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 …

Up until now we have introduced the
challenges faced when executing the LDBC SNB benchmark, as well as
explained
how some of these are overcome. With the foundations laid, we can now
explain precisely how operations are executed.

Based on the dependencies certain operations have, and on the
granularity of parallelism we wish to achieve while executing them, we
assign a Dependency Mode and an Execution Mode to every operation type.
Using these …

Until now we have discussed several aspects of the
Semantic Publishing Benchmark (SPB) such as the
difference in performance between virtual and real servers configuration, how to
choose an appropriate query mix for a benchmark run and our experience with using SPB in the
development process of GraphDB for finding performance issues.

In this post we provide a step-by-step guide on how to run SPB using the
Sesame RDF data store on a fresh
install …

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.

The SPIMBench …

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.

There are obvious marketing applications for a SNB-like dataset. There are also security …

LDBC’s Semantic Publishing Benchmark (SPB) measures the performance of an RDF database in a load
typical for metadata-based content publishing, such as the famous
BBC Dynamic Semantic Publishing scenario. Such load combines tens of
updates per second (e.g. adding metadata about new articles) with even
higher volume of read requests (SPARQL queries collecting recent content
and data to generate web page on a specific subject, e.g. Frank …