ATTENTION: The works hosted here are being migrated to a new repository that will consolidate resources, improve discoverability, and better show UTA's research impact on the global community. We will update authors as the migration progresses. Please see MavMatrix for more information.
Show simple item record
dc.contributor.advisor | Chakravarthy, Sharma | |
dc.creator | Bodra, Jay Dilipbhai D. | |
dc.date.accessioned | 2016-09-28T18:25:02Z | |
dc.date.available | 2016-09-28T18:25:02Z | |
dc.date.created | 2016-05 | |
dc.date.issued | 2016-05-12 | |
dc.date.submitted | May 2016 | |
dc.identifier.uri | http://hdl.handle.net/10106/25913 | |
dc.description.abstract | Representation of structured data using graphs is meaningful for applications such as road and social networks. With the increase in the size of graph databases, querying them to retrieve desired information poses challenges in terms of query representation and scalability. Independently, querying and graph partitioning have been researched in the literature. However, to the best of our knowledge, there is no effective scalable approach for querying graph databases using partitioning schemes. Also, it will be useful to analyze the quality of partitioning schemes from the query processing perspective.
In this thesis, we propose a divide and conquer approach to process queries over very large graph database using available partitioning schemes. We also identify a set of metrics to evaluate the effect of partitioning schemes on query processing. Querying over partitions requires handling answers that: i) are within the same partition, ii) span multiple partitions, and iii) requires the same partition to be used multiple times. Number of connected components in partitions and number of starting nodes of a plan in a partition may be useful for determining the starting partition and the sequence in which partitions need to be processed. Experiments on processing queries over three different graph databases (DBLP, IMDB, and Synthetic), partitioned using different partitioning schemes have been performed. Our experimental results show the correctness of the approach and provide some insights into the metrics gleaned from partitioning schemes on query processing. QP-Subdue a graph querying system developed at UTA, has been modified to process queries over partitions of a graph database. | |
dc.format.mimetype | application/pdf | |
dc.language.iso | en_US | |
dc.subject | Graph | |
dc.subject | Graph partitioning | |
dc.subject | Graph query | |
dc.subject | Graph catalog | |
dc.subject | Partition usage | |
dc.title | PROCESSING QUERIES OVER PARTITIONED GRAPH DATABASES: AN APPROACH AND IT'S EVALUATION | |
dc.type | Thesis | |
dc.degree.department | Computer Science and Engineering | |
dc.degree.name | Master of Science in Computer Science | |
dc.date.updated | 2016-09-28T18:27:09Z | |
thesis.degree.department | Computer Science and Engineering | |
thesis.degree.grantor | The University of Texas at Arlington | |
thesis.degree.level | Masters | |
thesis.degree.name | Master of Science in Computer Science | |
dc.type.material | text | |
dc.creator.orcid | 0000-0003-0723-0709 | |
Files in this item
- Name:
- BODRA-THESIS-2016.pdf
- Size:
- 5.492Mb
- Format:
- PDF
This item appears in the following Collection(s)
Show simple item record