update docker usage docs (#2856)

Author: typhoonzero

doc/quick_start.md

@@ -3,9 +3,14 @@
 It's quite simple to try out SQLFlow using [Docker](https://docs.docker.com/).
 
 1. Install [Docker Community Edition](https://docs.docker.com/install/).
-1. Run SQLflow by typing the command `docker run -it -p 8888:8888 sqlflow/sqlflow`.
-1. Access localhost:8888 in your Web browser.
-1. Open the notebook `iris-dnn.ipynb`.
+1. Run SQLflow by typing the below command:
+   ```bash
+   docker run --name=sqlflow-mysql -d -p 8888:8888 sqlflow/sqlflow:mysql
+   docker run --net=container:sqlflow-mysql -d sqlflow/sqlflow:latest sqlflowserver
+   docker run --net=container:sqlflow-mysql -d sqlflow/sqlflow:jupyter
+   ```
+1. Wait until the docker containers are all running, then access http://localhost:8888 in your Web browser.
+1. Open the a tutorial notebook like `iris-dnn.ipynb` and run the examples.
 
 
 For advanced usage, you might want to go on reading

doc/run/docker.md

@@ -1,30 +1,33 @@
 # Run SQLFlow Using Docker
 
-SQLFlow releases an "all-in-one" Docker image that contains the SQLFlow server, MySQL
+SQLFlow releases several Docker images that contains the SQLFlow server, MySQL
 server, sample datasets, Jupyter Notebook server, and the SQLFlow plugin for Jupyter.
 
-You can use this Docker image for either local trying out or production deployment.
+You can use these Docker images for either local trying out or production deployment.
 
 ## Preparation
 
 1. Install [Docker Community Edition](https://docs.docker.com/install/) on your PC/Macbook/Server.
-1. Pull the latest SQLFlow "all-in-one" Docker image. Or you can also 
+1. Pull the latest SQLFlow Docker images. Or you can also 
    build the Docker image from source code following [this guide](../build.md).
 
    ```
    docker pull sqlflow/sqlflow
+   docker pull sqlflow/sqlflow:mysql
+   docker pull sqlflow/sqlflow:jupyter
    ```
 
 ## Try Out SQLFlow Using Notebook
 
-1. Type the below command to start the container:
+1. Type the below command to start three containers to start a MySQL server, SQLFlow server and a Jupyter notebook server.
 
    ```
-   docker run --rm -it -p 8888:8888 sqlflow/sqlflow
+   docker run --name=sqlflow-mysql -d -p 8888:8888 sqlflow/sqlflow:mysql
+   docker run --net=container:sqlflow-mysql -d sqlflow/sqlflow:lateset sqlflowserver
+   docker run --net=container:sqlflow-mysql -d sqlflow/sqlflow:jupyter
    ```
-
-1. Open a web browser, go to `localhost:8888`, open `iris-dnn.ipynb` file, then you can
-   follow the tutorial and run the SQL statements to run the training and prediction.
+1. You can also use a specified version (e.g. `v0.4.0`) of the SQLFlow server by changing the second line above to `docker run --net=container:sqlflow-mysql -d sqlflow/sqlflow:v0.4.0 sqlflowserver`.
+1. Open a web browser, go to `localhost:8888`, open any tutorial notebook like  `iris-dnn.ipynb` file, then you can follow the tutorial and run the SQL statements to run the training and prediction.
 
 ## Connect to Your Own Database