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This page contains information about the progress on the data generation based on the SIB benchmark and the S3G2 data generator. It will serve as a meeting point for the task force to advance on the topics raised in the first action point of the last call.

Document of work

Graph Database Benchmark Design Process

A discussion related to how we go about developing this benchmark can be found here

SNA Graph Schema

A proposal for a SNA graph schema based on the SIB benchmark can be found here

Query Sets for SNA Benchmarking

A discussion related to the different query sets of the SNA benchmark can be found here

Dataset generator

  • Current version: 080113
  • GDB output
    • Standard formats: GRAPHML (http://graphml.graphdrawing.org/) or GEFX (http://gexf.net/format/). Both formats are the most widely used by graph analysis tools. This format is better to specify nodes and edges as atomic units, with all their attributes, and to define a proper sequence of insertions
    • Tabular CSV (comma separated values). This format allows a more efficient bulk load because all entities of the same type are grouped in a single file
  • Configuration file
    • size
      • # users
      • time scale
      • # posts
      • etc.
    • distributions and probabilities
    • dictionaries
  • [Norbert] The generator defines edges before the adjacent nodes have been created (e.g. sib:like). We need to check if it is valid in GRAPHML or GEFX.
  • [Norbert] It seems that the generated dataset does not correspond exactly with the logical schema specified in the document (validation in process)
  • [Norbert] Random generator:
    • is it necessary to guarantee that datasets generated in different platforms or in different moments have the same content?
    • Is it possible to do it with the current hadoop-based generator?
  • Known problems:
    • The SIB document defines Users and Accounts, but the generator generates Persons and Users
    • Texts from DBPEDIA contain UNICODE characters (UTF-8?). RDF readers such as JENA cannot process it in the current format.
    • All tokens extracted from a DBPEDIA entry are used as hashtags. It seems that some nodes have exactly the same hashtags as others, without any variability
    • Java VM memory size for large datasets
    • Hadoop timeout
  • Experimental validation
    • Convert to property graph and export in tabular format (1 computer, 2 QuadCores, 128GB mem)

      Filename#Users#YearsT sibSize RDF#TriplesSize tabular#Nodes#Edges#Values#Total
      graph40040013m0.6GB16.9M363MB1.53M6.85M7.45M15.83M
       1000016m4.7GB126.5M2.8GB11.15M51.86M54.66M117.67M
       20000324m32GB839.7M19GB75.57M304.78M369.76M750.11M
       100000138m48GB1259.8M29GB111.18M518.26M544.93M1.15G
       100000274m103GB2.73B63GB244.81M1.13G1.20G2.58G
       2000002151m207GB5.46B126GB489.11M2.22G2.39G5.10G
    • Sample files can be downloaded from http://fedra.pc.ac.upc.edu/LDBC/<filename>.tar.gz

    • File data is compliant with the current property graph schema
    • Each row contains one node or one edge with comma-separated values
    • String values are not quoted except post and comments
    • The first value is always the node or the edge label
    • For nodes, after the label comes each attribute value in the same order as in the schema
    • For edges, after the label comes the source label and id, the destination label and id, and the attribute values

Benchmark Execution

  • Performance metrics proposed in SIB
    • Query per second
    • Query mix per hour
    • Total execution time
  • [Norbert] Scaling (scale factor)
  • We are running some configurations of the generator to analyze the dataset sizes in GB and number of triples
  • [Norbert] reference data set and expected query results?
  • [Norbert, Miquel] frequencies of queries in query mix?
  • [Norbert, Miquel] dynamic arguments for queries?

 

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