Everything you should know about Apache Hadoop Yarn

Hadoop YARN (Yet Another Resource Negotiator) is a cluster management system responsible for managing resources and running applications in a Hadoop cluster. Essentially, Hadoop YARN is responsible for efficiently using the cluster's resources, such as storage and computing power, and running various applications on a cluster.

Hadoop YARN consists of two core components: the ResourceManager and the NodeManager. The ResourceManager is responsible for coordinating and monitoring the resources in the cluster. It receives resource requests from the applications and assigns tasks to the NodeManagers to be executed across the cluster environment. The NodeManager is responsible for running the applications on the node and managing the resource usage of the node.

Applications to run on Hadoop YARN must be packaged into containers that contain resource requirements and other relevant information. The ResourceManager distributes these containers to the NodeManagers, which run them and ensure they get the resources they need. Once the containers are completed, the NodeManager releases the resources so that they are available to other applications.

Hadoop YARN is designed to be flexible and scalable, allowing developers to support various applications running on different frameworks such as MapReduce, Spark, Hive, and others.

How can you monitor and manage resource usage in Hadoop YARN?

There are various methods to monitor and manage resource usage in Hadoop YARN. Some of the main methods are:

1. YARN Web UI: YARN Web UI provides a graphical user interface for monitoring resource consumption. You can click on the Web UI access by using the URL Open :8088 in the web browser. You can then view the resource consumption of your applications, jobs and containers.
2. Command-line tools: Hadoop provides various command-line tools to help you monitor and manage resource consumption in YARN. Some of the most important tools are "yarn top", "yarn logs" and "yarn node".
3. Cluster Manager: You can also use a cluster manager such as Apache Ambari or Cloudera Manager to monitor and manage YARN's resource consumption. These tools provide a centralized user interface that allows you to monitor resource consumption in real time and make various configuration changes to YARN.
4. Metrics system: Hadoop YARN also provides a metrics system that allows you to monitor metrics such as CPU utilization, memory usage, and network activity. You can then analyze these metrics to optimize the performance and resource consumption of your applications.

Overall, there are various ways to monitor and manage resource usage in Hadoop YARN. The choice of method depends on your specific needs and what type of information you need to optimize the performance of your applications.

How can you ensure your applications run on Hadoop YARN without impacting other applications?

What is the difference between Hadoop MapReduce and Hadoop YARN?

How can you ensure the availability of Hadoop YARN?

How can you improve Hadoop YARN performance?

How do you set up and configure Hadoop YARN on a clustered environment?

How can you ensure security in Hadoop YARN?

How can you determine if a specific job is running on Hadoop YARN?

How can you integrate Hadoop YARN with other big data technologies?