Use materialize() function to persist a teradataml dataframe, created for lazy operations on a teradataml DataFrame, into a database for the current session, in the form of a view.
Example Setup
>>> load_example_data("dataframe", "admissions_train") >>> df = DataFrame("admissions_train") >>> df
masters gpa stats programming admitted id 13 no 4.00 Advanced Novice 1 26 yes 3.57 Advanced Advanced 1 5 no 3.44 Novice Novice 0 19 yes 1.98 Advanced Advanced 0 15 yes 4.00 Advanced Advanced 1 40 yes 3.95 Novice Beginner 0 7 yes 2.33 Novice Novice 1 22 yes 3.46 Novice Beginner 0 36 no 3.00 Advanced Novice 0 38 yes 2.65 Advanced Beginner 1
Example 1: Perform lazy DataFrame operation and manually materialize the view
>>> df2 = df.get([["id", "masters", "gpa"]])
Initially, the table name will be None.
>>> df2._table_name
>>> df2.materialize()
masters gpa id 15 yes 4.00 7 yes 2.33 22 yes 3.46 17 no 3.83 13 no 4.00 38 yes 2.65 26 yes 3.57 5 no 3.44 34 yes 3.85 40 yes 3.95
After materialize(), view name will be assigned.
>>> df2._table_name '"ALICE"."ml__select__172077355985236"' >>>