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DBpedia SPARQL Benchmark – Performance Assessment with Real Queries on Real Data
Published on Nov 25, 20112937 Views
Triple stores are the backbone of increasingly many Data Web applications. It is thus evident that the performance of those stores is mission critical for individual projects as well as for data integ
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DBpedia SPARQL Benchmark–Performance Assessment with Real Queries on Real Data00:00
Motivation00:00
Motivation: Existing benchmarks - 100:36
Motivation: Existing benchmarks - 201:00
Motivation: Existing benchmarks - 301:18
Motivation: Existing benchmarks - 401:32
Motivation: Existing benchmarks - 501:44
Motivation: Existing benchmarks - 601:57
Motivation: Existing benchmarks - 702:02
Approach - 102:38
Query List Generation - 103:01
Query List Generation - 203:36
Preprocessing - 103:38
Preprocessing - 204:33
Query List Generation - 305:15
Clustering - 105:19
Similarity Computation05:40
Clustering - 206:27
Query List Generation - 407:30
QueriesSPARQL Feature Selection and Query Variability - 107:38
QueriesSPARQL Feature Selection and Query Variability - 207:53
QueriesSPARQL Feature Selection and Query Variability - 308:29
Approach - 209:12
Requirements for Dataset Generation09:21
Dataset Generation09:40
Dataset Generation: Small Datasets - 109:56
Dataset Generation: Small Datasets - 211:11
Dataset Generation: Large Datasets11:23
Experimental Setup11:50
Results: Queries per Second (QpS) - 112:39
Results: Queries per Second (QpS) - 212:45
Results: Slow Queries14:10
Results: Fast Queries15:41
Results: Query Mixes per Hour (QMpH)15:55
Results: Scalability16:20
Conclusion17:15
Future Work17:48
Thank you19:40