Apache Hadoop YARN Description
YARN's core concept revolves around the division of resource management and job scheduling/monitoring into distinct daemons, aiming for a centralized ResourceManager (RM) alongside individual ApplicationMasters (AM) for each application. Each application can be defined as either a standalone job or a directed acyclic graph (DAG) of jobs. Together, the ResourceManager and NodeManager create the data-computation framework, with the ResourceManager serving as the primary authority that allocates resources across all applications in the environment. Meanwhile, the NodeManager acts as the local agent on each machine, overseeing containers and tracking their resource consumption, including CPU, memory, disk, and network usage, while also relaying this information back to the ResourceManager or Scheduler. The ApplicationMaster functions as a specialized library specific to its application, responsible for negotiating resources with the ResourceManager and coordinating with the NodeManager(s) to efficiently execute and oversee the execution of tasks, ensuring optimal resource utilization and job performance throughout the process. This separation allows for more scalable and efficient management in complex computing environments.
Apache Hadoop YARN Alternatives
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Apache Helix
Apache Helix serves as a versatile framework for managing clusters, ensuring the automatic oversight of partitioned, replicated, and distributed resources across a network of nodes. This tool simplifies the process of reallocating resources during instances of node failure, system recovery, cluster growth, and configuration changes. To fully appreciate Helix, it is essential to grasp the principles of cluster management. Distributed systems typically operate on multiple nodes to achieve scalability, enhance fault tolerance, and enable effective load balancing. Each node typically carries out key functions within the cluster, such as data storage and retrieval, as well as the generation and consumption of data streams. Once set up for a particular system, Helix functions as the central decision-making authority for that environment. Its design ensures that critical decisions are made with a holistic view, rather than in isolation. Although integrating these management functions directly into the distributed system is feasible, doing so adds unnecessary complexity to the overall codebase, which can hinder maintainability and efficiency. Therefore, utilizing Helix can lead to a more streamlined and manageable system architecture.
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AWS Elastic Beanstalk
AWS Elastic Beanstalk offers a user-friendly platform for deploying and scaling web applications and services built using various programming languages such as Java, .NET, PHP, Node.js, Python, Ruby, Go, and Docker, utilizing well-known servers like Apache, Nginx, Passenger, and IIS. By merely uploading your code, Elastic Beanstalk takes care of the entire deployment process, which includes capacity provisioning, load balancing, auto-scaling, and monitoring application health. Importantly, you maintain complete control over the AWS resources that support your application and can access the underlying infrastructure whenever necessary. There is no extra cost associated with Elastic Beanstalk itself; you are charged solely for the AWS resources required to store and operate your applications. Notably, Elastic Beanstalk is considered the quickest and most straightforward method for deploying your application on AWS. You can effortlessly upload your application using the AWS Management Console, a Git repository, or an integrated development environment (IDE) like Eclipse or Visual Studio, ensuring a seamless integration into your workflow. This flexibility allows developers to focus on coding rather than worrying about the intricacies of deployment.
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Company Details
Company:
Apache Software Foundation
Year Founded:
1999
Headquarters:
Uniited States
Website:
hadoop.apache.org/docs/current/hadoop-yarn/hadoop-yarn-site/YARN.html
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