I've encountered the same warning when running this notebook from DA.

https://github.com/databricks-academy/scalable-machine-learning-with-apache-spark-english/blob/publi...

I've managed to get rid of that warning by explicitly defining the argument `conda_env=mlflow.spark.get_default_conda_env()` in `mlflow.spark.log_model()`

The documentation reads

conda_env – Either a dictionary representation of a Conda environment or the path to a Conda environment yaml file. If provided, this decsribes the environment this model should be run in. At minimum, it should specify the dependencies contained in get_default_conda_env(). If None, the default get_default_conda_env() environment is added to the model. 

So I'm not sure why my solution works.

The doc also reads

The following arguments can’t be specified at the same time:

• conda_env
• pip_requirements
• extra_pip_requirements

So I wonder if there is special inference rule when all three are None by default.