0.25
0.5
0.75
1.25
1.5
1.75
2
Answering Provenance-Aware Queries on RDF Data Cubes under Memory Budgets
Published on Nov 22, 20182669 Views
The steadily-growing popularity of semantic data on the Web and the support for aggregation queries in SPARQL 1.1 have propelled the interest in Online Analytical Processing (OLAP) and data cubes in R
Related categories
Chapter list
Answering Provenance-Aware Queries on RDF Data Cubes under Memory Budgets00:00
Data Cubes - 100:24
Data Cubes - 200:27
Data Cubes & OLAP - 101:07
Data Cubes & OLAP - 201:17
Data Cubes & OLAP - 301:25
Data Cubes & OLAP - 401:57
RDF Data Cubes - 102:02
RDF Data Cubes - 202:05
RDF Data Cubes - 302:29
RDF Data Cubes & OLAP02:44
Provenance RDF Data Cubes02:55
RDF Cubes & Provenance - 102:59
RDF Cubes & Provenance - 203:05
RDF Cubes & Provenance - 303:23
Quads & Named Graphs - 103:27
Quads & Named Graphs - 203:37
Answering Provenance-Aware Queries on RDF Data Cubes under Memory Budgets - 103:48
Provenance-aware queries - 103:52
Provenance-aware queries - 204:12
Answering provenance-aware queries - 104:38
Answering provenance-aware queries - 204:43
Answering provenance-aware queries - 304:49
Answering provenance-aware queries - 404:53
Answering provenance-aware queries - 505:34
Answering provenance-aware queries - 605:44
Answering provenance-aware queries - 706:36
Answering Provenance-Aware Queries on RDF Data Cubes under Memory Budgets - 206:44
Building the PAC06:53
Fragment selection under memory budget - 107:38
Fragment selection under memory budget - 207:51
Fragment selection under memory budget - 308:01
Fragment selection under memory budget - 408:03
Fragment selection under memory budget - 508:30
Fragment selection under memory budget - 608:45
Fragment selection under memory budget - 709:06
Evaluation: Settings - 109:08
Evaluation: Settings - 209:34
PAC vs. in-memory DB09:49
Performance @ different budgets - 110:30
Performance @ different budgets - 211:00
Conclusions11:18