• Shubham Mittal
• Manish Sharma

Implementation of the distribution system includes a number of issues during fault tolerance and synchronization. It directly affects the reliability of the system, as it becomes a complex task to process large data sets. It needs more number of machines. Big data computation requires numerous frameworks such as Spark, Storm, Dryad, MapReduce etc. for the execution of sensitive data. In recent years, Hadoop becomes quite trending due to its tremendous processing capacity. It is widely utilized for the number of tasks such as analysis of large-scale data, crunching web server log, to recommend systems and to construct the index information. A platform for real resource management named as thread permits to run number of structures along with the shared system. This paper depicts a novel fair allocation technique for cloud environment in order to process large volumes of data. However, due to unprinted asset allocation, there is a violation of numerous important features of shared computer systems. It results as the inadequate supply of yarn due to random policy assignments.

Cloud computing, Yarn, Hadoop, Frameworks, Fair Resource Allocation

"Big Data Allocation through Fair Resource Allocation in Cloud Computing", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.941-946, June 2019, Available :http://www.jetir.org/papers/JETIR1906U27.pdf

"Big Data Allocation through Fair Resource Allocation in Cloud Computing", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp941-946, June 2019, Available at : http://www.jetir.org/papers/JETIR1906U27.pdf