MR2 and YARN Briefly Explained
- by Harsh Chouraria
- October 21, 2012
- 2 comments
With CDH4 onward, the Apache Hadoop component introduced two new terms for Hadoop users to wonder about: MR2 and YARN. Unfortunately, these terms are mixed up so much that many people are confused about them. Do they mean the same thing, or not?
This post aims to clarify these two terms.
What is YARN?
YARN stands for “Yet-Another-Resource-Negotiator”. It is a new framework that facilitates writing arbitrary distributed processing frameworks and applications.
YARN provides the daemons and APIs necessary to develop generic distributed applications of any kind, handles and schedules resource requests (such as memory and CPU) from such applications, and supervises their execution.
YARN’s execution model is more generic than the earlier MapReduce implementation. YARN can run applications that do not follow the MapReduce model, unlike the original Apache Hadoop MapReduce (also called MR1).
What is MR2?
With the advent of YARN, there is no longer a single JobTracker to run jobs and a TaskTracker to run tasks of the jobs. The old MR1 framework was rewritten to run within a submitted application on top of YARN. This application was christened MR2, or MapReduce version 2. It is the familiar MapReduce execution underneath, except that each job now controls its own destiny via its own ApplicationMaster taking care of execution flow (such as scheduling tasks, handling speculative execution and failures, etc.). It is a more isolated and scalable model than the MR1 system where a singular JobTracker does all the resource management, scheduling and task monitoring work.
MR2 and a new proof-of-concept application called the DistributedShell are the first two applications using the YARN API in CDH4.
YARN is a generic platform for any form of distributed application to run on, while MR2 is one such distributed application that runs the MapReduce framework on top of YARN. For a more extensive post on this topic, click here.