What requests resources from YARN during a MapReduce job?ApplicationMasterApplicationsManagerMap and reduce tasksDataNodes
Question
What requests resources from YARN during a MapReduce job?ApplicationMasterApplicationsManagerMap and reduce tasksDataNodes
Solution
The ApplicationMaster is the component that requests resources from YARN during a MapReduce job. Here's a step-by-step explanation:
-
When a MapReduce job is submitted, the client first contacts the ResourceManager, which is the master daemon of YARN.
-
The ResourceManager then starts an ApplicationMaster for that job. The ApplicationMaster is a separate process that manages the lifecycle of the job and coordinates distributed execution.
-
The ApplicationMaster requests resources from the ResourceManager. These resources are in the form of containers, which are specific amounts of resource capacity on specific nodes.
-
Once the ApplicationMaster gets the necessary resources, it then communicates with the NodeManagers (slave daemons of YARN) on the allocated nodes to start the Map and Reduce tasks.
-
The Map and Reduce tasks process the data and the results are written back to the Hadoop Distributed File System (HDFS).
-
Once the job is completed, the ApplicationMaster deregisters with the ResourceManager and shuts down, returning its containers to the resource pool.
So, in summary, it's the ApplicationMaster that requests resources from YARN during a MapReduce job.
Similar Questions
Which Hadoop service is responsible for requesting resources for, and monitoring the completion of, MapReduce processes?Application MasterNameNodeDataNodeApplication Manager
Which component of Hadoop is responsible for job scheduling andresource management?Question 2Answera. HDFSb.MapReducec.YARNd. Pig
Which of the following about the MapReduce framework is/are correct?Question 7Select one or more:Select one or more:a.The MapReduce framework must be able to handle concurrent transactions, which are common in a distributed computing environment.b.The key/value pairs generated by map workers are directly sent to reduce workers as input.c.A reduce worker can only start a reduce task after all map workers finish their map tasks.d.A reduce worker may start a reduce task while some map workers are still running their map tasks.e.In the MapReduce framework, developers need to handle load balancing by writing code in the map and reduce functions.
What is MapReduce in the context of Big Data processing?Question 14Answera.A data visualization toolb.A data processing modelc.A data storage systemd.A data security protocol
Using hdfs dfs -get or hdfs dfs -cat, you can verify that the results of this program are exactly thesame as the results of the MapReduce WordCount example that we saw in the first assignment.Copy the logs of the MapReduce framework (the output that you get in your terminal after the yarncommand) to a text file. We will come back to this later.
Upgrade your grade with Knowee
Get personalized homework help. Review tough concepts in more detail, or go deeper into your topic by exploring other relevant questions.