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Benchmarking
        Linked Open Data technology
SRbench: 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, 2005



Ying Zhang, Peter Boncz – Benchmarking Linked Open Data Technology   June 7, 2012 @EDF Copenhagen
Benchmarking LOD Technology
LOD = 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 2012-2015
vendor cooperation to establish accepted RDF/Graph
  database benchmarks and benchmark results




6/9/2012                                  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 results




spin-off


  6/9/2012                                 6
Benchmarking
           Linked Open Data technology
SRbench: A Benchmark for Streaming RDF Storage Engines



          Ying Zhang, Peter Boncz (CWI, Amsterdam)
SRbench: Streaming RDF Benchmark
Traditional 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 answering




Ying 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 Health
Monitor 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 Benchmark

Streaming 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 Benchmark

Streaming 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 application


SRbench: used Datasets
                                           LinkedSensorData
            LinkedObservationData                                         LinkedSensorMetaData
                                             om-owl:procedure
                  Observation                                        System


                          om-owl:result
                                                                                om-owl:hasLocatedNearRel
om-owl:samplingTime
                        ResultData                                 om-owl:processLocation

Instant               MeasureData         TruthData
                                                                     Point            LocatedNearRel




                            DBpedia                             GeoNames           om-owl:hasLocation
                                               owl:sameAs
                            Airport                             Feature



Ying 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

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EDF2012 Peter Boncz - LOD benchmarking SRbench

  • 1. Benchmarking Linked Open Data technology SRbench: A Benchmark for Streaming RDF Storage Engines Ying Zhang, Peter Boncz (CWI, Amsterdam)
  • 2. 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
  • 3. Why Benchmarking?  make competing products comparable  accelerate progress, make technology viable © Jim Gray, 2005 Ying Zhang, Peter Boncz – Benchmarking Linked Open Data Technology June 7, 2012 @EDF Copenhagen
  • 4. Benchmarking LOD Technology LOD = 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
  • 5. * tentative/expected project LDBC: FP7 2012-2015 vendor cooperation to establish accepted RDF/Graph database benchmarks and benchmark results 6/9/2012 5
  • 6. 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 results spin-off 6/9/2012 6
  • 7. Benchmarking Linked Open Data technology SRbench: A Benchmark for Streaming RDF Storage Engines Ying Zhang, Peter Boncz (CWI, Amsterdam)
  • 8. SRbench: Streaming RDF Benchmark Traditional 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 answering Ying Zhang, Peter Boncz – Benchmarking Linked Open Data Technology June 7, 2012 @EDF Copenhagen
  • 9. Data Streams (1/4): Stock Market
  • 10. 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
  • 11. 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
  • 12. Data Streams (4/4): Tele Health Monitor 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
  • 13. SRbench: Streaming RDF Benchmark Streaming 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
  • 14. SRbench: Streaming RDF Benchmark Streaming 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
  • 15. Use case: wheather information application SRbench: used Datasets LinkedSensorData LinkedObservationData LinkedSensorMetaData om-owl:procedure Observation System om-owl:result om-owl:hasLocatedNearRel om-owl:samplingTime ResultData om-owl:processLocation Instant MeasureData TruthData Point LocatedNearRel DBpedia GeoNames om-owl:hasLocation owl:sameAs Airport Feature Ying Zhang, Peter Boncz – Benchmarking Linked Open Data Technology June 7, 2012 @EDF Copenhagen
  • 17. 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
  • 18. 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