Factorized Databases

Dan Olteanu, Maximilian Schleich
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引用次数: 82

Abstract

This paper overviews factorized databases and their application to machine learning. The key observation underlying this work is that state-of-the-art relational query processing entails a high degree of redundancy in the computation and representation of query results. This redundancy can be avoided and is not necessary for subsequent analytics such as learning regression models.
映像数据库
本文综述了分解数据库及其在机器学习中的应用。这项工作的关键观察结果是,最先进的关系查询处理在查询结果的计算和表示中需要高度冗余。这种冗余是可以避免的,并且对于诸如学习回归模型之类的后续分析来说是不必要的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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