Video Animation Company Junagadh
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,
Video Animation Company Junagadh
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.