Snowtire is a docker image which aims to provide Snowflake users with a turn key docker environment already set-up with Snowflake drivers of the version of your choice with a comprehensive data science environment including Jupyter Notebooks, Python, Spark, R to experiment the various Snowflake connectors available:

• ODBC
• JDBC
• Python Connector
• Spark Connector
• SnowSQL Client.

SQL Alchemy python package is also installed as part of this docker image.

The base docker image is Jupyter Docker Stacks. More specifically, the image used is jupyter/all-spark-notebook which provides a comprehensive jupyter environment including r, sci-py, pyspark and scala.

NOTE: Snowtire is not officially supported by Snowflake, and is provided as-is.

• You need git on your Mac.
• You need to download and install Docker Desktop for Mac. You may need to create an account on Docker to be able to download it.

Change the Directory to a location where you are storing your Docker images:

mkdir DockerImages
cd DockerImages
git clone https://github.com/zoharsan/snowtire.git
cd snowtire

If you are just updating the repository to the latest version (always recommended before building a docker image). Run the following command from within your local clone (under snowtire directory):

git pull

First check the latest clients available in the official Snowflake documentation

Once you have chosen the versions, you can customize the line 26 in the Dockerfile. For example:

RUN odbc_version=2.21.1 jdbc_version=3.12.3 spark_version=2.7.0-spark_2.4 snowsql_version=1.2.5 /deploy_snowflake.sh

NOTE: SnowSQL CLI has the ability to auto-upgrade to the latest version available. So, you may not need to specify a higher version.

docker build --pull -t snowtire .

You may get some warnings which are non critical, and/or expected. You can safely ignore them:

...
debconf: delaying package configuration, since apt-utils is not installed
...
==> WARNING: A newer version of conda exists. <==
  current version: 4.6.14
  latest version: 4.7.5

Please update conda by running

    $ conda update -n base conda
...
grep: /etc/odbcinst.ini: No such file or directory
...
grep: /etc/odbc.ini: No such file or directory

You should see the following message at the very end:

Successfully tagged snowtire:latest

docker run -p 8888:8888 --name spare-0 snowtire:latest

If the port 8888 is already taken on your laptop, and you want to use another port, you can simply change the port mapping. For example, for port 9999, it would be:

docker run -p 9999:8888 --name spare-1 snowtire:latest

You should see a message like the following the very first time you bring up this image. Copy the token value in the URL:

[I 23:33:42.828 NotebookApp] Writing notebook server cookie secret to /home/jovyan/.local/share/jupyter/runtime/notebook_cookie_secret
[I 23:33:43.820 NotebookApp] JupyterLab extension loaded from /opt/conda/lib/python3.7/site-packages/jupyterlab
[I 23:33:43.820 NotebookApp] JupyterLab application directory is /opt/conda/share/jupyter/lab
[I 23:33:43.822 NotebookApp] Serving notebooks from local directory: /home/jovyan
[I 23:33:43.822 NotebookApp] The Jupyter Notebook is running at:
[I 23:33:43.822 NotebookApp] http://(a8e53cbad3a0 or 127.0.0.1):8888/?token=eb2222f1a8cd14046ecc5177d4b1b5965446e3c34b8f42ad
[I 23:33:43.822 NotebookApp] Use Control-C to stop this server and shut down all kernels (twice to skip confirmation).
[C 23:33:43.826 NotebookApp] 
    
    To access the notebook, open this file in a browser:
        file:///home/jovyan/.local/share/jupyter/runtime/nbserver-17-open.html
    Or copy and paste one of these URLs:
        http://(a8e53cbad3a0 or 127.0.0.1):8888/?token=eb2222f1a8cd14046ecc5177d4b1b5965446e3c34b8f42ad

Note: If you are restarting the image, and you need to retrieve the token you can retrieve it as following:

• Retrieve its value from the docker logs as following:

docker logs spare-0 --tail 10

• Open a bash session on the docker container

docker exec -it spare-0 /bin/bash

Then run the following command:

jupyter notebook list

Open a web browser on: http://localhost:8888

It will prompt you for a Password or token. Enter the token you have in the previous message.

Snowtire come with 4 different small examples of python notebooks allowing to test various connectors including odbc, jdbc, spark. You will need to customize your Snowflake account name, your credentials (user/password), database name and warehouse.

You can always upload to the jupyter environment any demo notebook from the main interface. See the Upload button at the top right:

These notebooks can work with the tpch_sf1 database which is provided as a sample within any Snowflake environment.

If you plan to develop new notebooks within the Docker environment, in order to avoid losing any work due to a Docker container discarded accidentally or any other container corruption, it is recommended to always keep a local copy of your work once you are done. This can be done in the Jupyter menu: File->Download as.

Once finished, you can stop the image with the following command:

docker stop spare-0

If you want to resume work, you can start the image with the following command:

docker start spare-0

• To delete the image. WARNING: If you do this, you will lose any notebook, and any work you have saved or done within the container.

docker rm spare-0

• To open a bash session on the docker container, which will be useful to use the snowsql interface:

docker exec -it spare-0 /bin/bash

• To copy files in the docker container:

docker cp <absolute-file-name> spare-0:<absolute-path-name in the container>
Example: docker cp README.md spare-0:/

• To list all docker containers available:

docker ps -a

Make sure you have enough memory allocated for your Docker Workstation, at least 4 GB. On Mac:

• Stop all your docker images (See instructions above to stop/start docker images).
• Click on the Docker Icon on the top right hand side of your Mac Menu bar.
• Select Preferences
• Select Resources
• Set CPUs to minimum of 2.
• Set Memory to 4 GB.
• Click on Apply & Restart.

In case you have the Python kernel dying while running the notebook, and you want to troubleshoot the root cause, please add these lines as your first paragraph of your notebook and execute the paragraph:

# Debugging

import logging
import os
  
for logger_name in ['snowflake','botocore','azure']:
    logger = logging.getLogger(logger_name)
    logger.setLevel(logging.DEBUG)
    ch = logging.FileHandler('python_connector.log')
    ch.setLevel(logging.DEBUG)
    ch.setFormatter(logging.Formatter('%(asctime)s - %(threadName)s %(filename)s:%(lineno)d - %(funcName)s() - %(levelname)s - %(message)s'))
    logger.addHandler(ch)

This will generate a python_connector.log file where the notebook resides. Use the commands above to ssh into the image and examine the log.

Please check known issues log for known issues with Snowtire.