Docker Compose Deployment

Qiantong9/16/25About 3 min

Before We Start

Who Should Read This Guide?

Newcomers to qData who want to quickly experience its features
Users who don't want to deal with complex environment configurations or frontend builds
Users who prefer a "one-click start" for a hassle-free full-platform experience

We’ve prepared a ready-to-use deployment package for you, including:

✅ Frontend static resources (pre-built dist folder)
✅ DolphinScheduler (no additional installation required)
✅ Hadoop ecosystem (HDFS + YARN)
✅ Flink 1.12 and Spark 3.3.0 (already extracted)
✅ Pre-configured .env environment variable file
✅ Complete directory structure and image packages (no manual downloads required)

No need to manually install dependencies, build the frontend, or configure complex settings. Just extract and run the script—the entire big data platform and qData will be up and running!
Even beginners can easily set it up and experience qData in 10 minutes!

Step 1: Install Docker and Docker Compose

qData runs via Docker containers, so you must first install Docker and Docker Compose.

Recommended versions:
- Docker: ≥ 19.03
- Docker Compose: ≥ 1.28

🖥️ Windows / macOS

Download and install Docker Desktop.
After installation, Docker Compose is automatically included—no additional setup needed.

🐧 Linux (Ubuntu 18.04+)

The deployment package includes offline installers and installation scripts. Run the following:

# Enter Docker installation directory
cd ~/qData/docker-install

# Install Docker components
sudo dpkg -i containerd.io_1.6.9-1_amd64.deb docker-ce_24.0.7-1~ubuntu.20.04~focal_amd64.deb docker-ce-cli_24.0.7-1~ubuntu.20.04~focal_amd64.deb docker-compose-plugin_2.6.0~ubuntu-focal_amd64.deb

# Add current user to docker group (optional, to avoid sudo)
sudo usermod -aG docker $USER
newgrp docker

# Verify installation
sudo docker -v
# Example output: Docker version 24.0.7, build afdd5

Install Docker Compose:

# Grant execute permission and move to system path
sudo chmod +x docker-compose
sudo mv docker-compose /usr/local/bin/docker-compose

# Verify installation
sudo docker-compose -v
# Example output: Docker Compose version v2.20.2

Step 2: Download Deployment Package

🔗 Baidu Pan (Baidu Cloud Disk): https://pan.baidu.com/s/1QI0rWL8i9G-qYJFHTh19zA

🔑 Extraction Code: Join the QQ group to get the code
[Join QQ Group](https://qm.qq.com/q/Qz5NJut20y)
[Join QQ Group](https://qm.qq.com/q/Bpml33lTWK)

After downloading, extract the package (e.g., to ~/qData).

Step 3: Load qData Images

After extracting the package, go to the images folder and run the following commands to load images and verify successful import:

cd ~/qData(images)/images

# Load big data-related images
sudo docker load -i bigdata-images.tar

# Load main qData image (x.x.x is the version number)
sudo docker load -i qdata-x.x.x.tar

# View local image list to confirm successful import
sudo docker images

Expected output should include entries like:

REPOSITORY                             TAG                       IMAGE ID       CREATED         SIZE
qiantong/qdata-quality                 1.0.5                     0e3b87492cd8   4 hours ago     734MB
qiantong/qdata                         1.0.5                     59cf25909087   4 hours ago     760MB
apache/dolphinscheduler-tools          latest                    19eddd1bef1d   4 days ago      402MB
apache/dolphinscheduler-worker         latest                    fa746d141ae2   4 days ago      618MB
apache/dolphinscheduler-master         latest                    1f2294402261   5 days ago      573MB
apache/dolphinscheduler-alert-server   latest                    a8f4934125fb   5 days ago      423MB
apache/dolphinscheduler-api            latest                    c3f6757463c7   5 days ago      621MB
eclipse-temurin                        8-jdk                     139cd3f3ddf9   4 weeks ago     274MB
dm8                                    dm8_20250506_x86_rh7_64   54dae26a70ed   8 weeks ago     1.99GB
redis                                  6-alpine                  b7f611844a19   8 weeks ago     30.2MB
rabbitmq                               3.12-management           c48161165ad4   11 months ago   247MB
mongo                                  4.4                       d896c071ac69   18 months ago   427MB
bitnami/zookeeper                      3.7.1                     3ab0e8f032ab   23 months ago   510MB
apache/hadoop                          3.3.6                     3d418cee563e   2 years ago     1.66GB
bitnami/postgresql                     15.2.0                    52e3f8496daf   2 years ago     273MB
nginx                                  1.24.0                    6c0218f16876   2 years ago     142MB
bitnami/spark                          3                         15018b527afc   3 years ago     2.54GB

If images are not displayed, check the .tar file paths and ensure files are intact.

Step 4: Start qData

Inside the deployment package is a docker.zip archive. Extract it first.
After extraction, navigate to the ~/qData/docker directory (you'll find many .yml files here).

4.1 Initialize Database (Required for First-Time Run)

sudo docker-compose --profile schema up -d

⚠️ Note: Entrypoint Script Permission Issues
If the first command sudo docker-compose --profile schema up -d fails due to permission or Windows line-ending issues, run the following commands:

# Grant script permissions and fix line endings
cd ~/qData(location where package was extracted)
sudo chmod -R 755 docker
sudo chown -R $USER:$USER ./docker

sed -i 's/\r$//' ./database/dm8/entrypoint.sh

# Verify permissions
ls -l ./database/dm8/entrypoint.sh
# Should show: -rwxr-xr-x

# Run again
sudo docker-compose --profile schema up -d

4.2 Start qData and All Dependencies

sudo docker-compose --profile all up -d

4.3 Local Source Code Mode (Alternative)

# Skip steps 4.1 and 4.2 above
docker-compose --profile local up -d

⚠️ Note: Port Conflicts
If sudo docker-compose --profile all up -d reports port conflicts:

Close the processes occupying those ports on your server based on the error message;
Or modify the *.yaml files in the deployment package to comment out or remove port mappings (except port 80)—this won’t affect internal container operations.

4.4 Other Common Commands

View status of all services:

sudo docker-compose --profile all ps

Pause all qData services (data preserved):

sudo docker-compose --profile all stop

Restart all services:

sudo docker-compose --profile all restart

Shut down completely and remove data (restore to default environment):

sudo docker-compose --profile all down
sudo docker-compose --profile schema down

Start middleware required for local source mode:

docker-compose --profile local up -d

⚠️ down removes all data. Use stop if you wish to preserve data.

Deployment Complete! 🎉

After deployment, access the following URLs:

🌐 qData Data Mid-Platform
http://< server-IP >:80
Username: admin
Password: qData123
📅 Scheduler: DolphinScheduler
http://< server-IP >:12345/dolphinscheduler/ui/home
Username: admin
Password: dolphinscheduler123
⚡ Spark Dashboard
http://< server-IP >:8080/

🔑 Replace <server-IP> with your server's public or private IP address.

💡 Tips

After initial startup, wait 1–2 minutes for all containers to initialize.
Use docker ps to check container status.
If you can't access the services, verify that the server firewall allows port 80.