Introduction to the role of Yarn Explorer

Yarn is a resource manager for large-scale distributed computing. It is one of the core components of the Apache Hadoop ecosystem and aims to provide efficient cluster resource management and job scheduling.

The main functions of Yarn Explorer include:

1. Cluster resource management: Yarn resource manager is responsible for managing computing resources in the entire Hadoop cluster. It tracks the available resources (such as memory, CPU, etc.) in the cluster, and allocates and schedules them according to the requirements of applications.
2. Job scheduling: Yarn resource manager makes the best use of cluster resources by scheduling different jobs. It receives job requests from application clients and assigns these jobs to the available computing nodes (Node Manager) in the cluster for execution.
3. Fault tolerance and high availability: Yarn resource manager has fault tolerance mechanism, which can monitor each component in the cluster and automatically recover in case of failure. In addition, by configuring multiple instances of resource managers, you can achieve high availability of resource managers and ensure that the cluster can continue to operate normally even if a resource manager fails.
4. Resource isolation: Yarn Explorer supports resource isolation for different applications. It uses the concept of container to divide cluster resources into multiple independent resource allocation units, and each application runs in its own container to achieve resource isolation and protection.

In a word, as the core component of Hadoop cluster, Yarn resource manager provides functions such as cluster resource management, job scheduling, fault tolerance and resource isolation, which makes large-scale distributed computing environment more efficient and reliable.