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Interactive Workload

8th TUC Meeting - Social Network Benchmark: Interactive Workload

  • Posted on: 20 December 2016
  • By: Adrian Diaz

Arnau Prat, Lead Researcher at DAMA-UPC from the Technological University of Catalonia presented a talk on the Interactive Workload of the Social Network Benchmark. One of the key aspects of his talk was the introduction of the SNB Data Generator, tool that generates a Facebook-degree social network distribution (groups, posts, likes…). This synthetic social network follows the principle of homophily, isn’t uniform and allows a fair comparison and reproducibility of benchmark executions while being also scalable by using Apache Hadoop.

LDBC participates in the 36th edition of the ACM SIGMOD/PODS conference

  • Posted on: 25 May 2015
  • By: Damaris Coll

LDBC is presenting two papers at the next edition of the ACM SIGMOD/PODS conference held in Melbourne from May 31st to June 4th, 2015. The annual SCM SIGMOD/PODS conference is a leading international forum for database researchers, practitioners, developers, and users to explore cutting-edge ideas and results, and to exchange techniques, tools and experiences.

SNB Interactive Part 1 - What is SNB Interactive Really About?

  • Posted on: 14 May 2015
  • By: Orri Erling

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.    

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.

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