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Impact analysis of data placement strategies on query efforts in distributed RDF stores
Published on 2018-11-222781 Views
In the last years, scalable RDF stores in the cloud have been developed, where graph data is distributed over compute and storage nodes for scaling efforts of query processing and memory needs. One ma
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Presentation
Impact Analysis of Data Placement Strategies on Query Efforts in Distributed RDF Stores00:00
Distributed RDF Stores 00:02
Why using distributed RDF Stores?00:37
Challenges of RDF Stores in the Cloud - 101:24
Challenges of RDF Stores in the Cloud - 201:43
Terminology: Graph Cover 01:48
Common Graph Cover Strategies02:15
Horizontal Containment03:42
Comparing Complete RDF Stores05:09
Evaluation With Batch Processing Frameworks05:59
Our Novel Evaluation Methodology06:50
Dataset & Queries07:20
Koral07:53
Evaluation Measures08:32
Experimental Setup09:37
Overall Query Performance (10 Slaves)10:05
Horizontal Containment (10 Slaves)10:43
Workload Imbalance (10 Slaves)11:03
Vertical Parallelization11:20
Effect of Scaling Number of Slaves11:47
Conclusion - 113:13
Conclusion - 214:17