This guide covers starting FeatureBase using a Docker compose file. Kafka and Zookeeper are also run and a Python example file is provided to insert data into FeatureBase by sending the data to Kafka for ingestion.
If you want to run FeatureBase and Kafka from a terminal shell, you may follow this guide.
Clone the FeatureBase examples repo in a terminal and change into the docker-example directory:
git clone https://github.com/FeatureBaseDB/featurebase-examples.git
cd featurebase-examples/docker-example
Start the services using docker-compose:
docker-compose up -d
NOTE: If you have issues with docker compose, try disabling v2 by going into settings..general in Docker Desktop.
You should now have three containers running:
Before we can run the Python example, we'll need to install the requirements for running the insert code. Start a new terminal and run the following:
pip3 install -r requirements.txt
You may need to update pip:
pip3 install pip --upgrade
The final step is to run the Python script to insert data into Kafka, which will then be read by the Kafka consumer and inserted into FeatureBase:
% python3 main.py
200000 records inserted.
NOTE:
If you have changed the schema in schema.json, you will need to rebuild the FeatureBase container.
./build.sh
Kill the container in the Docker UI and then run the compose file again to restart FeatureBase:
docker-compose up -d
To check this worked, in your browser head over to http://0.0.0.0:10101 and run the following query:
select * from allyourbase limit 20;
To remove the deployment run the following:
docker-compose down
In the next guide, we'll be exploring inserting a LOT more data and setting up Python queries for doing some simple reporting and graphing, using a simple Flask server driving a UI.
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