Open scotty-tarvan opened 1 year ago
For that you would have to transform the dataframe before writing it using normal spark, like this:
column_mapping = {"col1_name": "Col1Name", "col2_name": "Col2Name"}
for old_name, new_name in column_mapping.items():
df = df.withColumnRenamed(old_name, new_name)
Hello,
Im using a python synapse notebook and cant figure out how to pass column mappings to the bulk copy. We have to ensure that the dataframe schema matches the target table 100% else it fails.
Is this possible?
Sample code below.