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Hadoop Yarn Architecture

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Apache Hadoop YARN Architecture consists of the following main components :

You can consider YARN as the brain of your Hadoop Ecosystem. The image above represents the YARN Architecture.

The first component of YARN Architecture is,

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Resource Manager

  • It is the ultimate authority in resource allocation
  • On receiving the processing requests, it passes parts of requests to corresponding node managers accordingly, where the actual processing takes place.
  • It is the arbitrator of the cluster resources and decides the allocation of the available resources for competing applications.
  • Optimizes the cluster utilization like keeping all resources in use all the time against various constraints such as capacity guarantees, fairness, and SLAs.
  • It has two major components:  a) Scheduler    b) Application Manager

        a) Scheduler

  • The scheduler is responsible for allocating resources to the various running applications subject to constraints of capacities, queues etc.
  • It is called a pure scheduler in ResourceManager, which means that it does not perform any monitoring or tracking of status for the applications.
  • If there is an application failure or hardware failure, the Scheduler does not guarantee to restart the failed tasks.
  • Performs scheduling based on the resource requirements of the applications.
  • It has a pluggable policy plug-in, which is responsible for partitioning the cluster resources among the various applications. There are two such plug-ins: Capacity Scheduler and Fair Scheduler, which are currently used as Schedulers in ResourceManager.

        b) Application Manager

  • It is responsible for accepting job submissions.
  • Negotiates the first container from the Resource Manager for executing the application specific Application Master.
  • Manages running the Application Masters in a cluster and provides service for restarting the Application Master container on failure.

Coming to the second component which is :

Node Manager

  • It takes care of individual nodes in a Hadoop cluster and manages user jobs and workflow on the given node.
  • It registers with the Resource Manager and sends heartbeats with the health status of the node.
  • Its primary goal is to manage application containers assigned to it by the resource manager.
  • It keeps up-to-date with the Resource Manager.
  • Application Master requests the assigned container from the Node Manager by sending it a Container Launch Context(CLC) which includes everything the application needs in order to run. The Node Manager creates the requested container process and starts it.
  • Monitors resource usage (memory, CPU) of individual containers.
  • Performs Log management.
  • It also kills the container as directed by the Resource Manager.

The third component of Apache Hadoop YARN is,

Application Master

  • An application is a single job submitted to the framework. Each such application has a unique Application Master associated with it which is a framework specific entity.
  • It is the process that coordinates an application’s execution in the cluster and also manages faults.
  • Its task is to negotiate resources from the Resource Manager and work with the Node Manager to execute and monitor the component tasks.
  • It is responsible for negotiating appropriate resource containers from the ResourceManager, tracking their status and monitoring progress.
  • Once started, it periodically sends heartbeats to the Resource Manager to affirm its health and to update the record of its resource demands.

The fourth component is:

Container

  • It is a collection of physical resources such as RAM, CPU cores, and disks on a single node.
  • YARN containers are managed by a container launch context which is container life-cycle(CLC). This record contains a map of environment variables, dependencies stored in a remotely accessible storage, security tokens, payload for Node Manager services and the command necessary to create the process.
  • It grants rights to an application to use a specific amount of resources (memory, CPU etc.) on a specific host.