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Space-efficient finger search on degree-balanced search trees

机译:度平衡搜索树上的空间有效手指搜索

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We show how to support the finger search operation on degree-balanced search trees in a space-efficient manner that retains a worst-case time bound of O(log d), where d is the difference in rank between successive search targets. While most existing tree-based designs allocate linear extra storage in the nodes (e.g., for side links and parent pointers), our design maintains a compact auxiliary data structure called the "hand" during the lifetime of the tree and imposes no other storage requirement within the tree.The hand requires O(log n) space for an n-node tree and has a relatively simple structure. It can be updated synchronously during insertions and deletions with time proportional to the number of structural changes in the tree. The auxiliary nature of the hand also makes it possible to introduce finger searches into any existing implementation without modifying the underlying data representation (e.g., any implementation of Red-Black trees can be used). Together these factors make finger searches more appealing in practice.Our design also yields a simple yet optimal in-order walk algorithm with worst-case O(1) work per increment (again without any extra storage requirement in the nodes), and we believe our algorithm can be used in database applications when the overall performance is very sensitive to retrieval latency.
机译:我们展示了如何以节省空间的方式在度数平衡的搜索树上支持手指搜索操作,该方法保留最坏情况下的时间范围 O (log d ),其中 d 是连续搜索目标之间的排名差异。尽管大多数现有的基于树的设计都在节点中分配了线性额外的存储空间(例如,用于边链接和父指针),但我们的设计在树的生命周期内维护了一个紧凑的辅助数据结构,称为“手”,并且强制使用 树中的其他存储需求。手需要一个 n 节点树的 O (log n )空间,并具有一个相对简单的结构。它可以在插入和删除期间同步更新,其时间与树中结构更改的数量成正比。手的辅助性质还可以将手指搜索引入到任何现有实现中而无需修改基础数据表示形式(例如,可以使用红黑树的任何实现)。这些因素加在一起使手指搜索在实践中更具吸引力。我们的设计还产生了一种简单而优化的有序行走算法,每增量递增最坏情况O (1)的工作量(同样无需在存储中添加任何额外的存储要求)节点),并且我们认为当整体性能对检索延迟非常敏感时,我们的算法可用于数据库应用程序。

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