| Author: | Zhou, You |
| Title: | A scalable and flexible correlated data storage framework based on heterogeneous graph |
| Degree: | M.Sc. |
| Year: | 2014 |
| Subject: | Information storage and retrieval systems. Computer vision. Hong Kong Polytechnic University -- Dissertations |
| Department: | Department of Computing |
| Pages: | vii, 57 leaves : illustrations ; 30 cm |
| Language: | English |
| Abstract: | Heterogeneous Graph, with the ability to store data and relations with diverse schemas, is both intuitive to manage relational information and powerful to mine underlying knowledge from them. In typical cases, the graph is required to be progressive, which means the attributes of nodes (or edges) need to support drill down/up to represent information with different granularity. To meet this requirement, previous works simply copy and transform the data from predefined granularity and store it as a graph, which is not flexible and results in redundant data across graphs. However, due to the fact that graphs with millions of nodes and edges are now common places, it is costly to copy data with extreme high volume and might lead to sync problem. Moreover, with the design of centralized data storage, those works are not scalable as well. To address the problems, GNODE, a scalable and flexible heterogeneous graph storage framework, is proposed. The contributions of this paper include: 1) multi-schema data model and dynamic binding design permit graphs with different granularity built sharing the same dataset to reduce data redundancy and increase flexibility; 2) distributed architecture and index design increase the scalability and performance without losing flexibility. With the experiments conducted on varisized datasets, GNODE is proved to have similar performance to current graph database like neo4j but outperform in flexibility and scalability. |
| Rights: | All rights reserved |
| Access: | restricted access |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| b27577259.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 2.14 MB | Adobe PDF | View/Open |
Copyright Undertaking
As a bona fide Library user, I declare that:
- I will abide by the rules and legal ordinances governing copyright regarding the use of the Database.
- I will use the Database for the purpose of my research or private study only and not for circulation or further reproduction or any other purpose.
- I agree to indemnify and hold the University harmless from and against any loss, damage, cost, liability or expenses arising from copyright infringement or unauthorized usage.
By downloading any item(s) listed above, you acknowledge that you have read and understood the copyright undertaking as stated above, and agree to be bound by all of its terms.
Please use this identifier to cite or link to this item:
https://theses.lib.polyu.edu.hk/handle/200/7542