Yedalog:大规模探索知识

Brian Chin, D. V. Dincklage, V. Ercegovac, Peter Hawkins, Mark S. Miller, F. Och, Christopher Olston, Fernando C Pereira
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引用次数: 33

摘要

随着数据处理框架的巨大进步,在分析大型数据存储库时,人类程序员经常成为瓶颈。我们介绍Yedalog,一种声明式编程语言,它允许程序员在一种语言中无缝地混合数据并行管道和计算。相比之下,大多数现有的数据并行计算工具在通用语言中嵌入数据并行管道的子语言,反之亦然。Yedalog扩展了Datalog,不仅包含了逻辑编程的计算特性,还包含了处理作为嵌套记录结构的数据的特性。Yedalog程序既可以在单台机器上运行,也可以以批处理和交互模式分布在集群上,允许程序员轻松地混合不同的执行模式。1998 ACM学科分类D.3.2数据流语言、约束和逻辑语言
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Yedalog: Exploring Knowledge at Scale
With huge progress on data processing frameworks, human programmers are frequently the bottleneck when analyzing large repositories of data. We introduce Yedalog, a declarative programming language that allows programmers to mix data-parallel pipelines and computation seamlessly in a single language. By contrast, most existing tools for data-parallel computation embed a sublanguage of data-parallel pipelines in a general-purpose language, or vice versa. Yedalog extends Datalog, incorporating not only computational features from logic programming, but also features for working with data structured as nested records. Yedalog programs can run both on a single machine, and distributed across a cluster in batch and interactive modes, allowing programmers to mix dierent modes of execution easily. 1998 ACM Subject Classification D.3.2 Data-flow languages, Constraint and Logic Languages
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