143 lines
5.3 KiB
Markdown
143 lines
5.3 KiB
Markdown
# Docker User Guide
|
||
|
||
---
|
||
|
||
### **1. Pull Docker Image**
|
||
|
||
You may pull a Docker image from the [Analytics Zoo Docker Hub](https://hub.docker.com/r/intelanalytics/analytics-zoo).
|
||
|
||
To pull the nightly build version, use
|
||
```bash
|
||
sudo docker pull intelanalytics/analytics-zoo:latest
|
||
```
|
||
|
||
To pull other versions, please refer to [Analytics Zoo Docker Hub Tags](https://hub.docker.com/r/intelanalytics/analytics-zoo/tags?page=1&ordering=last_updated), select a tag and use
|
||
```bash
|
||
sudo docker pull intelanalytics/analytics-zoo:tag_name
|
||
```
|
||
|
||
**Configuring resources**
|
||
|
||
For Docker Desktop users, the default resources (2 CPUs and 2GB memory) are relatively small, and you may want to change them to larger values (8GB memory and 4 CPUs should be a good estimate for most examples, and the exact memory requirements vary for different applications). For more information, view the Docker documentation for [MacOS](https://docs.docker.com/docker-for-mac/#resources) and [Windows](https://docs.docker.com/docker-for-windows/#resources).
|
||
|
||
**Speed up pulling image by adding mirrors**
|
||
|
||
To speed up pulling the image from DockerHub, you may add the registry-mirrors key and value by editing `daemon.json` (located in `/etc/docker/` folder on Linux):
|
||
```
|
||
{
|
||
"registry-mirrors": ["https://<my-docker-mirror-host>"]
|
||
}
|
||
```
|
||
For instance, users in China may add the USTC mirror as follows:
|
||
```
|
||
{
|
||
"registry-mirrors": ["https://docker.mirrors.ustc.edu.cn"]
|
||
}
|
||
```
|
||
|
||
|
||
After that, flush changes and restart docker：
|
||
|
||
```
|
||
sudo systemctl daemon-reload
|
||
sudo systemctl restart docker
|
||
```
|
||
|
||
### **2. Launch Docker Container**
|
||
|
||
After pulling the Analytics Zoo Docker image, you can launch an Analytics Zoo Docker container:
|
||
```
|
||
sudo docker run -it --rm --net=host \
|
||
-e NOTEBOOK_PORT=12345 \
|
||
-e NOTEBOOK_TOKEN="your-token" \
|
||
-e http_proxy=http://your-proxy-host:your-proxy-port \
|
||
-e https_proxy=https://your-proxy-host:your-proxy-port \
|
||
intelanalytics/analytics-zoo:latest bash
|
||
```
|
||
|
||
* The value 12345 is a user specified port number.
|
||
* The value "your-token" is a user specified string.
|
||
* If you need to use http/https proxy, please use -e http_proxy/https_proxy
|
||
|
||
Once the container is successfully launched, you will automatically login into the container and see this as the output:
|
||
```
|
||
root@[hostname]:/opt/work#
|
||
```
|
||
|
||
The /opt/work directory contains:
|
||
|
||
* download-analytics-zoo.sh is used for downloading Analytics-Zoo distributions.
|
||
* start-notebook.sh is used for starting the jupyter notebook. You can specify the environment settings and spark settings to start a specified jupyter notebook.
|
||
* analytics-Zoo-${ANALYTICS_ZOO_VERSION} is the Analytics-Zoo home of Analytics-Zoo distribution.
|
||
* analytics-zoo-SPARK_x.x-x.x.x-dist.zip is the zip file of Analytics-Zoo distribution.
|
||
* spark-${SPARK_VERSION} is the Spark home.
|
||
* analytics-zoo is cloned from https://github.com/intel-analytics/analytics-zoo, contains apps, examples using analytics-zoo.
|
||
|
||
### **3. Run Jupyter Notebook Examples in the Container**
|
||
|
||
After a Docker container is launched and user login into the container, you can start the Jupyter Notebook service inside the container.
|
||
|
||
#### **3.1 Start the Jupyter Notebook services**
|
||
|
||
In the `/opt/work` directory, run this command line to start the Jupyter Notebook service:
|
||
```
|
||
./start-notebook.sh
|
||
```
|
||
|
||
You will see the output message like below. This means the Jupyter Notebook service has started successfully within the container.
|
||
```
|
||
[I 01:04:45.625 NotebookApp] Serving notebooks from local directory: /opt/work/analytics-zoo-0.5.0-SNAPSHOT/apps
|
||
[I 01:04:45.625 NotebookApp] The Jupyter Notebook is running at:
|
||
[I 01:04:45.625 NotebookApp] http://(the-host-name or 127.0.0.1):12345/?token=...
|
||
[I 01:04:45.625 NotebookApp] Use Control-C to stop this server and shut down all kernels (twice to skip confirmation).
|
||
```
|
||
|
||
#### **3.2 Connect to Jupyter Notebook service from a browser**
|
||
|
||
After the Jupyter Notebook service is successfully started, you can connect to the Jupyter Notebook service from a browser.
|
||
|
||
1. Get the IP address of the container
|
||
2. Launch a browser, and connect to the Jupyter Notebook service with the URL: https://container-ip-address:port-number/?token=your-token
|
||
As a result, you will see the Jupyter Notebook like this:
|
||
|
||
|
||
|
||
#### **3.3 Run Analytics Zoo Jupyter Notebooks**
|
||
|
||
After connecting to the Jupyter Notebook in the browser, you can run multiple Analytics Zoo Jupyter Notebook examples. The example shown below is the “dogs-vs-cats”.
|
||
|
||
* Click into the "dogs-vs-cats" folder:
|
||
|
||
|
||
|
||
* Open the notebook file:
|
||
|
||
|
||
|
||
* Start to run the "dogs-vs-cats" notebook:
|
||
|
||
|
||
|
||
* Run through the example and check the prediction:
|
||
|
||
|
||
|
||
### **4. Shut Down Docker Container**
|
||
|
||
You should shut down the Analytics Zoo Docker container after using it.
|
||
|
||
1. You can list all the active Docker containers by command line:
|
||
```
|
||
sudo docker ps
|
||
```
|
||
|
||
2. You will see your docker containers:
|
||
```
|
||
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
|
||
40de2cdad025 intelanalytics/analytics-zoo:latest "/opt/work/start-n..." 3 hours ago Up 3 hours upbeat_al
|
||
```
|
||
|
||
3. Shut down the corresponding docker container by its ID:
|
||
```
|
||
$sudo docker rm -f 40de2cdad025
|
||
```
|