• shaffy girdher

The main focus of this paper is to compare the performance between Hadoop and Spark on some applications, such as iterative computation and real-time data processing. The runtime architectures of both Spark and Hadoop will be compared to illustrate their differences, and the components of their ecosystems will be tabled to show their respective characteristics. In this paper, we will highlight the performance comparison between Spark and Hadoop as the growth of data size and iteration counts, and also show how to tune in Hadoop and Spark in order to achieve higher performance. and how to verify the correctness of the running results. Inthis chapter, an overview of Hadoop and Spark is introduced to get a basic understanding of their frameworks, including their key component sand how data flows in MapReduce and Spark respectively. Next, their runtime architectures are dissected to better comprehend how an application works in Hadoop and Spark separately.In addition, their ecosystems are illustrated to show the characteristic and functionality of each element.

"A Review On Spark VS Hadoop which is better for Big Data Analytics", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.363-368, June 2019, Available :http://www.jetir.org/papers/JETIR1907O45.pdf

"A Review On Spark VS Hadoop which is better for Big Data Analytics", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp363-368, June 2019, Available at : http://www.jetir.org/papers/JETIR1907O45.pdf