streamingflow / dispel4py-server Goto Github PK

Open a new terminal with the new Laminar directory.

/data/Laminar> 

Clone the server application repository.

/data/Laminar> git clone https://github.com/StreamingFlow/dispel4py-server.git

Enter the server directory.

/data/Laminar> cd dispel4py-server

To manage permission issues, run:

/data/Laminar/dispel4py-server> chmod +x gradlew

To configure the required fields, navigate to /src/main/resources/application.properties and fill in the required variables

To run the server

/data/Laminar/dispel4py-server> ./gradlew bootRun

The server will now be running, and ready to receive requests. You should see this sample output

/data/Laminar/dispel4py-server>
...
com.dispel4py.rest.RestApplication: Started RestApplication in 66.905 seconds (JVM running for 69.911)
...

To run the application in a docker container follow these intstructions

Clone the server application repository.

/data/Laminar> git clone https://github.com/Laminar-2/dispel4py-server.git

Enter the server directory.

/data/Laminar> cd dispel4py-server

Run docker compose to load up the server and database. The first time we recommend to use --build flag.

docker compose up --build

Next time you could use:

docker compose up

If you need to rebuild the Docker containers (for instance, after making configuration changes), you can do so by following these steps:

First, bring down the running containers:

docker-compose down

Then, rebuild and start the containers:

docker-compose up --build

By following these steps, you can ensure that the server is properly configured and running efficiently.

You can also prune the data from the docker, if you need to:

 docker system prune -a

We recommend to do this step after docker-compose down and before docker-compose up --build. But be carreful, this will delete the full registry database information.

The laminar client offers a user-friendly interface for registering and managing Processing Elements (PEs) as well as stream-based dispel4py workflows. For detailed guidance on how to interact with the system, please refer to the user manual available on the project's wiki.

In addition, the laminar execution-engine is a critical component that must be installed, either locally or remotely, to facilitate the serverless execution of workflows.