AllegroGraph RDFStore Version 3.3 LUBM Benchmark Results

The following describes the performance of retrieval and RDFS reasoning with the native AllegroGraph RDFS++ Reasoner and AllegroGraph Prolog using the LUBM benchmark, with on average 20 departments per university.

These queries were performed with full RDFS++ reasoning at query time. Because the LUBM benchmark was designed to test some aspects of OWL reasoning that (by design) are beyond the strength of the RDFS++ reasoner, we added the single triple:

  • ub:GraduateStudent rdfs:subClassOf ub:Student

The AllegroGraph RDFS++ Reasoner handles the following RDFS and OWL predicates correctly:

RDFS:

<http://www.w3.org/1999/02/22-rdf-syntax-ns#type>

<http://www.w3.org/2000/01/rdf-schema#subPropertyOf>

<http://www.w3.org/2000/01/rdf-schema#subClassOf>

<http://www.w3.org/2000/01/rdf-schema#range>

<http://www.w3.org/2000/01/rdf-schema#domain>

OWL:

<http://www.w3.org/2002/07/owl#sameAs>

<http://www.w3.org/2002/07/owl#inverseOf>

<http://www.w3.org/2002/07/owl#TransitiveProperty>

The AllegroGraph Reasoner does not handle full OWL restrictions. For that we recommend RacerPro.

Dynamic Materialization

AllegroGraph version 3.3's RDFS++ engine dynamically maintains the ontological entailments required for reasoning: it has no explicit materialization phase. Materialization is the pre-computation and storage of inferred triples so that future queries run more efficiently. The central problem with materialization is its maintenance: changes to the triple-store's ontology or facts usually change the set of inferred triples. In static materialization, any change in the store requires complete re-processing before new queries can run. AllegroGraph's dynamic materialization simplifies store maintenance and reduces the time required between data changes and querying.

AllegroGraph RDFStore 3.3 Benchmark for LUBM(50)

The total number of files read in is 1000. The total number of triples after running the queries is 6,875,705.

In the LUBM(50) results below, AllegroGraph's dynamic materialization occurred as necessary to answer each query. For AllegroGraph version 3.3, loading, indexing and merging required a total of 7 minutes and 50 seconds.

Query Performance Improvements in AllegroGraph version 3.3

Table 1 shows the results of running the LUBM 50 queries with both version 3.1 and 3.3 of AllegroGraph. The total query time for the 14 queries on went from 275.379 seconds in version 3.1 to 3.798 seconds in version 3.3. The results are reported in seconds.

Table 1: Summary of LUBM(50) Results

Lubm Query
# Triples
3.1 Time
3.3 Time
Query 1
4
0.000
0.007
Query 2
130
2.634
0.330
Query 3
6
0.002
0.006
Query 4
34
0.046
0.030
Query 5
719
3.899
0.055
Query 6
519,842
5.420
1.363
Query 7
67
0.027
0.013
Query 8
7,790
3.371
0.303
Query 9
13,639
254.107
1.245
Query 10
4
0.002
0.010
Query 11
224
0.075
0.010
Query 12
15
3.470
0.025
Query 13
228
0.091
0.014
Query 14
383,730
2.235
0.387

The platform for the tests was a Quad 1.8GHz AMD64 Opteron 884, with 16Gb of memory running Fedora 8.

Download the LUBM(50) Benchmark files

The details are in the Learning Center example here: LUBM(50) Dataset

AllegroGraph RDFStore 3.3 Benchmark for LUBM(8000)

The total number of files read in is 160,007 N-Triples files, a total of 155 GB. The total number of triples after running the queries is 1,105,993,401. In the LUBM(8000) results below, AllegroGraph's dynamic materialization occurred as necessary to answer each query. Loading required a total of 30 hours, 28 minutes and 43.5 seconds. The total query time was 10 minutes and 11.397 seconds.

Table 2 shows the results of running the LUBM(8000) queries with version 3.3 of AllegroGraph. The results are reported in seconds.

Table 2: Summary of LUBM(8000) Results

Lubm Query
# Triples
3.3 Time
Query 1
4
0.009
Query 2
2,528
135.541
Query 3
6
0.008
Query 4
34
0.031
Query 5
719
0.065
Query 6
83,557,706
208.065
Query 7
67
0.015
Query 8
7,790
0.384
Query 9
2,178,420
206.133
Query 10
4
0.011
Query 11
224
0.013
Query 12
15
0.028
Query 13
37,118
0.093
Query 14
63,400,587
61.001

The platform for the tests was a Quad 1.8GHz AMD64 Opteron 884, with 16Gb of memory running Fedora 8.

Download the LUBM(8000) Benchmark files

The details are in the Learning Center example here: LUBM(8000) Dataset

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