Testing Big Data Applications

N. Punn, Sonali Agarwal, M. Syafrullah, K. Adiyarta
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Abstract

Today big data has become the basis of discussion for the organizations. The big task associated with big data stream is coping with its various challenges and performing the appropriate testing for the optimal analysis of the data which may benefit the processing of various activities, especially from a business perspective. Big data term follows the massive volume of data, (might be in units of petabytes or exabytes) exceeding the processing and analytical capacity of the conventional systems and thereby raising the need for analyzing and testing the big data before applications can be put into use. Testing such huge data coming from the various number of sources like the internet, smartphones, audios, videos, media, etc. is a challenge itself. The most favourable solution to test big data follows the automated/programmed approach. This paper outlines the big data characteristics, and various challenges associated with it followed by the approach, strategy, and proposed framework for testing big data applications. Keywords—Big data, Testing, MapReduce, Hadoop.
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测试大数据应用
今天,大数据已经成为组织讨论的基础。与大数据流相关的重大任务是应对其各种挑战,并为数据的最佳分析执行适当的测试,这可能有利于各种活动的处理,特别是从业务角度来看。“大数据”一词指的是大量的数据(可能以pb或eb为单位)超过了传统系统的处理和分析能力,从而提出了在应用程序投入使用之前对大数据进行分析和测试的需求。测试来自互联网、智能手机、音频、视频、媒体等各种来源的海量数据本身就是一个挑战。测试大数据最有利的解决方案遵循自动化/编程方法。本文概述了大数据的特征,以及与之相关的各种挑战,然后是测试大数据应用的方法、策略和拟议框架。关键词:大数据,测试,MapReduce, Hadoop
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