This post is the first in a series of blogs analyzing the LDBC Social Network Benchmark Interactive workload. This is written from the dual perspective of participating in the benchmark design and of building the OpenLink Virtuoso implementation of same.

With two implementations of SNB interactive at four different scales, we can take a first look at what the benchmark is really about. The hallmark of a benchmark implementation is that its …

Why Do We Need an LDBC SNB-Specific Workload Driver?


In a previous 3-part blog series we touched upon the difficulties of executing the LDBC SNB Interactive (SNB) workload, while achieving good performance and scalability. What we didn’t discuss is why these difficulties were unique to SNB, and what aspects of the way we perform workload execution are scientific contributions - novel solutions to previously unsolved problems. This post will highlight the differences between SNB and more …

Event Driven Post Generation in Datagen


As discussed in previous posts, one of the features that makes Datagen more realistic is the fact that the activity volume of the simulated Persons is not uniform, but forms spikes. In this blog entry I want to explain more in depth how this is actually implemented inside of the generator.

First of all, I start with a few basics of how Datagen works internally. In Datagen, once the person graph has been created (persons and their relationships), …

The LDBC Datagen Community Structure


This blog entry is about one of the features of DATAGEN that makes it different from other synthetic graph generators that can be found in the literature: the community structure of the graph.

When generating synthetic graphs, one must not only pay attention to quantitative measures such as the number of nodes and edges, but also to other more qualitative characteristics such as the degree distribution, clustering coefficient. Real graphs, and …

OWL-Empowered SPARQL Query Optimization


The Linked Data paradigm has become the prominent enabler for sharing huge volumes of data using Semantic Web technologies, and has created novel challenges for non-relational data management systems, such as RDF and graph engines. Efficient data access through queries is perhaps the most important data management task, and is enabled through query optimization techniques, which amount to the discovery of optimal or close to optimal execution …