Array Database Scalability: Intercontinental Queries on Petabyte Datasets

A. Dumitru, Vlad Merticariu, P. Baumann
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引用次数: 11

Abstract

With the deluge of scientific big data affecting a large variety of research institutions, support for large multidimensional arrays has gained traction in the database community in the past decade. Array databases aim to cover the gap left by traditional relational database systems in the domains of large scientific data by enabling researchers to efficiently store and process their data through rich declarative query languages. Such large amounts of data need effective systems that are able to distribute the processing at both local level, through exploitation of heterogeneous hardware as well as at network level, enabling both intra-cloud and intra-federation distribution of data and processing. In this demonstration we aim to showcase the capabilities of rasdaman by allowing users to execute queries that combine petabyte datasets stored at two institutions on different continents.
阵列数据库可扩展性:对pb数据集的洲际查询
随着科学大数据的泛滥影响了各种各样的研究机构,对大型多维数组的支持在过去十年中在数据库社区中获得了牵引力。阵列数据库旨在填补传统关系数据库系统在大型科学数据领域的空白,使研究人员能够通过丰富的声明性查询语言有效地存储和处理数据。如此大量的数据需要有效的系统,这些系统能够通过利用异构硬件在本地级别和网络级别分发处理,从而实现云内部和联邦内部的数据和处理分发。在这个演示中,我们的目标是通过允许用户执行将存储在不同大洲的两个机构的pb数据集组合在一起的查询,来展示rasdaman的功能。
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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