When I tried to access specific version data and set the arguments value to the specific number, I get all version data.
data1 = delta_sharing.load_table_changes_as_spark(table_url, starting_version=1, ending_version=1)
data2 = delta_sharing.load_table_changes_as_spark(table_url, starting_version=2, ending_version=2)
Here data1 and data2 gives the same data. When I check the same version data using load_table_changes_as_pandas(), it gives specific version data.
data1 = delta_sharing.load_table_changes_as_pandas(table_url, starting_version=1, ending_version=1)
data2 = delta_sharing.load_table_changes_as_pandas(table_url, starting_version=2, ending_version=2)
In the pandas scenario, data1 is having version 1 data and data2 is having version 2 data. Both of these, data1 and data2, are having different data which was as expected.
What we have to do to get the specific version data in spark dataframe using load_table_changes_as_spark function?
