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首页> 外文期刊>Journal of Computer Sciences and Applications >Emergence of Big Data on Cloud Computing (An Insight to Current and Future)
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Emergence of Big Data on Cloud Computing (An Insight to Current and Future)

机译:云计算大数据的出现(对当前和未来的洞察)

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In Database the prime objective of database is to arrange the data in a well designed manner so that the data should be stored and retrieved effectively as and when required. But in traditional database like DBMS the major fault was scalability. So in this database management systems (DBMS) the following problems are arise always such as, 1. Update intensive application workloads, and 2. Decision support systems for descriptive and deep analytics. These are a critical part of the cloud infrastructure and play an important role in ensuring the smooth transition of applications from the traditional enterprise infrastructures to next generation cloud infrastructures. So these scalability natures of the data base cause a lot of problem for data integration when the amounts of data were huge. This paper presents an organized picture of the challenges faced by application developers and DBMS designers in developing and deploying internet scale applications. We have designed this paper on the basis of the following aspects, such as: (i) For supporting update heavy applications, and (ii) For ad-hoc analytics and decision support. Here we also focus on providing an in-depth analysis of systems for supporting update intensive web-applications which are mostly now a day’s used in the companies and provide a survey of the state-of-the art in this domain. We have tried to crystallize the design aspect of choices made by considering some large scale database management systems, analyze the application demands and access patterns, and enumerate the desiderata for a cloud-bound DBMS.
机译:在数据库中,数据库的主要目的是以合理设计的方式排列数据,以便应在需要时有效地存储和检索数据。但是在像DBMS这样的传统数据库中,主要的缺点是可伸缩性。因此,在此数据库管理系统(DBMS)中,总是会出现以下问题,例如:1.更新密集的应用程序工作负载,以及2.用于描述性和深度分析的决策支持系统。这些是云基础架构的关键部分,并在确保应用程序从传统企业基础架构到下一代云基础架构的平稳过渡中发挥重要作用。因此,当数据量巨大时,数据库的这些可伸缩性会给数据集成带来很多问题。本文以系统的方式呈现了应用程序开发人员和DBMS设计师在开发和部署Internet规模应用程序时面临的挑战。我们基于以下方面设计了本文,例如:(i)用于支持更新繁重的应用程序,以及(ii)用于临时分析和决策支持。在这里,我们还着重于对支持更新密集型Web应用程序的系统进行深入分析,这些应用程序现在在公司中每天都在使用,并提供了该领域的最新技术概览。我们试图通过考虑一些大型数据库管理系统来明确选择的设计方面,分析应用程序需求和访问模式,并列举针对云绑定DBMS的需求。

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