HADOOP: THE OPEN SOURCE FRAMEWORK FOR DATA PROCESSING

Hadoop software library is a framework that was developed for reliable, distributed and scalable processing. This is specifically for large data sets that are divided as clusters of computers using a few simple programming models. It was developed by Apache Software Foundation on April 1, 2006. This software is implemented in the Java programming language. It has a distributed file system in it for the management purposes. It uses MapReduce programming models to distribute the storage for its data. It uses the concept of clustering to split the files into blocks and assign to different file locations. This approach uses the concept of data locality where manipulation of data occurs for the ones that have access permissions. There are four base modules that Hadoop framework is composed of. They are:
Hadoop Common- container of libraries and utilities
Hadoop distributed file system- stores data in commodity machines with accurate bandwidth that is required
For the Hadoop to work on your system, it will require you to have a Java Run-time Environment (JRE) and Standard Secure Shell (SSH). Clusters are used to group the data into blocks in the form of nodes and load it into the HDFS. HDFS consists of five main services in the form of nodes: Name node, Secondary Name node, data node, job tracker and task tracker. Here are each in brief:
Name node-acts as a main central node which manages the file system, track files and has metadata and whole data in it
Resource box-
As we can see with the massive scope for the Hadoop framework, we get to conclude that a major framework like Hadoop is required for the maintenance, working and further expansion of data sets. It is an emerged and enormous area and would be a great option for students to take Hadoop training and make it as their career option.
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