Overview of Hadoop Applications
Hadoop is nothing but a resource of software framework which is generally used in the processing immense data simultaneously across many servers. In the recent years, it has turned out to be one of most feasible option for businesses, which has the never-ending requirement to save and manage all the data. The web-based businesses like Amazon, Facebook, Yahoo, and eBay have used high-end Hadoop applications to deal with their large data sets. It is assumed that Hadoop is relevant to both small and large organizations.
Hadoop is capable to process a large chunk of data in a lesser time which allows the companies to analyze that this was not possible earlier within that predetermined time. Another significant advantage of Hadoop applications is the cost-effectiveness. One can remove the high cost involved in the software licenses and the charge that has to be upgraded periodically when using anything except Hadoop. It is extremely recommended for the businesses, which have to work with large amount of data, to go for Hadoop applications as it tries in fixing any problem.
The Hadoop applications are divided into two parts; one is the HDFS other one is Hadoop map. HDFS stands for Hadoop Distributed File System. Hadoop map helps in processing data and scheduling job depending on priorities. Apart from these two components there are nine more parts of Hadoop. There are three most familiar functions of Hadoop applications. The first function is the storage of data and analysis of all the data. It does not need the loading of the RDBMS. It is used in the adaptation of huge repository of semi structured and unstructured data. Such complex data are very hard to understand in SQL tools like data mining and analyzing the graph.
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