大数据测试技术对比分析

Adiba Abidin, D. Lal, Naveen Garg, V. Deep
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引用次数: 8

摘要

大数据是最近讨论的一个大话题。从报纸到技术杂志,从社交媒体到期刊,它通常无处不在。大数据是指复杂的数据集,其规模在预期的时间跨度内超出了传统处理技术的能力。大数据包含大量的数据,可能是pb或Exabyte的数据,由数百万人的数十亿到数万亿的记录组成。测试如此庞大的数据量是一个巨大的挑战。随着社交媒体、云和智能手机的出现,各行业不得不处理海量数据。大数据为复杂的商业问题提供了解决方案,海量数据的分析为更快更好的决策提供了基础,同时也为客户开发了新的产品和服务[4]。本文着重于已经实现的各种技术。
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Comparative analysis on techniques for big data testing
Big data is a big affair of discussion these days. It is usually used everywhere from newspaper to technical magazines from social media to journals. The term big data refers to complex data sets whose size is beyond the ability of traditional processing techniques within a desired span of time. Big data consists of large volume that might be petabytes or Exabyte's of data consisting of billions to trillions of records of millions of people. Testing of this huge volume of data is a big challenge. With the emergence of social media, cloud and smart phones, industries have to deal with the voluminous data. while big data provide solutions to complex business problems like analysis of huge data serves as a basis for faster and better decision making, new products and services are being developed for the customers[4]. This paper focuses on the various techniques that have been implemented.
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