The Query Speed Improvement on Distributed Graph Database Using Streaming Graph Partitioning Strategy with Asynchronous Transaction Information
Date Issued
2016
Date
2016
Author(s)
Hung, Li-Yuan
Abstract
In this research, we propose an idea to delay the commit time in a dis-tributed graph database by the asynchronous transaction. In this way, moreinformation can be gathered to make better streaming graph partitioning de-cision and that will lead to faster query speed afterwards. We propose threestrategies: global max-probability, connected-component max-probability,and independent cascade. Compared with default random graph partitioning strategy,our best connected-component max-probability strategy can have an positive average query speed improvement.The query speed improvement is most effective in query FNoN and FSPand we conclude that’s because the intensive traversal in these two queriesbenefit more from the data locality.
Subjects
streaming graph partitioning
asynchronous transaction
graph database
Type
thesis
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