The hugegraph-computer is a distributed graph processing system for hugegraph. It is an implementation of Pregel. It runs on Kubernetes or YARN framework.

• Support distributed MPP graph computing, and integrates with HugeGraph as graph input/output storage.
• Based on BSP(Bulk Synchronous Parallel) model, an algorithm performs computing through multiple parallel iterations, every iteration is a superstep.
• Auto memory management. The framework will never be OOM(Out of Memory) since it will split some data to disk if it doesn't have enough memory to hold all the data.
• The part of edges or the messages of super node can be in memory, so you will never lose it.
• You can load the data from HDFS or HugeGraph, output the results to HDFS or HugeGraph, or adapt any other systems manually as needed.
• Easy to develop a new algorithm. You just need to focus on a vertex only processing just like as in a single server, without worrying about message transfer and memory/storage management.

The project homepage contains more information about hugegraph-computer.

And here are links of other repositories:

1. hugegraph-server (graph's core component - OLTP server)
2. hugegraph-toolchain (include loader/dashboard/tool/client)
3. hugegraph-commons (include common & rpc module)
4. hugegraph-website (include doc & website code)

• If some classes under computer-k8s cannot be found, you need to execute mvn clean install in advance to generate corresponding classes.

Welcome to contribute, please see How to Contribute for more information

Note: It's recommended to use GitHub Desktop to greatly simplify the PR and commit process.

hugegraph-computer is licensed under Apache 2.0 License.

• GitHub Issues: Feedback on usage issues and functional requirements (quick response)
• Feedback Email: [email protected] (subscriber only)
• WeChat public account: Apache HugeGraph, welcome to scan this QR code to follow us.