R-tree index merging updating method and device based on Hilbert curve and medium

Abstract

The invention discloses an R-tree index merging updating method and device based on a Hilbert curve and a medium. The method comprises the steps of S1, acquiringa first R tree to be combined and a second R tree to be inserted into the first R tree, wherein the upper limit range and the lower limit range of Hilbert values of contained objects are stored in non-leaf nodes of the R trees; s2, querying a to-be-inserted node of each merged leaf node in the first R leaf sub-node layer in the second R leaf sub-node layer through a hierarchical query algorithm from top to bottom; s3, according to a hierarchical adjustment algorithm from bottom to top, for each leaf node in the first R tree, inserting space objects contained in the leaf node into the to-be-inserted nodes determined in the S2 according to a Hilbert value sequence, and realizing the combination of the two R trees; and S4, for the combined second R tree, updating the storage information in each node layer by layer according to a sequence from the leaf node to the root node. The method has important practical application value in the field of high-performance storage of geographic space-time big data.

Description

Technical field[0001]The present invention relates to the technical field of data retrieval and update, in particular to a merge update technology of Hilbert R-tree index.Background technique[0002]The update frequency of spatial data is gradually increasing with the development of geographic information data collection equipment. The management of spatial data must not only meet the demand for efficient query, but also need to take into account the demand for rapid update. The spatial index combined with the LSM tree structure can effectively support the demand for frequent insertion and update of spatial data. Among them, the LSM R tree index has better universality and stability than the DBH tree, DHVB tree and SHB tree. However, the actual application of the LSM R tree often involves a large number of R tree merging operations. The R tree merging process will occupy a certain amount of memory and computing resources of the system, affecting the query, insertion, and deletion of t...

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Problems solved by technology

However, the actual application of LSM R trees often involves the merging of a large number of R trees. During the merging process, the R trees will occupy a certain amount of memory and computing resources in the system, which will affect the query, insertion, and deletion of indexes during this period. Efficiency of other operations

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