what is Apache Hadoop?
History And Technology Behind The Apache Hadoop
Apache Hadoop is a commonly known open source software framework that is designed for storage and distribution of processed Big Data on commodity hardware. Apache software foundation has sponsored this Apache product for making it a free Java-based programming. It is because of Hadoop that applications can easily be run on thousands of nodes that involve large amounts of terabytes. It facilitates a rapid transfer of data so that the system can continue to operate without any interruptions when there is a failure in the nodes. Hence, this approach lowers the risk of catastrophic system failure in any organization.
The primary inspiration of this framework was Google’s MapReduce. In this software framework, an application is broken down into small parts. These parts can easily be run on nodes. The creator of Hadoop, Doug Cutting named this framework after the stuffed toy elephant of his child. The current ecosystem of Apache Hadoop comprises of Hadoop Kernel, MapReduce and the file distribution system of Hadoop along with numbers of related projects like HBase, Apache Hive and Zookeeper. The framework of Hadoop is used by small and big players in the market including Google, IBM and Yahoo. They use it for applications involved in advertising and search engines. Apart from working with Windows and Linux, it can also work with OS X and BSD.
Taking A Look Back:
As per the definition of birth, Apache Hadoop is more than 10 years now. In this decade, the framework has helped in serving large numbers of purposes. These include:
- Hopeful answers to Yahoo’s search engine woes,
- Serving a computing platform for general purposes,
- Being the foundation of the next generation data-based applications.
It is predicted that Apache Hadoop alone can be worth $800 million in 2016. At the same time, it is likely that it will draw a big data market that will hit more than $25 billion. It has also helped the hundreds of startups and spurred millions in venture capital investment.
Interaction In Big Data Style:
On the basis of the types of parallel processing engines for analyzing relational data over the years, Hadoop will help analysts in asking and getting answers to their questions faster, closer to the speed of their intuitions. There is no denying the fact that SQL and its processing techniques brings a lot to Hadoop due to which Hadoop is able to bring the output to the table. It brings flexibility and scale that does not exist in traditional data.
Similar To Fine Wine:
Hadoop is similar to fine wine in large numbers of ways. It gets better with age when rough profiles are smoothed out. Consequently, those who wait to consume it will have the best of experiences. There are many companies that work at the distribution levels and this is undoubtedly significant. However, not every company can afford to manage Hadoop on a day to day basis. Based on what is transpiring today, the next question is what will Hadoop become next and the most suitable answer to this question is Hadoop will become faster and more useful like never before.