Description: Hadoop Distributed Computing is a model that allows the processing of large volumes of data across multiple machines within a Hadoop cluster. This approach is based on the idea of breaking down complex tasks into smaller subtasks that can be executed simultaneously on different nodes, optimizing resource use and speeding up processing. Hadoop, which is based on the Hadoop Distributed File System (HDFS), allows for efficient and scalable data storage. The main features of this model include scalability, as more nodes can be added to the cluster as needed, and fault tolerance, which ensures that the system continues to operate even if one or more nodes fail. Additionally, Hadoop uses a programming model known as MapReduce, which facilitates parallel data processing. This approach not only improves efficiency but also enables organizations to handle large datasets that would be difficult to process in traditional monolithic systems. In summary, Hadoop Distributed Computing represents a powerful solution for large-scale data analysis, allowing companies to extract value from their data more effectively and quickly.
History: Hadoop was created in 2005 by Doug Cutting and Mike Cafarella as an open-source project inspired by Google’s work on MapReduce and the distributed file system. Since its release, it has significantly evolved, becoming one of the most widely used platforms for big data processing in the industry. In 2011, the Apache Foundation took over the project, which boosted its development and global adoption.
Uses: Hadoop is primarily used in the analysis of large volumes of data, such as data mining, log analysis, real-time data processing, and data storage. It is also common in machine learning applications and predictive analytics, where processing and analyzing large datasets is required to gain valuable insights.
Examples: A practical example of Hadoop is its use by companies like Yahoo! and Facebook, which use the platform to process and analyze large amounts of data generated by their users. Another case is Netflix, which employs Hadoop to enhance its content recommendations through viewing data analysis.
