Practical Aspects of Declarative Languages - 24th International Symposium, PADL 2022, Philadelphia, PA, USA, January 17-18, 2022, Proceedings
Practical Aspects of Declarative Languages - 24th International Symposium, PADL 2022, Philadelphia, PA, USA, January 17-18, 2022, Proceedings
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陈述性语言的实用方面 - 第 24 届国际研讨会，PADL 2022，美国宾夕法尼亚州费城，2022 年 1 月 17-18 日，会议记录
DOI：
10.1007/978-3-030-94479-7_6
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发表时间：
2022
期刊：
影响因子：
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通讯作者：
Evans R
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文献类型：
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作者：
Evans R
数据流应用程序（如机器学习算法）可以运行数天，因此需要确保它们能够正常工作。目前的工具还不够好：任务之间的交互往往不是类型安全的，导致不希望的运行时错误。本文提出了一种新的声明式Haskell嵌入式DSL（eDSL），用于Java编程：定义为对工作流中的依赖关系进行建模的数据上的对称Monoidal前序（SMP），它具有强大的数学基础，重新关注数据如何通过应用程序流动，从而产生更具表现力的解决方案，不仅静态捕获错误，而且还实现了具有竞争力的运行时性能。在我们的初步评估中，通过更好地扩展输入数量，它的表现优于业界领先的Spotify Luigi库。的创新性创建也值得注意，举例说明如何创建一个模块化的eDSL，其语义需要效果，以及存储程序正确性的复杂类型信息至关重要。
Dataflow applications, such as machine learning algorithms, can run for days, making it desirable to have assurances that they will work correctly. Current tools are not good enough: too often the interactions between tasks are not type-safe, leading to undesirable runtime errors. This paper presents a new declarative Haskell Embedded DSL (eDSL) for dataflow programming:. Defined as a Symmetric Monoidal Preorder (SMP) on data that models dependencies in the workflow, it has a strong mathematical basis, refocusing on how data flows through an application, resulting in a more expressive solution that not only catches errors statically, but also achieves competitive run-time performance. In our preliminary evaluation,outperforms the industry-leading Luigi library of Spotify by scaling better with the number of inputs. The innovative creation ofis also of note, exemplifying how to create a modular eDSL whose semantics necessitates effects, and where storing complex type information for program correctness is paramount.