Hadoop is the widely used and most popular technology for Big Data. The Apache Hadoop is basically Infrastructure software for storing and processing very big data Apache Open Source team manages this platform.
Apache defines it as a framework that allows for the distributed processing of large data sets across clusters of computers using relatively simple programming models. The platform is highly scalable to accommodate from a few servers to thousands of machines that can do local computing and store enormous data.
It is used by some of the leading web companies such as Yahoo, eBay, LinkedIn and Facebook. This platform gives a facility of handling data in large quantity and managing them in a very cost effective manner.
To understand it, let us understand the term BIG DATA
The first thing to recognize is that Big Data does not have one single definition and it does not mean only large data but lots of data type. In fact, it’s a term that describes
- Capturing and managing lots of information: Numerous Independent market and research studies have found that data volumes are doubling every year. On top of all this extra new information, a significant percentage of organizations are also storing three or more years of historic data.
- Working with many new types of data: From one of the recent research it has been concluded that almost 80% of data that enterprises gather are in a much unstructured format. Such data include images, videos, audios, social media posts, text messages, etc. Enterprises, till Hadoop’s introduction, found it very difficult to manage the data and were unable to make the most out of it.
What can be done with BIG DATA?
Big Data has great potential to create positive impact on the business and provide insights that can be advantageous to enterprises. Big data can advantageous in:
- Customer Interaction and Getting easily discovered
- Delivering the services and products to various markets
- Attaining a good position over competitors
Most Interesting part is that these insights can be delivered in real-time, but only if your infrastructure is designed properly
Hadoop is a misnomer. What’s called “Hadoop” is really slang for a bunch of different open source software. Apache lists eight other solutions as part of Hadoop-related projects, what people really mean by “Hadoop” is the “Hadoop Core,” which is:
Hadoop’s Distributed File System is designed in a way that it can store large amount of data in clusters and access those data at high speed. The Main advantage of HDFS is that it is fast, scalable, reliable and fault-tolerant. As it is a Java based system it can be deployed on any server and more space can be added at any point of time.
MapReduce framework is used to code the applications which can process vast amount of data in the file system. MapReduce works on the principle of “divide and conquer”. It splits the data into various chunks and clusters them in parallel. The framework has an advantage of re-executing failed tasks.