The University of Southampton
University of Southampton Institutional Repository

基于二级索引结构的图压缩算法

基于二级索引结构的图压缩算法
基于二级索引结构的图压缩算法

The demand for the analysis and application of graph data in various fields is increasing day by day. The management of large-scale graph data with complicated structure and high degree of coupling faces two challenges: one is querying speed too slow, the other is space consumption too large. Facing the problems of long query time and large space occupation in graph data management, a two-level index compression algorithm named GComIdx for graph data was proposed. GComIdx algorithm used the ordered Key-Value structure to store the associated nodes and edges as closely as possible, and construct-ed two-level index and hash node index for efficient attribute query and neighbor query. Furthermore, GComIdx algorithm used a graph data compressed technology to compress the graph data before it directly stored in hard disk, which could effectively reduce the storing space consumption. The experimental results show that GComIdx algorithm can effectively reduce the initialization time of the graph data calculation and the disk space occupancy of the graph data storing, meanwhile, the query time is less than common graph databases and other Key-Value storage solutions

Attribute query, Graph compress, Key-Value structure, Neighbors query, Two-level index
1000-436X
109-115
Li, Gaochao
af5795ea-2af7-4dbc-8dbe-0ea324db247f
Li, Ben
fa1f31de-49d2-4805-8f22-7b712c8f720b
Lu, Yuhai
d8936e9f-4336-4a9c-b75d-d39ea13316a4
Liu, Mengya
24e44729-d719-4c97-aa3d-cb20f9107ca1
Liu, Yanbing
745ba67e-ef5d-497c-95c5-f7bff5e8c179
Li, Gaochao
af5795ea-2af7-4dbc-8dbe-0ea324db247f
Li, Ben
fa1f31de-49d2-4805-8f22-7b712c8f720b
Lu, Yuhai
d8936e9f-4336-4a9c-b75d-d39ea13316a4
Liu, Mengya
24e44729-d719-4c97-aa3d-cb20f9107ca1
Liu, Yanbing
745ba67e-ef5d-497c-95c5-f7bff5e8c179

Li, Gaochao, Li, Ben, Lu, Yuhai, Liu, Mengya and Liu, Yanbing (2018) 基于二级索引结构的图压缩算法. Tongxin Xuebao/Journal on Communications, 39 (6), 109-115. (doi:10.11959/j.issn.1000-436x.2018104).

Record type: Article

Abstract

The demand for the analysis and application of graph data in various fields is increasing day by day. The management of large-scale graph data with complicated structure and high degree of coupling faces two challenges: one is querying speed too slow, the other is space consumption too large. Facing the problems of long query time and large space occupation in graph data management, a two-level index compression algorithm named GComIdx for graph data was proposed. GComIdx algorithm used the ordered Key-Value structure to store the associated nodes and edges as closely as possible, and construct-ed two-level index and hash node index for efficient attribute query and neighbor query. Furthermore, GComIdx algorithm used a graph data compressed technology to compress the graph data before it directly stored in hard disk, which could effectively reduce the storing space consumption. The experimental results show that GComIdx algorithm can effectively reduce the initialization time of the graph data calculation and the disk space occupancy of the graph data storing, meanwhile, the query time is less than common graph databases and other Key-Value storage solutions

Text
1531102855628-1491305482 - Version of Record
Available under License Creative Commons Attribution.
Download (1MB)

More information

Published date: 25 June 2018
Alternative titles: Graph compression algorithm based on a two-level index structure
Keywords: Attribute query, Graph compress, Key-Value structure, Neighbors query, Two-level index

Identifiers

Local EPrints ID: 425150
URI: http://eprints.soton.ac.uk/id/eprint/425150
ISSN: 1000-436X
PURE UUID: adbcedc8-faa6-4c8f-b884-996098c2b63c

Catalogue record

Date deposited: 11 Oct 2018 16:30
Last modified: 07 Oct 2020 00:50

Export record

Altmetrics

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×