标题： 机器学习的数据虚拟化 显示英文标题

标题： Data Virtualization for Machine Learning

摘要： 如今，机器学习（ML）团队有多个并行的ML工作流用于不同的应用。 每个工作流通常涉及许多实验、迭代和协作活动，并且从初始的数据处理到模型部署通常需要几个月甚至几年的时间。 在组织层面，有大量的中间数据需要存储、处理和维护。 \emph{数据虚拟化}成为服务于ML工作流的基础设施中的关键技术。 在本文中，我们介绍了数据虚拟化服务的设计和实现，重点在于其服务架构和服务操作。 该基础设施目前支持六个ML应用，每个应用都有多个ML工作流。 数据虚拟化服务允许在未来几年内增加应用和工作流的数量。 显示英文摘要

摘要： Nowadays, machine learning (ML) teams have multiple concurrent ML workflows for different applications. Each workflow typically involves many experiments, iterations, and collaborative activities and commonly takes months and sometimes years from initial data wrangling to model deployment. Organizationally, there is a large amount of intermediate data to be stored, processed, and maintained. \emph{Data virtualization} becomes a critical technology in an infrastructure to serve ML workflows. In this paper, we present the design and implementation of a data virtualization service, focusing on its service architecture and service operations. The infrastructure currently supports six ML applications, each with more than one ML workflow. The data virtualization service allows the number of applications and workflows to grow in the coming years.