Getting started with LynxKite

  1. Fill out the form on the evaluation page.

  2. Click the “Try cloud version” button.

  3. Wait for your instance to start up. This can take a minute.

  4. You get to a JupyterLab interface. On the JupyterLab launcher you can find a big button to access the LynxKite UI, or you can check out some notebooks to see LynxKite’s Python API. Your LynxKite instance is preloaded with a series of example workspaces that implement our tutorials.

If something doesn’t work, let us know at lynxkite@lynxanalytics.com!

  1. Make sure you have Docker installed. (Supports both macOS and Linux.)

  2. Start the LynxKite Docker container:

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

    LynxKite stores metadata (such as your workspaces) and data (such as graphs) locally in the default configuration. Feel free to change lynxkite_meta and lynxkite_data in the example to store them under a different path.

    The KITE_MASTER_MEMORY_MB environment variable controls the amount of memory used by LynxKite. The default setting is 1 GB.

  3. After a few seconds you can navigate to http://localhost:2200/ and see the LynxKite UI.

If you cannot get it to work, let us know at lynxkite@lynxanalytics.com! If it does work, try LynxKite Tutorial: Flight Routes.

Docker Desktop supports 64-bit editions of Windows 10 with the exception of Home. For Windows 10 Home, please follow the LynxKite installation guide for Docker on other Windows instead.

  1. Download Docker Desktop for Windows. Run the installer and follow the on-screen instructions. If you get stuck, refer to the Docker Desktop installation guide for detailed instructions.

  2. Click the Docker Desktop icon and choose “Switch to Linux containers…”.

  3. LynxKite stores metadata (such as your workspaces) and data (such as graphs) locally in the default configuration. Create these directories in PowerShell. (Feel free to change lynxkite_meta and lynxkite_data in the example to store them under a different path):

     mkdir ~/lynxkite_meta
     mkdir ~/lynxkite_data
    
  4. Start the LynxKite Docker container:

    docker run `
      -p 2200:2200 `
      -v ~/lynxkite_meta:/metadata `
      -v ~/lynxkite_data:/data `
      -e KITE_MASTER_MEMORY_MB=1024 `
      --name lynxkite lynxkite/lynxkite
    

    The KITE_MASTER_MEMORY_MB environment variable controls the amount of memory used by LynxKite. The default setting is 1 GB.

  5. After a few seconds you can navigate to http://localhost:2200/ and see the LynxKite UI.

If you cannot get it to work, let us know at lynxkite@lynxanalytics.com! If it does work, try LynxKite Tutorial: Flight Routes.

  1. Download Docker Toolbox for Windows. Run the installer and follow the on-screen instructions. If you get stuck, refer to the Docker Toolbox installation guide for detailed instructions.

  2. Start the LynxKite Docker container:

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

    LynxKite stores metadata (such as your workspaces) and data (such as graphs) locally in the default configuration. Feel free to change lynxkite_meta and lynxkite_data in the example to store them under a different path.

    The KITE_MASTER_MEMORY_MB environment variable controls the amount of memory used by LynxKite. The default setting is 1 GB.

  3. After a few seconds you can navigate to http://192.168.99.100:2200/ and see the LynxKite UI.

If you cannot get it to work, let us know at lynxkite@lynxanalytics.com! If it does work, try LynxKite Tutorial: Flight Routes.

  1. Make sure you have Java 8 installed.

  2. Download LynxKite from the download page using the “Download for Linux” button.

  3. Extract the downloaded lynxkite-native-3.2.1.tgz file to a suitable directory:

    tar xf lynxkite-native-3.2.1.tgz
    
  4. Run the command lynxkite-native-3.2.1/tools/install_spark.sh. This will download Spark and extract it in your home directory.

  5. Using a text editor, write a .kiterc file in your home directory. It should contain at least the following lines:

    export SPARK_HOME=$HOME/spark-${SPARK_VERSION}
    export SPARK_MASTER=local
    export KITE_META_DIR=$HOME/lynxkite_meta
    export KITE_DATA_DIR=file:$HOME/lynxkite_data/
    export KITE_USERS_FILE=$HOME/lynxkite_users.txt
    export KITE_PID_FILE=$HOME/kite.pid
    export NUM_CORES_PER_EXECUTOR=*
    export KITE_MASTER_MEMORY_MB=4000
    export KITE_HTTP_PORT=2200
    

    The above values are just some sensible defaults. You can look up what they and various other settings mean in the Admin Manual.

  6. Run LynxKite:

    lynxkite-native-3.2.1/bin/biggraph interactive
    
  7. After a few seconds you can navigate to http://localhost:2200/ and see the LynxKite UI.

  8. If you want to use advanced machine learning boxes in LynxKite, install our Python dependencies, PyArrow and PyTorch Geometric.

If you cannot get it to work, let us know at lynxkite@lynxanalytics.com! If it does work, try LynxKite Tutorial: Flight Routes.