This project aims to simplify Modern ETL and Data Analytics Engine
Fork this repository by clicking on the fork button on the top of this page. This will create a copy of this repository in your account.
Now clone the forked repository to your machine. Go to your GitHub account, open the forked repository, click on the code button and then click the copy to clipboard icon.
Open a terminal and run the following git command:
git clone "url you just copied"
where "url you just copied" (without the quotation marks) is the url to this repository (your fork of this project). See the previous steps to obtain the url.
For example:
git clone https://github.com/YOUR-USERNAME/antimatter.git
where YOUR-USERNAME is your GitHub username. Here you're copying the contents of the first-contributions repository on GitHub to your computer.
Change to the repository directory on your computer (if you are not already there):
Run `cd antimatter`
Now create a branch using the git checkout command:
Run `git checkout <BRANCH_NAME>`
For example:
git checkout -b backend
If you go to the project directory and execute the command git status, you'll see there are changes.
Add those changes to the branch you just created using the git add command:
git add .
Now commit those changes using the git commit command:
git commit -m "Add <your-name> to the repository"
replacing <your-name> with your name.
Push your changes using the command git push:
git push origin <add-your-branch-name>
replacing <add-your-branch-name> with the name of the branch you created earlier.
If you go to your repository on GitHub, you'll see a Compare & pull request button. Click on that button.
Note: You need a linux environment to run this application.
First build the react app by running the below command
docker compose build antimatter
Now run the docker compose command to set up all services
docker compose up -d
Note: You may need to run chmod to give the necessary folder access to jitsu.
Now access the antimatter application on http://localhost:3000
Note: A minimum of 16GB RAM is required to start all the services at once. Insufficient RAM could result in crashing of the Docker daemon.