This notebook requires running examples/02_model_content_based_filtering/mmlspark_lightgbm_criteo.ipynb first on Databricks
The latter fails on Databricks (although it succeeds on Linux) at the load_spark_df() call.
Expected behavior (i.e. solution)
The notebooks should complete successfully on Jupyter (als_movie_o16n.ipynb) and Databricks (mmlspark_lightgbm_criteo.ipynb, lightgbm_criteo_o16n.ipynb).
To this end, the code should be rewritten to be consistent with the latest AzureML SDK and Databricks.
Description
Running notebooks
examples/05_operationalize/als_movie_o16n.ipynb
andexamples/05_operationalize/lightgbm_criteo_o16n.ipynb
fails in different ways.It seems that the code is not in sync with the version of AzureML SDK prescribed in the conda env.
In which platform does it happen?
How do we replicate the issue?
examples/05_operationalize/als_movie_o16n.ipynb
az login
)Workspace.create()
failsexamples/05_operationalize/lightgbm_criteo_o16n.ipynb
examples/02_model_content_based_filtering/mmlspark_lightgbm_criteo.ipynb
first on Databricksload_spark_df()
call.Expected behavior (i.e. solution)
The notebooks should complete successfully on Jupyter (
als_movie_o16n.ipynb
) and Databricks (mmlspark_lightgbm_criteo.ipynb, lightgbm_criteo_o16n.ipynb
).To this end, the code should be rewritten to be consistent with the latest AzureML SDK and Databricks.
Other Comments