On Graph Deltas for Historical Queries

TL;DR

This paper explores using graph deltas, logs of graph changes, to efficiently evaluate historical graph queries by reconstructing past snapshots and proposing algorithms for optimized performance.

Contribution

It introduces a storage model combining current graph snapshots with deltas and develops algorithms leveraging deltas for efficient historical query processing.

Findings

Efficient reconstruction of past graph snapshots using deltas.

Techniques like materializing snapshots and indexing deltas improve performance.

Algorithms based on deltas outperform traditional methods in query efficiency.

Abstract

In this paper, we address the problem of evaluating historical queries on graphs. To this end, we investigate the use of graph deltas, i.e., a log of time-annotated graph operations. Our storage model maintains the current graph snapshot and the delta. We reconstruct past snapshots by applying appropriate parts of the graph delta on the current snapshot. Query evaluation proceeds on the reconstructed snapshots but we also propose algorithms based mostly on deltas for efficiency. We introduce various techniques for improving performance, including materializing intermediate snapshots, partial reconstruction and indexing deltas.