What is Apache Hadoop?
Inspired by a Google File System paper and named after a toy elephant, Apache Hadoop officially started in 2006 and continues evolving today. As part of the open-source software model, Hadoop grows through the contributions of a dedicated team of volunteers. The software is a framework for distributed storage and big data processing, both key concepts within the Internet of Things.
Open Source IoT
Open Source IoT projects like Apache Hadoop allow companies and developers to tackle large-scale ventures like the Internet of Things together. Without proprietary licensing or corporate control, Open Source Software (OSS) enables cooperation and coordination across industries and even between business competitors. Additionally, the advent of open source IoT throughout industrial applications opens new opportunities. Many smaller businesses can now take advantage of IoT technology without needing a high-cost dedicated development team.
Big Data Processing and Distributed Computing in the Internet of Things
As Apache Hadoop and other OSS solutions grow, so do the possibilities through the application of IoT devices. While Big Data requires a lot of individual points to work effectively, Hadoop provides a solid framework for managing those nodes. The approach chosen by the team uses data locality – nodes manipulating their own accessible data. Unlike conventional supercomputer architecture, this method allows datasets to be processed quicker and more efficiently. Additionally, the team developing Apache Hadoop designed it for scalability. This permits both single-server and enterprise systems at the same level of computation performance. The software library also carries application-layer error detection, which amplifies the advantages of a distributed computing cluster model. Although an individual device may fail, the entire system dynamically adjusts and corrects as a whole.
Hadoop Distributed File System (HDFS)
Apache created HDFS as a decentralized and versatile Java-based file system for their data management framework. Through the Hadoop Distributed File System, users access application data at high-speeds via parallelization. With a unique block protocol, each data node sends data blocks over the network. The filesystem can be directly mounted through a Filesystem in Userspace (FUSE) virtual file system on some Unix operating systems such as Linux.
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