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An Overview of Reachability Indexes on Graphs

Authors: Zhang, Chao; Bonifati, Angela; Özsu, M. Tamer;

An Overview of Reachability Indexes on Graphs

Abstract

Graphs have been the natural choice for modeling entities and the relationships among them. One of the most fundamental graph processing operators is a reachability query, which checks whether a path exists from the source to the target vertex in a plain graph, and additionally whether the path can satisfy a given path constraint based on the edge labels in an edge-labeled graph. Processing reachability queries requires potentially visiting a large portion of the graph due to the inherent transitivity of these queries. This makes it costly to evaluate them on large graphs. Thus, significant effort has been spent to design indexing techniques for reachability queries in the last three decades, building advanced data structures to efficiently compress the transitive closure of the graph so as to accelerate online query processing, aka reachability indexes. In this tutorial, we provide an in-depth technical review of the existing reachability indexes, ranging from those designed for plain graphs to ones for edge-labeled graphs. We conclude the tutorial by summarizing the open challenges for integrating these techniques into GDBMSs.

Country
France
Keywords

Database query processing graph database, Data structures, reachability index, • Information systems → Graph-based database models, • Information systems → Graph-based database models Data structures Database query processing graph database reachability query reachability index, [INFO] Computer Science [cs], reachability query

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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
12
Top 10%
Average
Top 10%
Green