[PDF]

For a quick overview of LDBC SNB, start with our presentation.

For a guide on how to develop benchmark implementations, please check out the benchmark workflow file.

The two SNB workloads (Interactive/BI) are stored in different repositories:

• Interactive:
  • Data generator: https://github.com/ldbc/ldbc_snb_datagen_hadoop
  • Driver: https://github.com/ldbc/ldbc_snb_driver
  • Implementations: https://github.com/ldbc/ldbc_snb_interactive
• BI:
  • Data generator: https://github.com/ldbc/ldbc_snb_datagen_spark
  • Driver and implementations: https://github.com/ldbc/ldbc_snb_bi

• Social Network Benchmark:
  • Detailed specification: The LDBC Social Network Benchmark (version 0.3.3) by the LDBC Social Network Benchmark task force, 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.

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 and Python3 following dependencies:

sudo apt-get install -y pandoc
sudo apt-get install -y python3 python3-pip python3-setuptools
pip3 install -r requirements.txt

To build the document, run make or make texfot. The latter requires Perl but gives you a cleaner output.

We also provide an image on Docker Hub for building the document. To use it, run:

docker run -v `pwd`/:/mnt/ ldbc/docs /bin/bash -c \
  "cd /mnt/ && ./generate-tex.py && make generate_query_cards texfot compile_query_cards"; \
  sudo chown -R $USER:$USER .

You can also compile the image manually by issuing:

docker build . --tag ldbc/docs