Why Hadoop Developers Require Training Sessions?

Hadoop technology is a pack of Opensource features that let developers to store and process big data in a distributed environment throughout computer clusters with the help of simple programming models.

The technology plays vital role in the professional life of those who are working in the IT field. If hadoop developers want to take a step ahead, they need to consider hadoop training.

hadoop training and developmentWhy hadoop? Answers are written below-

Hadoop Tells Latest Updates About Big Data Market                            

Once developers get complete training of hadoop, they are ready to deal with the latest updates coming from the Big Data market. Hadoop let them to store and process large amount of data with economical commodity hardware. Moreover, it acts as an operating system for HDFS- data file system.

Every other person now knows about Big Data after worldwide connectivity and cloud computing. Companies need to pay for the processing power only and they get storage as and when they need. Many challenges are posed by Big Data and Hadoop is a boon to such challenges.

Booming Vacancies In Hadoop Market

Hadoop development market is getting rich job listings in the past year. That means developers have a chance to take their career to the new path. This all started when big companies of the world begin hiring for hadoop developer skills.

Companies Are Keeping Pace With Competitors Using Hadoop

According the research made by IT leaders, hadoop is now a must-have technology for large enterprises. It is now not just a data platform. It is now considered as an essential part of the company.

Hadoop is a must-have skill that should be acquired anyway by developers. These are the reasons that explain the significance of hadoop technology for programmers and companies. Hadoop developers should know what is coming new with the technology.

Save

Advertisements

The concept of Hadoop Distribution File System

Aegis Hadoop developers will explain the concept of Hadoop Distribution File System (HDFS) to entire development community across the globe. HDFS is intended to adhere to the conventional distributed file systems and Google File System advantages. The Apache Hadoop framework has its own file system- HDFS. It is a fault-tolerant, self-healing system that is developed in Java to store excessive data (in petabytes or terabytes). Regardless of format and schema, HDFS offers high scalability, reliability, and throughput while running on vast clusters of a commodity machine.

hdfs-magic
A brief about the HDFS

HDFS is designed and intended to address most complications and problems associated with conventional file distributed system. Major characteristics of HDFS:

1. Massive storage of data- HDFS supports zeta bytes or petabytes, or more data.

2. Commodity Machine usage – User does not require highly expensive machine to run HDFS. User can run HDFS on easily available commodity hardware. It also helps in managing data and addressing issues without interrupting the client/user.

3. Single writer/ Multiple reader model- HDFS follows the principle ‘Write once-read many’ to resolve issues of data coherency. HDFS is intended for batch processing and not for interactive usage.

4. File system management- Along with conventional file systems, file management system is also supported by HDFS. It includes write, read, rename, delete, relocate, and modify directories or files.

Read More Related This :

Apache hadoop development tools (HDT) aims at promoting plugins in Eclipse to assist developers and make their development task simple on Hadoop platform. In this blog, we are going to overview of few features offered by HDT.