NoSQL vs. SQL – What is Better?
17th February 2020
What is Blockchain Technology?
20th February 2020
YARN is an acronym for Yet Another Resource Negotiator. It is a cluster management technology that became part of Hadoop 2.0, significantly increasing the potential uses of Apache Hadoop.
What is Hadoop YARN?
YARN is one of the core components of the open-source Apache Haddop distributed processing frameworks which helps in job scheduling of various applications and resource management in the cluster. YARN was initially called ‘MapReduce 2’ since it took the original MapReduce to another level by giving new and better approaches for decoupling MapReduce resource management for scheduling capabilities from the data processing unit.
YARN is being extensively used for writing applications by Hadoop Developers. It lets them create applications, work with huge amounts of data, and manipulate them in an efficient manner. YARN is much more effective and versatile than Hadoop MapReduce, and this is exactly what is required in a world inundated with big data. However, it will remain the most sought-after tool until the perennial search—for a tool that works well in the challenging environment of Big Data Hadoop—comes up with a new befitting tool.
Why YARN?
In spite of being thoroughly proficient at data processing and computations, Hadoop had some shortcomings like delays in batch processing, scalability issues, etc. as it relied on MapReduce for processing big datasets. With YARN, Hadoop is now able to support a variety of processing approaches and has a larger array of applications. Hadoop YARN clusters are now able to run stream data processing and interactive querying side by side with MapReduce batch jobs. YARN framework runs even the non-MapReduce applications, thus overcoming the shortcomings of Hadoop 1.0.
Advantages of YARN
The architecture of YARN ensures that the Hadoop cluster can be enhanced in the following ways:
- Multi-tenancy
YARN lets you access various proprietary and open-source engines for deploying Hadoop as a standard for real-time, interactive, and batch processing tasks that are able to access the same dataset and parse it.
- Cluster Utilization
YARN lets you use the Hadoop cluster in a dynamic way, rather than in a static manner by which MapReduce applications were using it, and this is a better and optimized way of utilizing the cluster.
- Scalability
YARN gives the power of scalability to the Hadoop cluster. YARN ResourceManager (RM) service is the central controlling authority for resource management and it makes allocation decisions.
- Compatibility
YARN tool is highly compatible with the existing Hadoop MapReduce applications, and thus those projects that are working with MapReduce in Hadoop 1.0 can easily move on to Hadoop 2.0 with YARN without any difficulty, ensuring complete compatibility.
