تقرير
Towards Practical Learned Indexing
| العنوان: | Towards Practical Learned Indexing |
|---|---|
| المؤلفون: | Stoian, Mihail, Kipf, Andreas, Marcus, Ryan, Kraska, Tim |
| سنة النشر: | 2021 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Databases, Computer Science - Machine Learning |
| الوصف: | Latest research proposes to replace existing index structures with learned models. However, current learned indexes tend to have many hyperparameters, often do not provide any error guarantees, and are expensive to build. We introduce Practical Learned Index (PLEX). PLEX only has a single hyperparameter $\epsilon$ (maximum prediction error) and offers a better trade-off between build and lookup time than state-of-the-art approaches. Similar to RadixSpline, PLEX consists of a spline and a (multi-level) radix layer. It first builds a spline satisfying the given $\epsilon$ and then performs an ad-hoc analysis of the distribution of spline points to quickly tune the radix layer. Comment: 3rd International Workshop on Applied AI for Database Systems and Applications (AIDB'21), August 20, 2021, Copenhagen, Denmark |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2108.05117 |
| رقم الأكسشن: | edsarx.2108.05117 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |