lynxkite/lynxkite repository overview

Quick try:

docker run --rm -p2200:2200 lynxkite/lynxkite

Setup with persistent data:

docker run \
  -p 2200:2200 \
  -v ~/lynxkite/meta:/metadata -v ~/lynxkite/data:/data \
  -e KITE_MASTER_MEMORY_MB=1024 \
  --name lynxkite lynxkite/lynxkite

⁠LynxKite

LynxKite⁠ is a powerful open-source analytics tool for very large graphs and other datasets. It scales to billions of edges thanks to the underlying Apache Spark cluster computing engine. It seamlessly combines the benefits of a friendly graphical interface and a powerful Python API.

• Hundreds of scalable graph operations, including graph metrics like PageRank, embeddedness, and centrality, machine learning methods including GCNs⁠, graph segmentations like modular clustering, and various transformation tools like aggregations on neighborhoods.
• The two main data types are graphs and relational tables. Switch back and forth between the two as needed to describe complex logical flows. Run SQL on both.
• A friendly web UI for building powerful pipelines of operation boxes. Define your own custom boxes to structure your logic.
• Tight integration with Python lets you implement custom transformations or create whole workflows through a simple API.
• Integrates with the Hadoop ecosystem. Import and export from CSV, JSON, Parquet, ORC, JDBC, Hive, or Neo4j.
• Fully documented.⁠
• Proven in production on large clusters and real datasets.
• Fully configurable graph visualizations and statistical plots. Experimental 3D and ray-traced graph renderings.

⁠Using a GPU

Some algorithms in LynxKite can take advantage of NVIDIA GPUs. This is also supported through Docker, you just need to install the NVIDIA Container Toolkit⁠ and run the CUDA build of the LynxKite image:

docker run \
  -p 2200:2200 \
  --gpus all \
  --name lynxkite lynxkite/lynxkite:latest-cuda