a go and combines hundreds of files in a single data cluster.