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Zappandy/ice_sheets_bigData

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How to set up the system

Run all the docker commands from the root directory of the repository

docker network create kafka-network 

Build all the containers. The visualization is not functional, so it does not need to be built and started.

docker-compose -f kafka/docker-compose.yml build
docker-compose -f producers/docker-compose.yml build
docker-compose -f consumers/caribou_split_processor/docker-compose.yml build
docker-compose -f consumers/ice_sheets_predictor/docker-compose.yml build
docker-compose -f manual_cass_sinks/docker-compose.yml build
(docker-compose-f visualization/docker-compose build)

This can take a while as the data sources are downloaded to the images when building. If there's warnings about variables not being set, pass the flag --env-file .env, this is a must if running from WSL and not in Unix-based systems. This has not been tested with VMs.

First, start the message broker and the database by running

docker-compose -f kafka/docker-compose.yml up -d 

Sometimes the message broker container does not start up correctly. Simply check if it is running and then restart if necessary

docker ps
docker-compose -f kafka/docker-compose.yml up -d broker init-kafka

and it should start up without problems. Wait a couple of minutes, until everything is running (cassandra is slow to start up)

Finally, set up the other components of the stream processing system

docker-compose -f consumers/caribou_split_processor/docker-compose.yml up -d
docker-compose -f consumers/ice_sheets_predictor/docker-compose.yml up -d
docker-compose -f manual_cass_sinks/docker-compose.yml up -d
docker-compose -f producers/docker-compose.yml up -d

The producers start streaming messages immediately on startup.

If you want to control the producers, there is a control topic registered with kafka. By sending commands to this topic, the producers can be stopped and their speed can be adjusted. Some example commands are listed in the README under the producers directory: README. In order to use them, run a local kafka-console-producer and send the JSON commands to the "control" topic.

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