The framework allows you to store data into node and edges and creates edges as based on logic you can provide. The framework has visualization of metadata nodes and datanodes.

It is built using following

• pyspark
• cytoscape-js
• jupyter notebook
• backend graph engine is using neo4j
• python flask

The framework can be execute as part of docker containers

After checking out repo. Go to the local repo directory cd GnanaPath

# run docker build # docker build -t gnpath .

After the docker image is created run the image

#docker run -d -p 5050:5050 --name gnpath_server gnpath:latest

After that open browser http://:5050

Login/passwd: gnadmin/gnana

You can continue from "Connecting to backend Neo4j Server" section below

• Download and install jupyter/pyspark notebook or get docker container from https://hub.docker.com/r/jupyter/pyspark-notebook/

• If you choose docker container for notebook, then make sure you port map for 5050 for Gnana UI Example: # docker run -d -p 8888:8888 -p 5050:5050 --name jupyntbook jupyter/pyspark-notebook

• Open terminal on the notebook and git clone GnanaPath repo

# git clone https://github.com/Datalyrix/GnanaPath.git

• Install python related modules for this project

# pip install -r gnpappsrv/requirements.txt

We have used community edition of neo4j container to setup. For other options please visit http://neo4j.com

Please refer link to install neo4j as container https://github.com/neo4j/docker-neo4j

get Bolt port (ex: 7687) and user credentials (user/passw) for GnanaUI to connect

cd gnpappsrv

python gnpappsrv

You should see log like:

• Serving Flask app "gnp_appsrv_main" (lazy loading)
• Environment: production WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead.
• Debug mode: on
• Running on http://0.0.0.0:5050/ (Press CTRL+C to quit)
• Restarting with stat
• Debugger is active!
• Debugger PIN: XXX-XXX-XXX

Now open browser go to http://:5050 You can GnanaPath UI and click login Default user/passwd (gnadmin/gnana)

After you login into GnanaPath UI,

• click connect

• Enter Neo4j Server IP and Bolt Protocol port(ex: 7687) Ex: XXX.XXX.XXX.XXX:7687

• Enter username and password Click connect, if you connection is successful you will see success status message

Now you are ready to upload the data**

Currently, we support simple file upload using csv or json. we donot yet support nested json files.

• Click Upload on top menu options on GnanaPath UI

• Upload file from local file path

• After upload is complete, you will see upload success message

note currently csv file header line (line 1) is treated as meta data header.

Click MetaView on top men option to view meta nodes created from file upload and SearchView to view data nodes.

We have lot of todo list for this project and will be updating in this section.

• pyspark-based graph engine

• GnanaPath Team