NDLI: High performance risk aggregation: addressing the data processing challenge the hadoop mapreduce way

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High performance risk aggregation: addressing the data processing challenge the hadoop mapreduce way

High performance risk aggregation: addressing the data processing challenge the hadoop mapreduce way

Content Provider	ACM Digital Library
Author	Rau-Chaplin, Andrew Varghese, Blesson Yao, Zhimin
Abstract	Monte Carlo simulations employed for the analysis of portfolios of catastrophic risk process large volumes of data. Often times these simulations are not performed in real-time scenarios as they are slow and consume large data. Such simulations can benefit from a framework that exploits parallelism for addressing the computational challenge and facilitates a distributed file system for addressing the data challenge. To this end, the Apache Hadoop framework is chosen for the simulation reported in this paper so that the computational challenge can be tackled using the MapReduce model and the data challenge can be addressed using the Hadoop Distributed File System. A parallel algorithm for the analysis of aggregate risk is proposed and implemented using the MapReduce model in this paper. An evaluation of the performance of the algorithm indicates that the Hadoop MapReduce model offers a framework for processing large data in aggregate risk analysis. A simulation of aggregate risk employing 100,000 trials with 1000 catastrophic events per trial on a typical exposure set and contract structure is performed on multiple worker nodes in less than 6 minutes. The result indicates the scope and feasibility of MapReduce for tackling the computational and data challenge in the analysis of aggregate risk for real-time use.
Starting Page	53
Ending Page	60
Page Count	8
File Format	PDF
ISBN	9781450319799
DOI	10.1145/2465848.2465853
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2013-06-17
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Hadoop mapreduce High-performance analytics Data processing Risk aggregation Risk analysis
Content Type	Text
Resource Type	Article

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