Assume_timezone will "assume timezone" of the local time you pass it and give you a zoned timestamp. This means your timestamps will be interpreted as local times and converted to UTC in the background. Resulting array will have timezone metadata of your assumed timezone.
If you are starting from a UTC-zoned timestamp you can just cast it, as David suggests, to the desired timezone (this is a metadata only change) and proceed to extracting time components. Components will be extracted in the metadata timezone. On Thu, Feb 3, 2022 at 4:27 PM Li Jin <ice.xell...@gmail.com> wrote: > > David - Thanks for the pointers. I didn't know you could cast a timestamp > to time type to extract the hour/minute information. Nice! > > Rok - Not sure I understand what you mean... My input is UTC but I want to > extract the time information local to New York Timezone (e.g. filter time > to 10 AM New York time). How would I do this without assume_timezone? > > On Thu, Feb 3, 2022 at 10:13 AM Rok Mihevc <rok.mih...@gmail.com> wrote: > > > Hey Li, > > > > If your input data is in UTC you don't need assume_timezone [1]. You > > would need it if your input was America/New_York local time and you > > wanted to convert to a zoned timestamp array where underlying data is > > in UTC and timezone is metadata only. Perhaps python tests are > > interesting for reference [2]. > > > > Available extraction kernels are listed here: [3]. > > > > Rok > > > > [1] > > https://arrow.apache.org/docs/python/generated/pyarrow.compute.assume_timezone.html > > [2] > > https://github.com/apache/arrow/blob/master/python/pyarrow/tests/test_compute.py#L1908-L1999 > > [3] > > https://arrow.apache.org/docs/cpp/compute.html#temporal-component-extraction > > > > On Thu, Feb 3, 2022 at 3:54 PM Li Jin <ice.xell...@gmail.com> wrote: > > > > > > Hello! > > > > > > I am new to the Arrow C++ compute engine and trying to figure out this > > time > > > zone conversion and time extraction: > > > > > > t.dt.tz_convert('America/New_York').dt.time == datetime.time(11, 30, 0) > > > > > > So I started looking at: > > > > > https://github.com/apache/arrow/blob/master/cpp/src/arrow/compute/kernels/scalar_temporal_unary.cc > > > > > > and found these these functions seem relevant: > > > assume_timezone > > > hour > > > minute > > > > > > So my thinking is trying to figure out a way to build plan that basically > > > does these steps: > > > (1) Assume timezone to New_York (input data is UTC) > > > (2) Extract hour value > > > (3) Extract minute value > > > (4) Filter on hour and minute value > > > > > > I wonder what is a good way to map these functions in > > > scalar_temporal_unary to an ExecPlan? (Looked under > > > https://github.com/apache/arrow/tree/master/cpp/src/arrow/compute/exec > > but > > > didn't see anything obvious) > > > > > > Thanks! > > > Li > >
