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The DataPath System: A Data-Centric Analytic Processing Engine for Large Data Warehouses

机译:DataPath系统:用于大型数据仓库的数据以数据为中心的分析处理引擎

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Since the 1970's, database systems have been "compute-centric". When a computation needs the data, it requests the data, and the data are pulled through the system. We believe that this is problematic for two reasons. First, requests for data naturally incur high latency as the data are pulled through the memory hierarchy, and second, it makes it difficult or impossible for multiple queries or operations that are interested in the same data to amortize the bandwidth and latency costs associated with their data access. In this paper, we describe a purely-push based, research prototype database system called DataPath. DataPath is "data-centric". In DataPath, queries do not request data. Instead, data are automatically pushed onto processors, where they are then processed by any interested computation. We show experimentally on a multi-terabyte benchmark that this basic design principle makes for a very lean and fast database system.
机译:自1970年代以来,数据库系统已被“Compute”。当计算需要数据时,它请求数据,并通过系统拉动数据。我们认为这是有问题的两个原因。首先,对数据的数据请求自然会引起高延迟,因为数据被拉出存储层次结构,而第二个,它使得对对相同数据感兴趣的多个查询或操作难以或不可能进行摊销与其相关联的带宽和延迟成本的多个查询或操作数据访问。在本文中,我们描述了一种基于纯粹的推动的研究原型数据库系统,称为DataPath。数据路径是“以数据为中心”。在DataPath中,查询不请求数据。相反,数据会自动推动到处理器上,然后通过任何感兴趣的计算处理它们。我们在实验上显示了这种基本设计原理的多Terabyte基准,为一个非常精瘦和快速的数据库系统提供。

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