Enabling Active Data Archival over Cloud

Rajeev Gupta, H. Gupta, Ullas Nambiar, M. Mohania
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引用次数: 4

Abstract

The need to analyze huge amount of data for various business intelligence applications is well known. However, the rate at which enterprise data is generated now demands periodic migration of older data from the operational data warehouse to magnetic tapes. In this paper, we propose an "Active data archival service" in which the data is seamlessly archived on the cloud while ensuring that the archived data can be queried without any perceptible change to the end-user. This takes the burden of maintaining the archive off the user and shifts it to the archival service. We discuss the architecture of the service, challenges arising therein due to the federation of data brought on by the archival and how we handle these issues. Specifically, we investigate how the relational data needs to be transformed so that storing and retrieving the data from the cloud is efficient and seamless to the end user. We present our insights through an experimental study using TPC-DS benchmark.
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启用云上的活动数据归档
为各种商业智能应用程序分析大量数据的需求是众所周知的。但是,现在企业数据生成的速度要求定期将旧数据从操作数据仓库迁移到磁带。在本文中,我们提出了一种“主动数据归档服务”,该服务将数据无缝地归档到云上,同时确保最终用户可以在没有任何明显变化的情况下查询归档数据。这就减轻了用户维护档案的负担,并将其转移给了存档服务。我们将讨论服务的体系结构、由于存档带来的数据联合而产生的挑战,以及我们如何处理这些问题。具体来说,我们研究了需要如何转换关系数据,以便对最终用户有效且无缝地从云中存储和检索数据。我们通过使用TPC-DS基准的实验研究提出了我们的见解。
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