{"title":"鲁棒的多属性搜索结构","authors":"D. Lomet, B. Salzberg","doi":"10.1109/ICDE.1989.47229","DOIUrl":null,"url":null,"abstract":"A multiattribute index structure called the hB-tree is introduced. The hB-tree internode search and growth processes are precisely analogous to the corresponding processes in B-trees. The intranode processes are unique. A k-d tree is used as the structure within nodes for very efficient searching. Node splitting requires that this k-d tree be split. This produces nodes which do not represent brick-like regions in k-space but that can be characterized as holey bricks, i.e. bricks in which subregions have been extracted. Results are presented that guarantee hB-tree users decent storage utilization, reasonable-size index terms, and good search and insert performance regardless of key distribution.<<ETX>>","PeriodicalId":329505,"journal":{"name":"[1989] Proceedings. Fifth International Conference on Data Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1989-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"66","resultStr":"{\"title\":\"A robust multi-attribute search structure\",\"authors\":\"D. Lomet, B. Salzberg\",\"doi\":\"10.1109/ICDE.1989.47229\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A multiattribute index structure called the hB-tree is introduced. The hB-tree internode search and growth processes are precisely analogous to the corresponding processes in B-trees. The intranode processes are unique. A k-d tree is used as the structure within nodes for very efficient searching. Node splitting requires that this k-d tree be split. This produces nodes which do not represent brick-like regions in k-space but that can be characterized as holey bricks, i.e. bricks in which subregions have been extracted. Results are presented that guarantee hB-tree users decent storage utilization, reasonable-size index terms, and good search and insert performance regardless of key distribution.<<ETX>>\",\"PeriodicalId\":329505,\"journal\":{\"name\":\"[1989] Proceedings. Fifth International Conference on Data Engineering\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1989-02-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"66\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[1989] Proceedings. Fifth International Conference on Data Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDE.1989.47229\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1989] Proceedings. Fifth International Conference on Data Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDE.1989.47229","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A multiattribute index structure called the hB-tree is introduced. The hB-tree internode search and growth processes are precisely analogous to the corresponding processes in B-trees. The intranode processes are unique. A k-d tree is used as the structure within nodes for very efficient searching. Node splitting requires that this k-d tree be split. This produces nodes which do not represent brick-like regions in k-space but that can be characterized as holey bricks, i.e. bricks in which subregions have been extracted. Results are presented that guarantee hB-tree users decent storage utilization, reasonable-size index terms, and good search and insert performance regardless of key distribution.<>