feat(core): isolate namespace for different input data source (#252)
* set default job namespace to empty string
* use StringUtils.isEmpty
2 files changed
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:
- hugegraph-server (graph's core component - OLTP server)
- hugegraph-toolchain (include loader/dashboard/tool/client)
- hugegraph-commons (include common & rpc module)
- hugegraph-website (include doc & website code)
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.