基于栅格的R树更新缓存与批处理机制

R-tree Updating Caching and Batch Processing Mechanism Based on Gird

根据对象分布相对稳定的特点,选择与固定栅格对应的、代表对象分布情况的部分叶子节点作为容纳新记录的种子节点,新记录可直接与种子节点合并而无须遍历R树。随机选择部分无法合并的记录作为种子记录,对活动记录进行简单有效的分组,以插入种子记录的代价实现批量插入。上述2种方法考虑了R树的空间聚簇特性,可在一次更新中完成多项插入与删除,减少了对节点的写操作及对R树的遍历次数。实验证明,该机制在降低索引维护I/O开销的同时保证了查询效率。

According to the relative stability of objects＇ distribution and based on fixed grids, some leaf nodes representing the distribution of objects are selected as seed-nodes for new records to directly merge new records into seed-nodes without traversing R-tree. Some records which can not be merged into seed-nodes are chosen randomly as seed-records. Such records are grouped simply but effectively, so that they can be inserted into R-tree with the cost of inserting seed-nodes. The strategies pay attention to R-tree＇s spatial clustering, and perform multiple inserting and deleting in one write-operation, decreasing the demand of writing and traversing R-tree. Experiments show that the strategies reduce the I/O cost of R-tree maintaining without affecting the query performance.