K. Langendoen, Brad Glasbergen, Khuzaima S. Daudjee
{"title":"NIR-Tree: A Non-Intersecting R-Tree","authors":"K. Langendoen, Brad Glasbergen, Khuzaima S. Daudjee","doi":"10.1145/3468791.3468818","DOIUrl":null,"url":null,"abstract":"Indexes for multidimensional data based on the R-Tree are popularly used by databases for a wide range of applications. Such index trees support point and range queries but are costly to construct over datasets of millions of points. We present the Non-Intersecting R-Tree (NIR-Tree), a novel insert-efficient, in-memory, multidimensional index that uses bounding polygons to provide efficient point and range query performance while indexing data at least an order of magnitude faster. The NIR-Tree leverages non-intersecting bounding polygons to reduce the number of nodes accessed during queries, compared to existing R-family indexes. Our experiments demonstrate that inserting into a NIR-Tree is 27 × faster than the ubiquitous R*-Tree, with point queries completing 2 × faster and range queries executing just as quickly.","PeriodicalId":312773,"journal":{"name":"33rd International Conference on Scientific and Statistical Database Management","volume":"112 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"33rd International Conference on Scientific and Statistical Database Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3468791.3468818","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Indexes for multidimensional data based on the R-Tree are popularly used by databases for a wide range of applications. Such index trees support point and range queries but are costly to construct over datasets of millions of points. We present the Non-Intersecting R-Tree (NIR-Tree), a novel insert-efficient, in-memory, multidimensional index that uses bounding polygons to provide efficient point and range query performance while indexing data at least an order of magnitude faster. The NIR-Tree leverages non-intersecting bounding polygons to reduce the number of nodes accessed during queries, compared to existing R-family indexes. Our experiments demonstrate that inserting into a NIR-Tree is 27 × faster than the ubiquitous R*-Tree, with point queries completing 2 × faster and range queries executing just as quickly.