[latest PDF (2.2.1-SNAPSHOT)] [stable PDF (2.2.0)]
For a quick overview of LDBC SNB, start with our presentation.
For a guide on how to develop SNB Interactive implementations, please check out the README of the Interactive implementations repository.
The two SNB workloads are stored in different repositories:
- Interactive:
- Data generator (for versions 0.x and 1.x): https://github.com/ldbc/ldbc_snb_datagen_hadoop
- Data generator (for version 2.0): https://github.com/ldbc/ldbc_snb_datagen_spark
- Driver: https://github.com/ldbc/ldbc_snb_interactive_driver
- Reference implementations: https://github.com/ldbc/ldbc_snb_interactive_impls
- Business Intelligence (BI):
- Data generator: https://github.com/ldbc/ldbc_snb_datagen_spark
- Driver and reference implementations: https://github.com/ldbc/ldbc_snb_bi
- Social Network Benchmark:
- Detailed specification: The LDBC Social Network Benchmark by the LDBC Social Network Benchmark task force and contributors, arXiv/CoRR abs/2001.02299, 2020. [bib]
- BI workload: An early look at the LDBC Social Network Benchmark's Business Intelligence workload, GRADES-NDA at SIGMOD 2018 by G. Szárnyas et al. [bib]
- Interactive workload: The LDBC Social Network Benchmark: Interactive Workload, SIGMOD 2015 by O. Erling et al. [bib]
- Related benchmarks:
- LDBC Graphalytics: LDBC Graphalytics: A Benchmark for Large-Scale Graph Analysis on Parallel and Distributed Platforms, VLDB 2016 paper by A. Iosup et al. [bib], The LDBC Graphalytics Benchmark, technical report [bib]
- LDBC Semantic Publishing Benchmark: Benchmarking RDF Query Engines: The LDBC Semantic Publishing Benchmark, BLINK at ISWC 2016 by V. Kotsev et al. [bib]
- LSQB (Labelled Subgraph Query Benchmark): a microbenchmark focusing on subgraph queries (graph pattern matching) using labelled graphs produced by the LDBC data generator. [bib]
This repository contains the LaTeX source for the specification of the LDBC Social Network Benchmark. This README discusses how to build the specification PDF from source.
To get consistent formatting, query cards are generated from query specifications defined in YAML format. This is a necessary step to compile to the document.
Install Pandoc, Python, and the required packages:
scripts/install-dependencies.sh
To build the document locally, run make
or make texfot
. The latter requires Perl but produces a cleaner output.
We also provide a GitHub Action repository and a Docker container and images on Docker Hub. To use this locally, run:
docker run --rm --volume=`pwd`:"/github/workspace" ldbc/document-builder:2021 texfot query_cards workloads && sudo chown -R ${USER}:${USER} .