Currently it's not straightforward to construct a MonthDayNanoIntervalArray from existing data. The python layer adds conversion from timedelta/relativedelta/tuples of ints, but so that's only for generic python->arrow conversion, not if you already have arrow data. For example, converting an array of integers that represents the number of days to an interval array.
Proposal: a scalar kernel that can construct an interval array from its parts (eg month_day_nano_interval_from_parts(months, days, nanos), so where each of the months/days/nanos parts can be an array or a scalar.
Currently it's not straightforward to construct a MonthDayNanoIntervalArray from existing data. The python layer adds conversion from timedelta/relativedelta/tuples of ints, but so that's only for generic python->arrow conversion, not if you already have arrow data. For example, converting an array of integers that represents the number of days to an interval array.
Proposal: a scalar kernel that can construct an interval array from its parts (eg
month_day_nano_interval_from_parts(months, days, nanos), so where each of the months/days/nanos parts can be an array or a scalar.