https://github.com/ldbc/ldbc_graphalytics
Generic driver for LDBC Graphalytics implementation
https://github.com/ldbc/ldbc_graphalytics
graphalytics ldbc
Last synced: 3 months ago
JSON representation
Generic driver for LDBC Graphalytics implementation
- Host: GitHub
- URL: https://github.com/ldbc/ldbc_graphalytics
- Owner: ldbc
- License: apache-2.0
- Created: 2014-07-30T14:17:54.000Z (almost 12 years ago)
- Default Branch: main
- Last Pushed: 2024-12-19T12:46:30.000Z (over 1 year ago)
- Last Synced: 2025-05-25T14:05:25.106Z (about 1 year ago)
- Topics: graphalytics, ldbc
- Language: Java
- Homepage: https://ldbcouncil.org/benchmarks/graphalytics/
- Size: 2.67 MB
- Stars: 83
- Watchers: 11
- Forks: 34
- Open Issues: 28
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE
Awesome Lists containing this project
README
Graphalytics
A Big Data Benchmark For Graph-Processing Platforms
Graph processing is of increasing interest for many scientific areas and revenue-generating applications, such as social networking, bioinformatics, online retail, and online gaming. To address the growing diversity of graph datasets and graph-processing algorithms, developers and system integrators have created a large variety of graph-processing platforms, which we define as the combined hardware, software, and programming system that is being used to complete a graph processing task. **LDBC Graphalytics**, an industrial-grade benchmark under [LDBC](https://ldbcouncil.org), is developed to enable objective comparisons between graph processing platforms by using six representative graph algorithms, and a large variety of real-world and synthetic datasets. Visit [our website](https://ldbcouncil.org/benchmarks/graphalytics/) for the most recent updates of the Graphalytics project.
### Publication
Want to know more about Graphalytics? Read [our VLDB paper](https://www.vldb.org/pvldb/vol9/p1317-iosup.pdf) and the [specification](https://github.com/ldbc/ldbc_graphalytics_docs).
### Build & run your first benchmark
The Graphalytics provides platform drivers for the state-of-the-arts graph processing platforms. To start your first benchmark with Graphalytics, we recommend using our reference implementations:
[GraphBLAS](https://github.com/ldbc/ldbc_graphalytics_platforms_graphblas) and
[Umbra](https://github.com/ldbc/ldbc_graphalytics_platforms_umbra).
Our datasets are hosted publicly – see the [Graphalytics website](https://ldbcouncil.org/benchmarks/graphalytics/) for download instructions.
### Participate in competitions
LDBC Graphalytics hosts competitions for graph processing platforms. Are you interested in the state-of-the-art performance? To participate, reach out to Gabor Szarnyas and David Puroja. Our email addresses are under `firstname.lastname@ldbcouncil.org`.
### Building the project
The project uses the [Build Number Maven plug-in](https://www.mojohaus.org/buildnumber-maven-plugin/) to ensure reproducibility. Hence, builds fail if the local Git repository contains uncommitted changes.
To build & install locally regardless (for testing), run:
```bash
scripts/install-local.sh
```
### Deploying Maven artifacts
We use a manual process for deploying Maven artifacts for the Graphalytics framework.
1. Clone the [`graphalytics-mvn` repository](https://github.com/ldbc/graphalytics-mvn) next to the driver repository's directory.
2. In the driver repository, run:
```bash
scripts/package-mvn-artifacts.sh
```
3. Go to the `graphalytics-mvn` directory, check whether the JAR files are correct.
4. Add the newly created and updates files using git, then commit and push.
5. Wait for approx. 5 minutes for the deployment process to finish.