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No Size Fits All - Running the Star Schema Benchmark with SPARQL and RDF Aggregate Views
Published on Jul 08, 20133852 Views
Statistics published as Linked Data promise efficient extraction, transformation and loading (ETL) into a database for decision support. The predominant way to implement analytical query capabilities
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Chapter list
No Size Fits All – Running the Star Schema Benchmark with SPARQL and RDF Aggregate Views00:00
Motivation - 100:13
Motivation - 201:07
Motivation - 301:58
Problem 02:53
Problem: ROLAP vs OLAP4LD - 105:30
Related Work06:32
Outline - 107:17
Star Schema Benchmark [SSB] – Data07:42
Star Schema Benchmark [SSB] – Queries09:16
Star Schema Benchmark (SSB) – 4 Query Flights of 13 Queries10:25
Experimental Setup11:02
Problem: ROLAP vs OLAP4LD - 212:05
ROLAP vs OLAP4LD – Results12:14
ROLAP vs OLAP4LD – Query processing - 112:21
ROLAP vs OLAP4LD – Query processing - 212:38
ROLAP vs OLAP4LD – Query processing - 313:05
ROLAP vs OLAP4LD – Query processing - 413:24
Outline - 214:21
Evaluating Materialised Aggregate Views14:37
Data Cube Lattice – Features15:23
View Selection and Computation16:23
Outline - 317:50
Problem: ROLAP vs OLAP4LD - 317:57
OLAP4LD vs OLAP4LD-M – Results18:03
OLAP4LD vs OLAP4LD-M – Query processing - 618:49
OLAP4LD vs OLAP4LD-M – Query processing - 719:07
OLAP4LD vs OLAP4LD-M – Query processing - 820:47
OLAP4LD vs OLAP4LD-M – Query processing - 921:02
Conclusion21:19
Feedback & Questions22:44
ROLAP vs OLAP4LD – Query processing - 523:05