Software engineering issues in big data application development

Z. Karakaya
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引用次数: 9

Abstract

Big Data has become one of the most important concepts that is being studied in Computer/Software Engineering. The data produced in recent years have increased rapidly and exponentially, necessitating the solution of major problems such as the collection, processing and storage of huge volume of data. Big Data Frameworks are developed specifically to solve these problems that facilitates application developers by providing opportunities to collect, process, manage, monitor and analyze these data. A few examples of these frameworks are Hadoop, Spark, Storm, and Flink, which are developed by Software Engineers as open source projects. Although the challenges raised from coordination of IT resources such as huge amounts of computation power, storage area, memory, and network bandwidth in a distributed manner solved by these frameworks, there still remains many Software Engineering problems in application development phase, even if they based on these frameworks. High scalability, fault tolerance, flexibility, reliability and testability can be listed as the main issues need to be carefully considered in terms of Software Engineering. In this paper, we first clarify the terms Framework-Application, and then the overview information about Big Data and related frameworks are given before emphasizing the problems arising in terms of Software Engineering. Nevertheless, we tried to provide guidance to the people who would develop software for Big Data and tried to give the further research guidance.
大数据应用开发中的软件工程问题
大数据已经成为计算机/软件工程研究中最重要的概念之一。近年来产生的数据呈指数级快速增长,需要解决大量数据的收集、处理和存储等重大问题。大数据框架是专门为解决这些问题而开发的,它为应用程序开发人员提供了收集、处理、管理、监控和分析这些数据的机会。这些框架的一些例子是Hadoop、Spark、Storm和Flink,它们是由软件工程师作为开源项目开发的。尽管这些框架解决了大量计算能力、存储区域、内存和分布式网络带宽等IT资源协调带来的挑战,但在应用程序开发阶段仍然存在许多软件工程问题,即使这些问题是基于这些框架的。高可扩展性、容错性、灵活性、可靠性和可测试性是软件工程中需要仔细考虑的主要问题。本文首先对“框架-应用”这两个术语进行了澄清,然后对大数据及其相关框架进行了概述,然后重点介绍了软件工程方面出现的问题。尽管如此,我们还是试图为大数据开发软件的人提供指导,并试图给予进一步的研究指导。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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