ACM Transactions on Database Systems · 1990 · 277 citations · 16 references
Cluster ComputingEngineeringBig Data IndexingStorage StructureHb-tree CopesInformation RetrievalData ScienceData MiningK-d TreeKeyvalue DatabaseData IntegrationParallel ComputingCombinatorial OptimizationData ManagementHb-tree Internode SearchKnowledge DiscoveryComputer EngineeringText IndexingComputer ScienceData IndexingGood Guaranteed PerformanceParallel ProgrammingSearch Engine IndexingIndexing TechniqueBig Data
A new multiattribute index structure called the hB-tree is introduced. It is derived from the K-D-B-tree of Robinson [15] but has additional desirable properties. The hB-tree internode search and growth processes are precisely analogous to the corresponding processes in B-trees [1]. 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 This produces nodes which no longer represent brick-like regions in k-space, but that can be characterized as holey bricks, bricks in which subregions have been extracted. We present results that guarantee hB-tree users decent storage utilization, reasonable size index terms, and good search and insert performance. These results guarantee that the hB-tree copes well with arbitrary distributions of keys.
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J. Nievergelt, Hans Hinterberger, Kenneth C. Sevcik · ACM Transactions on Database Systems · 1984 · 1.1K citations · Full text
John T. Robinson · 1981 · 885 citations · Full text