Arkouda: interactive data exploration backed by Chapel
Arkouda: interactive data exploration backed by Chapel
复制标题
Arkouda：Chapel 支持的交互式数据探索
DOI：
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
Timothy Neumann
中科院分区：
文献类型：
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作者：
M. Merrill;William Reus;Timothy Neumann
探索性数据分析（EDA）是所有数据科学的先决条件。EDA是不可协商的交互式的--到目前为止，EDA最流行的环境是一个100字节的笔记本--而且，随着数据集的增长，计算强度也越来越大。现有的几个项目试图结合联合收割机的交互性和分布式计算使用编程范例和工具，从云计算，但这些项目都没有接近满足我们的高性能EDA的需求。为了填补这一空白，我们开发了一个原型，称为arkouda，它允许用户交互式地发布分布式数据上的大规模并行计算。
Exploratory data analysis (EDA) is the prerequisite for all data science. EDA is non-negotiably interactive—by far the most popular environment for EDA is a Jupyter notebook—and, as datasets grow, increasingly computationally intensive. Several existing projects attempt to combine interactivity and distributed computation using programming paradigms and tools from cloud computing, but none of these projects have come close to meeting our needs for high-performance EDA. To fill this gap, we have developed a prototype, called arkouda, that allows a user to interactively issue massively parallel computations on distributed data.