Published on : May 05, 2016
Hadoop was born out of the need to process large volumes of data. In present times, the ceaseless penetration of smart electronics across all industry vertical is generating massive amounts of data that needs to be stored and accessed from anywhere in the world.
Hadoop refers to a Java-based open source framework that enables storing and processing large volumes of data in a distributed computing environment. The application framework and the technology ecosystem of Hadoop is managed and supported by the Apache Software Foundation.
Hadoop comprises two main subprojects: MapReduce and Hadoop Distributed File System (HDFS). MapReduce is the core component of Hadoop, the application framework that allows the distributed processing of large sets of data on clusters of commodity hardware. The MapReduce framework schedule tasks, monitor tasks, and re-executes failed tasks. The other subproject of Hadoop, HDFS refers to a distributed file system that offers scalability and reliability for data storage over large clusters of commodity hardware.
Since its inception in 2009, the global Hadoop market is displaying progressive growth as it has emerged as one of the best tools to manage big data. Increasing volumes of both unstructured and structured data across a spectrum of industries such as healthcare, retail, telecommunications, media and entertainment, and BFSI is exhibiting demand for Hadoop solutions. This is predominantly due to the ever-increasing use of smart electronics that generate large sets of data for day to day functioning.
Data that is generated across a host of industries include web content, social media data, administrative documents, and e-mail. As most of this data is unstructured, organizations are adopting solutions for sorting this data to make it utilizable. Hence, in order to structure this data corporations are spending large sums of money to deploy systems that can are compatible with Hadoop and similar other open-source application frameworks.