Apache Hadoop’s YARN is responsible for managing resources allocation and task execution across different nodes within a Hadoop cluster.
What is Apache Hadoop YARN?
Apache Hadoop, a Java-based open-source framework, is used by businesses to store and process large datasets across multiple servers. It provides a distributed file system, known as Hadoop Distributed File System (HDFS), and a MapReduce processing system that allows for distributed data processing across a cluster of nodes.
Yet, while Hadoop is great for processing large datasets, it wasn’t initially designed to work with other applications within the same cluster. Enter Apache Hadoop YARN (Yet Another Resource Negotiator). YARN is an essential component of Hadoop that enables applications to access and utilize resources in a shared infrastructure.
In short, YARN is responsible for allocating Hadoop’s computational resources to different applications and scheduling tasks on those resources.
FAQ about Apache Hadoop YARN
1. Why is Apache Hadoop YARN important?
YARN enables businesses to use a shared infrastructure by providing a central resource management platform that allocates computational resources to different applications. This resource allocation improves cluster utilization and application management.
2. What makes YARN different from Hadoop MapReduce?
Hadoop MapReduce was the primary computation engine for Hadoop, but it had limitations when it came to running interactive, iterative, and real-time applications. YARN, on the other hand, provides a general framework for processing and executing any application, not just MapReduce, across multiple nodes in a cluster.
3. How does YARN allocate and manage resources?
YARN follows a hierarchical architecture comprising of a ResourceManager (RM) and many NodeManagers (NMs) that handle the execution of tasks. The RM is responsible for allocating resources to various applications and scheduling those resources to perform the required tasks. Meanwhile, the NMs are responsible for monitoring node health and application progress and executing and managing the various container and task lifecycles.
4. What does an application developer need to know about YARN?
Developers need to have a clear understanding of YARN’s application submission and resource management process. They also need to determine the resources needed for their applications accurately. To submit applications to a YARN cluster, developers need to create a YARN Application Master that sets up, coordinates, and manages the application’s required containers and resources.
5. How has YARN evolved over time?
Since its inception in 2013, YARN has evolved alongside Hadoop, with improved features and functionality with each release. The latest version of YARN includes support for Docker containers, increased capacity scheduling, and support for GPUs, among other features.
Apache Hadoop YARN extends Hadoop’s functionality beyond MapReduce and enables an efficient resource allocation system for multiple applications running within the same cluster. As businesses increasingly adopt big data processing to manage massive datasets, YARN remains an essential component of the Hadoop ecosystem.