DIBS: A Data Integration Benchmark Suite
DIBS: A Data Integration Benchmark Suite
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DIBS：数据集成基准套件
DOI：
10.1145/3185768.3186307
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
R. Chamberlain
中科院分区：
文献类型：
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作者：
A. Cabrera;Clayton J. Faber;Kyle Cepeda;Robert Derber;Cooper Epstein;Jason Zheng;R. Cytron;R. Chamberlain
随着数据的生成变得更加多产，对这些数据执行分析所需的时间和资源也会增加。然而，人们不太了解的是，在开始任何有意义的分析之前，必须应用数据预处理步骤。这种以某种初始形式获取数据并将其转换为所需形式的问题称为数据集成。在这里，我们介绍数据集成基准套件(DIBS)，这是一套代表多个学科的数据集成工作负载的应用程序。我们对这些应用程序进行了全面的描述，以更好地了解数据集成任务的一般行为。由于我们的基准测试套件和表征方法，我们提供了关于数据集成任务的见解，将指导其他研究人员在该领域设计解决方案。
As the generation of data becomes more prolific, the amount of time and resources necessary to perform analyses on these data increases. What is less understood, however, is the data preprocessing steps that must be applied before any meaningful analysis can begin. This problem of taking data in some initial form and transforming it into a desired one is known as data integration. Here, we introduce the Data Integration Benchmarking Suite (DIBS), a suite of applications that are representative of data integration workloads across many disciplines. We apply a comprehensive characterization to these applications to better understand the general behavior of data integration tasks. As a result of our benchmark suite and characterization methods, we offer insight regarding data integration tasks that will guide other researchers designing solutions in this area.