The Day of Graph Analytics

  • Posted on: 9 October 2014
  • By: Orri Erling

Note: consider this post as a continuation of the "Making it interactive" post by Orri Erling.

I have now completed the Virtuoso TPC-H work, including scale out.  Optimization possibilities extend to infinity but the present level is good enough. TPC-H is the classic of all analytics benchmarks and is difficult enough, I have extensive commentary on this on my blog (In Hoc Signo Vinces series), including experimental results.  This is, as it were, the cornerstone of the true science.  This is however not the totality of it.  From the LDBC angle, we might liken this to the last camp before attempting a mountain peak.

Making It Interactive

  • Posted on: 26 September 2014
  • By: Orri Erling

Synopsis: Now is the time to finalize the interactive part of the Social Network Benchmark (SNB). The benchmark must be both credible in a real social network setting and pose new challenges. There are many hard queries but not enough representation for what online systems in fact do. So, the workload mix must strike a balance between the practice and presenting new challenges.

SNB Data Generator - Getting Started

  • Posted on: 18 September 2014
  • By: Arnau Prat

In previous posts (this and this) we briefly introduced the design goals and philosophy behind DATAGEN, the data generator used in LDBC-SNB. In this post, I will explain how to use DATAGEN to generate the necessary datatsets to run LDBC-SNB. Of course, as DATAGEN is continuously under development,  the instructions given in this tutorial might change in the future.

Introducing SNB Interactive, the LDBC Social Network Benchmark Online Workload

  • Posted on: 4 September 2014
  • By: Orri Erling

The LDBC Social Network Benchmark (SNB) is composed of three distinct workloads, interactive, business intelligence and graph analytics. This post introduces the interactive workload.

The benchmark measures the speed of queries of medium complexity against a social network being constantly updated. The queries are scoped to a user's social environment and potentially access data associated with the friends or a user and their friends.

Using LDBC-SPB to Find OWLIM Performance Issues

  • Posted on: 20 August 2014
  • By: Venelin Kotsev

During the past six months we (the OWLIM Team at Ontotext) have integrated the LDBC Semantic Publishing Benchmark (LDBC-SPB) as a part of our development and release process.

First thing we’ve started using the LDBC-SPB for is to monitor the performance of our RDF Store when a new release is about to come out.

Initially we’ve decided to fix some of the benchmark parameters :

DATAGEN: data generation for the Social Network Benchmark

  • Posted on: 14 August 2014
  • By: Arnau Prat

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 S3G21.

Getting Started with the Semantic Publishing Benchmark

  • Posted on: 8 August 2014
  • By: Irini Fundulaki

The Semantic publishing benchmark, 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 proposed by BBC that define numerous properties for content; they contain asll RDFS schema constructs and certain OWL ones.

Is SNB like Facebook's LinkBench?

  • Posted on: 29 July 2014
  • By: Peter Boncz
table showing which kind of graph data management system might be tested for the three different  SNB workloads.

In this post, I will discuss in some detail the rationale and goals of the design of the Social Network Benchmark (SNB) and explain how it relates to real social network data as in Facebook, and in particular FaceBook's own graph benchmark called LinkBench. We think SNB is the most intricate graph database benchmark to date (it's also available in RDF!), that already has made some waves. SNB recently receiv

Social Network Benchmark goals

  • Posted on: 24 July 2014
  • By: Josep Larriba Pey

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.

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