In previous posts (Getting started with SNB, DATAGEN: data generation for the Social Network Benchmark), Arnau Prat discussed the main features and characteristics of DATAGEN: realism, scalability, determinism, usability. DATAGEN is the social network data generator used by the three LDBC-SNB workloads, which produces data simulating the activity in a social network site during a period of time. In this post, we conduct a series of experiments …

In this multi-part blog we consider the challenge of running the LDBC Social Network Interactive Benchmark (LDBC SNB) workload in parallel, i.e. the design of the workload driver that will issue the queries against the System Under Test (SUT). We go through design principles that were implemented for the LDBC SNB workload generator/load tester (simply referred to as driver). Software and documentation for this driver is available here: …

LDBC SPB (Semantic Publishing Benchmark) is based on the BBC linked data platform use case. Thus the data modelling and transaction mix reflects the BBC’s actual utilization of RDF. But a benchmark is not only a condensation of current best practices. The BBC linked data platform is an Ontotext Graph DB deployment. Graph DB was formerly known as OWLIM.

So, in SPB we wanted to address substantially more complex queries than the lookups that …

The Semantic Publishing Benchmark (SPB), developed in the context of LDBC, aims at measuring the read and write operations that can be performed in the context of a media organisation. It simulates the management and consumption of RDF metadata describing media assets and creative works. The scenario is based around a media organisation that maintains RDF descriptions of its catalogue of creative works. These descriptions use a set of ontologies …

The Linked Data Benchmark Council (LDBC) mission is to design and maintain benchmarks for graph data management systems, and establish and enforce standards in running these benchmarks, and publish and arbitrate around the official benchmark results. The council and its https://ldbcouncil.org website just launched, and in its first 1.5 year of existence, most effort at LDBC has gone into investigating the needs of the field through interaction …

The Linked Data Benchmark Council (LDBC) is reaching a milestone today, June 23 2014, in announcing that two of the benchmarks that it has been developing since 1.5 years have now reached the status of Public Draft. This concerns the Semantic Publishing Benchmark (SPB) and the interactive workload of the Social Network Benchmark (SNB). In case of LDBC, the release is staged: now the benchmark software just runs read-only queries. This will be …

Social Network interaction is amongst the most natural and widely spread activities in the internet society, and it has turned out to be a very useful way for people to socialise at different levels (friendship, professional, hobby, etc.). As such, Social Networks are well understood from the point of view of the data involved and the interaction required by their actors. Thus, the concepts of friends of friends, or retweet are well established …

It is with great pleasure that we announce the new LDBC organisation site at www.ldbcouncil.org. The LDBC started as a European Community FP7 funded project with the objective to create, foster and become an industry reference for benchmarking RDF and Graph technologies. A period of more than one and a half years has led us to the creation of the first two workloads, the Semantic Publishing Benchmark and the Social Network Benchmark in its …

Following the 1st International workshop on Benchmarking RDF Systems (BeRSys 2013) the aim of the BeRSys 2014 workshop is to provide a discussion forum where researchers and industrials can meet to discuss topics related to the performance of RDF systems. BeRSys 2014 is the only workshop dedicated to benchmarking different aspects of RDF engines - in the line of TPCTC series of workshops.The focus of the workshop is to expose and initiate …

As explained in a previous post, the LDBC Social Network Benchmark (LDBC-SNB) has the objective to provide a realistic yet challenging workload, consisting of a social network and a set of queries. Both have to be realistic, easy to understand and easy to generate. This post has the objective to discuss the main features of DATAGEN, the social network data generator provided by LDBC-SNB, which is an evolution of S3G2 [1].

One of the most …