Graph query processing

Semih Salihoglu, N. Yakovets

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

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.
LanguageEnglish
Title of host publicationEncyclopedia of Big Data Technologies
EditorsSherif Sakr, Albert Y. Zomaya
Place of PublicationBerlin
PublisherSpringer
Pages890-898
Number of pages9
ISBN (Electronic)978-3-319-77525-8
ISBN (Print)978-3-319-77524-1
DOIs
StatePublished - 20 Feb 2019

Fingerprint

Query processing
Planning

Cite this

Salihoglu, S., & Yakovets, N. (2019). Graph query processing. In S. Sakr, & A. Y. Zomaya (Eds.), Encyclopedia of Big Data Technologies (pp. 890-898). Berlin: Springer. DOI: 10.1007/978-3-319-77525-8_215
Salihoglu, Semih ; Yakovets, N./ Graph query processing. Encyclopedia of Big Data Technologies. editor / Sherif Sakr ; Albert Y. Zomaya. Berlin : Springer, 2019. pp. 890-898
@inbook{55606c9a305a44b6aa884490fdff5c33,
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.",
author = "Semih Salihoglu and N. Yakovets",
year = "2019",
month = "2",
day = "20",
doi = "10.1007/978-3-319-77525-8_215",
language = "English",
isbn = "978-3-319-77524-1",
pages = "890--898",
editor = "Sherif Sakr and Zomaya, {Albert Y.}",
booktitle = "Encyclopedia of Big Data Technologies",
publisher = "Springer",
address = "Germany",

}

Salihoglu, S & Yakovets, N 2019, Graph query processing. in S Sakr & AY Zomaya (eds), Encyclopedia of Big Data Technologies. Springer, Berlin, pp. 890-898. DOI: 10.1007/978-3-319-77525-8_215

Graph query processing. / Salihoglu, Semih; Yakovets, N.

Encyclopedia of Big Data Technologies. ed. / Sherif Sakr; Albert Y. Zomaya. Berlin : Springer, 2019. p. 890-898.

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

TY - CHAP

T1 - Graph query processing

AU - Salihoglu,Semih

AU - Yakovets,N.

PY - 2019/2/20

Y1 - 2019/2/20

N2 - 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.

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.

U2 - 10.1007/978-3-319-77525-8_215

DO - 10.1007/978-3-319-77525-8_215

M3 - Chapter

SN - 978-3-319-77524-1

SP - 890

EP - 898

BT - Encyclopedia of Big Data Technologies

PB - Springer

CY - Berlin

ER -

Salihoglu S, Yakovets N. Graph query processing. In Sakr S, Zomaya AY, editors, Encyclopedia of Big Data Technologies. Berlin: Springer. 2019. p. 890-898. Available from, DOI: 10.1007/978-3-319-77525-8_215