snowflake.snowpark.functions.sort_array¶
- snowflake.snowpark.functions.sort_array(array: Union[Column, str], sort_ascending: Optional[bool] = True, nulls_first: Optional[bool] = False) Column[source]¶
Returns rows of array column in sorted order. Users can choose the sort order and decide where to keep null elements.
- Parameters:
array – name of the column or column element which describes the column
sort_ascending – Boolean that decides if array elements are sorted in ascending order. Defaults to True.
nulls_first – Boolean that decides if SQL null elements will be placed in the beginning of the array. Note that this does not affect JSON null. Defaults to False.
- Examples::
- Behavior with SQL nulls:
>>> df = session.sql("select array_construct(20, 0, null, 10) as A") >>> df.select(array_sort(df.a).as_("sorted_a")).show() --------------- |"SORTED_A" | --------------- |[ | | 0, | | 10, | | 20, | | undefined | |] | --------------- >>> df.select(array_sort(df.a, False).as_("sorted_a")).show() --------------- |"SORTED_A" | --------------- |[ | | 20, | | 10, | | 0, | | undefined | |] | --------------- >>> df.select(array_sort(df.a, False, True).as_("sorted_a")).show() ---------------- |"SORTED_A" | ---------------- |[ | | undefined, | | 20, | | 10, | | 0 | |] | ----------------
- Behavior with JSON nulls:
>>> df = session.create_dataframe([[[20, 0, None, 10]]], schema=["a"]) >>> df.select(array_sort(df.a, False, False).as_("sorted_a")).show() -------------- |"SORTED_A" | -------------- |[ | | null, | | 20, | | 10, | | 0 | |] | -------------- >>> df.select(array_sort(df.a, False, True).as_("sorted_a")).show() -------------- |"SORTED_A" | -------------- |[ | | null, | | 20, | | 10, | | 0 | |] | --------------
See also