YARN MRv2 Framework
A YARN MRv2 Framework is a data processing cluster framework that is part of Hadoop v2.
- AKA: Yet Another Resource Negotiator, MRv2.
- Context:
- It can define a YARN Cluster Master (hosting a YARN ResourceManager).
- …
- Counter-Example(s):
- See: Parallel Iterative Algorithm, Cloudera Manager.
References
2015
- http://ci.apache.org/projects/flink/flink-docs-release-0.8.1/faq.html#is-flink-a-hadoop-project
- Flink is a data processing system and an alternative to Hadoop’s MapReduce component. It comes with its own runtime, rather than building on top of MapReduce. As such, it can work completely independently of the Hadoop ecosystem. However, Flink can also access Hadoop’s distributed file system (HDFS) to read and write data, and Hadoop’s next-generation resource manager (YARN) to provision cluster resources. Since most Flink users are using Hadoop HDFS to store their data, we ship already the required libraries to access HDFS.
2014
- http://hadoop.apache.org/docs/current/hadoop-yarn/hadoop-yarn-site/YARN.html
- MapReduce has undergone a complete overhaul in hadoop-0.23 and we now have, what we call, MapReduce 2.0 (MRv2) or YARN.
The fundamental idea of MRv2 is to split up the two major functionalities of the JobTracker, resource management and job scheduling/monitoring, into separate daemons. The idea is to have a global ResourceManager (RM) and per-application ApplicationMaster (AM). An application is either a single job in the classical sense of Map-Reduce jobs or a DAG of jobd.
The ResourceManager and per-node slave, the NodeManager (NM), form the data-computation framework. The ResourceManager is the ultimate authority that arbitrates resources among all the applications in the system.
The per-application ApplicationMaster is, in effect, a framework specific library and is tasked with negotiating resources from the ResourceManager and working with the NodeManager(s) to execute and monitor the tasks.
- MapReduce has undergone a complete overhaul in hadoop-0.23 and we now have, what we call, MapReduce 2.0 (MRv2) or YARN.
- http://hortonworks.com/hadoop/yarn/
- Part of the core Hadoop project, YARN is the architectural center of Hadoop that allows multiple data processing engines such as interactive SQL, real-time streaming, data science and batch processing to handle data stored in a single platform, unlocking an entirely new approach to analytics
- http://www.ibm.com/developerworks/library/bd-yarn-intro/
- … Apache Hadoop 2.0 includes YARN, which separates the resource management and processing components. The YARN-based architecture is not constrained to MapReduce. This article describes YARN and its advantages over the previous distributed processing layer in Hadoop. Learn how to enhance your clusters with YARN's scalability, efficiency, and flexibility.
- http://www.ibm.com/developerworks/library/bd-yarn-intro/Figure3Architecture-of-YARN.png
