Graph query processing

Semih Salihoglu; N. Yakovets

doi:10.1007/978-3-319-77525-8_215

Graph query processing

Semih Salihoglu, N. Yakovets

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Abstract

While being eminently useful in a wide variety of application domains, the high expressiveness of graph queries makes them hard to optimize and, hence, challenging to process efficiently. We discuss a number of state-of-the-art approaches which aim to overcome these challenges, focusing specifically on planning, optimization, and execution of two commonly used types of declarative graph queries: subgraph queries and regular path queries.

Original language	English
Title of host publication	Encyclopedia of Big Data Technologies
Editors	Sherif Sakr, Albert Y. Zomaya
Place of Publication	Berlin
Publisher	Springer
Pages	890-898
Number of pages	9
ISBN (Electronic)	978-3-319-77525-8
ISBN (Print)	978-3-319-77524-1
DOIs	https://doi.org/10.1007/978-3-319-77525-8_215
Publication status	Published - 20 Feb 2019

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title = "Graph query processing",

abstract = "While being eminently useful in a wide variety of application domains, the high expressiveness of graph queries makes them hard to optimize and, hence, challenging to process efficiently. We discuss a number of state-of-the-art approaches which aim to overcome these challenges, focusing specifically on planning, optimization, and execution of two commonly used types of declarative graph queries: subgraph queries and regular path queries.",

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AB - While being eminently useful in a wide variety of application domains, the high expressiveness of graph queries makes them hard to optimize and, hence, challenging to process efficiently. We discuss a number of state-of-the-art approaches which aim to overcome these challenges, focusing specifically on planning, optimization, and execution of two commonly used types of declarative graph queries: subgraph queries and regular path queries.

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BT - Encyclopedia of Big Data Technologies

A2 - Sakr, Sherif

A2 - Zomaya, Albert Y.

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Graph query processing

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