Installation

• Install on your Macbook.
• Pull the latest SQLFlow “all-in-one” Docker image, which contains pre-built SQLFlowbinary, sample datasets (under ), and jupyter notebook.

• Open a web browser, go to localhost:8888 and paste the token output from Notebook command above. Select the “New” drop-down menu on the right side, and open the “Python 3” development environment in a new Notebook cell (also in a new tab). In the new cell, type in below SELECT statement to fetch 5 records from train table in Iris database.

• Now you’ve successfully tested SQLFlow installation and written some SQL from Jupyter Notebook. Just as shown in the Quick Overview, you can continue your SQLFlow journey in the command line setting. Also feel free to check out more if you are new to Jupyter Notebook.

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

• After data is popularized in MySQL, let’s test the installation by running a query in Jupyter Notebook. If you are using Docker for Linux, please change to localhost:3306. If you are connecting to a remote database, please make sure to change to the remote address.

If you are running MySQL on remote, please be aware that MySQL only allows connections from localhost by default. Fix can be found here.