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.

This …

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 …

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.

It is about to be showtime for LDBC. The initial installment of the …

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.

Getting and Configuring Hadoop

DATAGEN runs on top of hadoop 1.2.1 to be scale. …

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, …

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 :

• the dataset size - 50 million triples (LDBC-SPB50) * benchmark warmup …