Kafka Link Prediction
This repo contains code that supports Confluent Blog post explaining how to use Neo4j together with Kafka.
The purpose of this code is to give a worked example of how to use the two together in a simple scenario, running inside of Docker. This example assumes that you have a working Confluent Cloud instance.
Setup the "fakestream" module for simulating data sent to Kafka:
git submodule sync
cd fakestream && pipenv install
Set up your topics in Kafka:
- Create a topic called "recommendations"
- Create a topic called "friends"
The "out of the box" configuration assumes you are using Confluent Cloud.
Export your configuration from confluent cloud and start the Neo4j server:
export CONFLUENT_API_KEY=(your value) export CONFLUENT_API_SECRET=(your value) export KAFKA_BOOTSTRAP_SERVERS=(your value) docker-compose up
If you are not using Confluent Cloud and running Kafka locally
Inspect docker-compose.yml, uncomment the correct section, and put in your configuration.
Stream Data to Neo4j
Have a look at the
run-stream.sh shell script for how to use fakestream to start a stream
of friend requests.
Run the Examples
Take a look at the cypher files in this directory to follow along with examples from the blog post.