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EDF2012   Peter Boncz - LOD benchmarking SRbench
 

EDF2012 Peter Boncz - LOD benchmarking SRbench

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    EDF2012   Peter Boncz - LOD benchmarking SRbench EDF2012 Peter Boncz - LOD benchmarking SRbench Presentation Transcript

    • Benchmarking Linked Open Data technologySRbench: A Benchmark for Streaming RDF Storage Engines Ying Zhang, Peter Boncz (CWI, Amsterdam)
    • What is Database Benchmarking?Standard test to measure and understand how technology performs Dataset definition  at various scales (100GB, 300GB, 1TB, 3TB, etc)  mimicks a recognizable relevant usage scenario Database Queries  often between 10-100 queries, with parameters  + rules/programs that specify how these queries are posed Result Metrics  a number to understand the result  tps = “transactions/second” $/QphH@size = “price per query per hour” Audit Rules  allow results to be checked by independent auditors  prevent/limit cheating Ying Zhang, Peter Boncz – Benchmarking Linked Open Data Technology June 7, 2012 @EDF Copenhagen
    • Why Benchmarking? make competing products comparable accelerate progress, make technology viable © Jim Gray, 2005Ying Zhang, Peter Boncz – Benchmarking Linked Open Data Technology June 7, 2012 @EDF Copenhagen
    • Benchmarking LOD TechnologyLOD = Linked Open Data web addressable data RDF data format ( ) lots of useful data on the web (“LOD cloud”)LOD technology (SPARQL) benchmarks: BSBM, DBpedia Benchmark, SIB SRbench  topic of this talk New industry cooperation: Ying Zhang, Peter Boncz – Benchmarking Linked Open Data Technology June 7, 2012 @EDF Copenhagen
    • * tentative/expected project LDBC: FP7 2012-2015vendor cooperation to establish accepted RDF/Graph database benchmarks and benchmark results6/9/2012 5
    • LDBC Goals 1. Create the LDBC Foundation of graph and RDF DB vendors 2. Equip de LDBC Foundation with a good initial set of benchmarks, and benchmark resultsspin-off 6/9/2012 6
    • Benchmarking Linked Open Data technologySRbench: A Benchmark for Streaming RDF Storage Engines Ying Zhang, Peter Boncz (CWI, Amsterdam)
    • SRbench: Streaming RDF BenchmarkTraditional Database System vs. Stream Database System stream stream stream of of of queries queries data queries stream “pull” based query answering Persistent Persistent Queries “push” based Data “continuous queries” query answeringYing Zhang, Peter Boncz – Benchmarking Linked Open Data Technology June 7, 2012 @EDF Copenhagen
    • Data Streams (1/4): Stock Market
    • Data Streams (2/4): Social Chatter Detect breaking news Analyze Marketing campaigns Ying Zhang, Peter Boncz – Benchmarking Linked Open Data Technology June 7, 2012 @EDF Copenhagen
    • Data Streams (3/4): Car Traffic monitor positions and speeds of cars detect accidents, traffic jams Applications: better safety, improved logistics Ying Zhang, Peter Boncz – Benchmarking Linked Open Data Technology June 7, 2012 @EDF Copenhagen
    • Data Streams (4/4): Tele HealthMonitor health of elderly in their homes Who are the users? Why?- Difficult to reach locations- Make health care more affordable How? Ying Zhang, Peter Boncz – Benchmarking Linked Open Data Technology June 7, 2012 @EDF Copenhagen
    • SRbench: Streaming RDF BenchmarkStreaming RDF data benefits: apply Linked Open Data (LOD) principles to streaming data  Link streaming data to data on the web (enrichment)  Publish data streams on the web support (simple) reasoning semantics in stream queries Richer semantics than relational streaming database systems Ying Zhang, Peter Boncz – Benchmarking Linked Open Data Technology June 7, 2012 @EDF Copenhagen
    • SRbench: Streaming RDF BenchmarkStreaming RDF data challenges: Proper benchmark dataset  use real-world datasets from LOD No standard query language  natural language query definition + three implementations (SPARQLStream, CQELS, C-SPARQL) Limited systems support  evaluate on the strRS system (UPM) Ying Zhang, Peter Boncz – Benchmarking Linked Open Data Technology June 7, 2012 @EDF Copenhagen
    • Use case: wheather information applicationSRbench: used Datasets LinkedSensorData LinkedObservationData LinkedSensorMetaData om-owl:procedure Observation System om-owl:result om-owl:hasLocatedNearRelom-owl:samplingTime ResultData om-owl:processLocationInstant MeasureData TruthData Point LocatedNearRel DBpedia GeoNames om-owl:hasLocation owl:sameAs Airport FeatureYing Zhang, Peter Boncz – Benchmarking Linked Open Data Technology June 7, 2012 @EDF Copenhagen
    • SRBench Queries
    • Summary the importance of  Database System Benchmarking  RDF Database System Benchmarking ( )  Streaming RDF Database System Benchmarking SRbench  Developed in PlanetData (CWI, UPM)  First dedicated streaming RDF/SPARQL benchmark SRbench future work:  performance evaluation  results verification (not easy!) Ying Zhang, Peter Boncz – Benchmarking Linked Open Data Technology June 7, 2012 @EDF Copenhagen
    • Thank You!Questions? Ying Zhang (zhang@cwi.nl) Peter Boncz (boncz@cwi.nl) Ying Zhang, Peter Boncz – Benchmarking Linked Open Data Technology June 7, 2012 @EDF Copenhagen