Description: Hadoop resource management refers to the process of managing and allocating resources in a Hadoop cluster, which is a framework designed for processing and storing large volumes of data. This process is crucial to ensure that the cluster’s resources, such as CPU, memory, and storage, are used efficiently and effectively. Hadoop employs a distributed programming model that allows users to run tasks in parallel, maximizing performance and reducing processing time. Resource management is primarily carried out through YARN (Yet Another Resource Negotiator), which acts as a centralized resource management system. YARN enables cluster administrators to define resource allocation policies, prioritize jobs, and monitor resource usage in real-time. Additionally, it facilitates cluster scalability, allowing nodes to be added or removed as needed. Proper resource management not only improves operational efficiency but also optimizes the operational cost of the cluster, which is essential in business environments where handling large volumes of data is a constant necessity.
