The 5th LDBC Technical User Community (TUC) meeting took place in Athens on 14.11.2014 being well attended by both Graph and RDF databases industry and academia. In the morning session, members of the LDBC project gave an update on the status of the project and its benchmarks:
The SNB Driver part 1 post introduced, broadly, the challenges faced when developing a workload driver for the LDBC SNB benchmark. In this blog we'll drill down deeper into the details of what it means to execute "dependent queries" during benchmark execution, and how this is handled in the driver. First of all, as many driver-specific terms will be used, below is a listing of their definitions. There is no need to read them in detail, it is just there to serve as a point of reference.
The Semantic Publishing Instance Matching Benchmark (SPIMBench) is a novel benchmark for the assessment of instance matching techniques for RDF data with an associated schema. SPIMBench extends the state-of-the art instance matching benchmarks for RDF data in three main aspects: it allows for systematic scalability testing, supports a wider range of test cases including semantics-aware ones, and provides an enriched gold standard.
We are presently working on the SNB BI workload. Andrey Gubichev of TU Munchen and myself are going through the queries and are playing with two SQL based implementations, one on Virtuoso and the other on Hyper.
As discussed before, the BI workload has the same choke points as TPC-H as a base but pushes further in terms of graphiness and query complexity.