A Comparative Study on the Performance of the IB+&amp;nbsp;&lt;i&gt;Tree&lt;/i&gt;&amp;nbsp;and the I2B+&amp;nbsp;&lt;i&gt;Tree&lt;/i&gt;

Alexandre Valle De Carvalho,Edgar Carneiro,Marco Amaro Oliveira

doi:10.21601/jisem/11007

Abstract

Index structures were often used to optimise fetch operations to external storage devices (secondary memory). Nowadays, this also holds for increasingly large amounts of data residing in main-memory (primary memory). Within this scope, this work focuses on index structures that efficiently insert, query and delete valid-time data from very large datasets. This work performs a comparative study on the performance of the Interval B+ tree (IB+ tree) and the Improved Interval B+ tree (I2B+ tree): a variant that improves the time-efficiency of the deletion operation by reducing the number of traversed nodes to access siblings. We performed an extensive analysis of the performance of two operations: insertions and deletions, on both index structures, using multiple datasets with growing volumes of data, distinct temporal distributions and tree parameters (time-split alpha and node order). Results confirm that the I2B+ tree globally outperforms the IB+ tree, since, on average, deletion operations are 7% faster, despite insertions requiring 2% more time. Furthermore, results also allowed to determine the key factors that augment the performance difference on deletions between both trees.

Highlights

The classic performance analysis of index structures had its focus on disk access optimisation
As shown in the algorithms above, the IB+ tree method consists of a call to a recursive function that will repeat itself 2 ∗ (DDAA − DDNN), where DDAA − DDNN represents the number of depth levels between the common ancestor node (AA) and the node finding the sibling ( NN )
We studied the fundamental differences between the IB+ tree and the I2B + tree

Summary

INTRODUCTION

The classic performance analysis of index structures had its focus on disk access optimisation. Index structures are required by new and distinct application domains, usually involving large datasets, where high-speed access to information is mandatory In these new circumstances, evaluating disk access optimisation might no longer make sense, while the study of the performance of index structures as a function of the volume of data appears as a more adequate analysis. The cost of both primary and secondary memory storage space has been consistently decreasing, allowing larger amounts of data to be captured and stored (Liu & Yuan, 2019). Section Related Work summarises different structures for indexing valid-time information and presents an analysis of the IB+ tree.

RELATED WORK

EXPERIMENTS, RESULTS AND DISCUSSION

CONCLUSION