Skip to content

docker.md

Latest commit

 

History

History
39 lines (24 loc) · 1.3 KB

docker.md

File metadata and controls

39 lines (24 loc) · 1.3 KB

Run SQLFlow Using Docker

SQLFlow releases an "all-in-one" Docker image 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.

Preparation

  1. Install Docker Community Edition on your PC/Macbook/Server.

  2. Pull the latest SQLFlow "all-in-one" Docker image. Or you can also build the Docker image from source code following this guide.

    docker pull sqlflow/sqlflow

Try Out SQLFlow Using Notebook

  1. Type the below command to start the container:

    docker run --rm -it -p 8888:8888 sqlflow/sqlflow

  2. 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.

Connect to Your Own Database

If you have your own database setup, below steps enables running a separated SQLFlow server and Jupyter Notebook which connects to your own database service.

For MySQL, please refer to run_with_mysql.

For Hive, please refer to run_with_hive.

For MaxCompute, please refer to run_with_maxcompute.