跨越大数据：使用Grasshopper算法加速Ad-hoc OLAP搜索
Hopping over Big Data: Accelerating Ad-hoc OLAP Queries with Grasshopper Algorithms
摘要：
本文提出了一个快速子集过滤算法族内的整数表示的组合键的有序集。应用程序包括针对数据仓库的（ad-hoc）分析查询的显著加速，而无需任何额外的索引。该算法适用于多个属性的点、范围和集合限制，可以任意组合，并且本质上是多维的。其主要思想是将顺序爬行与跳过大部分不相关的键相结合。组合它们的方式是自适应的基础数据存储的特征。
英文摘要：
This paper presents a family of algorithms for fast subset filtering within ordered sets of integers representing composite keys. Applications include significant acceleration of (ad-hoc) analytic queries against a data warehouse without any additional indexing. The algorithms work for point, range and set restrictions on multiple attributes, in any combination, and are inherently multidimensional. The main idea consists in intelligent combination of sequential crawling with jumps over large portions of irrelevant keys. The way to combine them is adaptive to characteristics of the underlying data store.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
