What kind of advance we get when running this line in our project.

Hi David, the readme has a little more information: https://github.com/dagster-io/dagster/blob/master/examples/basic_pyspark/README.md

dagster_pyspark.DataFrame

, which is a 

DagsterType

 knows how to save and load PySpark DataFrames. 

make_python_type_usable_as_dagster_type

 tells Dagster that when a solid has a return type annotation for a, 

pyspark.sql.DataFrame

, then Dagster should use the 

dagster_pyspark.DataFrame

 to save and load it.

Does that answer your question? There are a bunch of concepts involved - I can explain in more detail if it would be helpful

We wanna know if we are using our own load and save functions, did we also need to run this line.

Would you be able to share a code snippet? That line should only be required if your solid function returns a Spark DataFrame and you expect Dagster to save it for you.

Ok, thanks. We don't use dagster to save DataFrame.