Year: 2004
Type: preprint
Abstract: In a variety of applications, we need to keep track of the development of a data set over time. For maintaining and querying this multi version data I/O-efficiently, external memory data structures are required. In this paper, we present a probabilistic self-balancing persistent data structure in external memory called the persistent buffer tree, which supports insertions, updates and deletions of data items at the present version and range queries for any version, past or present. The persistent buffer tree is I/O-optimal in the sense that the expected amortized I/O performance bounds are asymptotically the same as the deterministic amortized bounds of the (single version) buffer tree in the worst case.
Source: arXiv (Cornell University)
Authors: Dominic, Saju Jude, Sajith, G.
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W1659673178