Oh thanks that could be a workaround! I thought pa tables are supposed to be immutable , is there a safe way to just change the metadata?
On Wed, Feb 15, 2023 at 5:44 PM Rok Mihevc <rok.mih...@gmail.com> wrote: > Well that's suboptimal. As a workaround I suppose you could just change the > metadata if the array is timezone aware. > > On Wed, Feb 15, 2023 at 10:37 PM Li Jin <ice.xell...@gmail.com> wrote: > > > Oh found this comment: > > > > > https://github.com/apache/arrow/blob/master/cpp/src/arrow/compute/kernels/scalar_cast_temporal.cc#L156 > > > > > > > > On Wed, Feb 15, 2023 at 4:23 PM Li Jin <ice.xell...@gmail.com> wrote: > > > > > Not sure if this is actually a bug or expected behavior - I filed > > > https://github.com/apache/arrow/issues/34210 > > > > > > On Wed, Feb 15, 2023 at 4:15 PM Li Jin <ice.xell...@gmail.com> wrote: > > > > > >> Hmm..something feels off here - I did the following experiment on > Arrow > > >> 11 and casting timestamp-naive to int64 is much faster than casting > > >> timestamp-naive to timestamp-utc: > > >> > > >> In [16]: %time table.cast(schema_int) > > >> CPU times: user 114 µs, sys: 30 µs, total: 144 µs > > >> *Wall time: 231 µs* > > >> Out[16]: > > >> pyarrow.Table > > >> time: int64 > > >> ---- > > >> time: [[0,1,2,3,4,...,99999995,99999996,99999997,99999998,99999999]] > > >> > > >> In [17]: %time table.cast(schema_tz) > > >> CPU times: user 119 ms, sys: 140 ms, total: 260 ms > > >> *Wall time: 259 ms* > > >> Out[17]: > > >> pyarrow.Table > > >> time: timestamp[ns, tz=UTC] > > >> ---- > > >> time: [[1970-01-01 00:00:00.000000000,1970-01-01 > > >> 00:00:00.000000001,1970-01-01 00:00:00.000000002,1970-01-01 > > >> 00:00:00.000000003,1970-01-01 00:00:00.000000004,...,1970-01-01 > > >> 00:00:00.099999995,1970-01-01 00:00:00.099999996,1970-01-01 > > >> 00:00:00.099999997,1970-01-01 00:00:00.099999998,1970-01-01 > > >> 00:00:00.099999999]] > > >> > > >> In [18]: table > > >> Out[18]: > > >> pyarrow.Table > > >> time: timestamp[ns] > > >> ---- > > >> time: [[1970-01-01 00:00:00.000000000,1970-01-01 > > >> 00:00:00.000000001,1970-01-01 00:00:00.000000002,1970-01-01 > > >> 00:00:00.000000003,1970-01-01 00:00:00.000000004,...,1970-01-01 > > >> 00:00:00.099999995,1970-01-01 00:00:00.099999996,1970-01-01 > > >> 00:00:00.099999997,1970-01-01 00:00:00.099999998,1970-01-01 > > >> 00:00:00.099999999]] > > >> > > >> On Wed, Feb 15, 2023 at 2:52 PM Rok Mihevc <rok.mih...@gmail.com> > > wrote: > > >> > > >>> I'm not sure about (1) but I'm pretty sure for (2) doing a cast of > > >>> tz-aware > > >>> timestamp to tz-naive should be a metadata-only change. > > >>> > > >>> On Wed, Feb 15, 2023 at 4:19 PM Li Jin <ice.xell...@gmail.com> > wrote: > > >>> > > >>> > Asking (2) because IIUC this is a metadata operation that could be > > zero > > >>> > copy but I am not sure if this is actually the case. > > >>> > > > >>> > On Wed, Feb 15, 2023 at 10:17 AM Li Jin <ice.xell...@gmail.com> > > wrote: > > >>> > > > >>> > > Hello! > > >>> > > > > >>> > > I have some questions about type casting memory usage with > pyarrow > > >>> Table. > > >>> > > Let's say I have a pyarrow Table with 100 columns. > > >>> > > > > >>> > > (1) if I want to cast n columns to a different type (e.g., float > to > > >>> int). > > >>> > > What is the smallest memory overhead that I can do? (memory > > overhead > > >>> of 1 > > >>> > > column, n columns or 100 columns?) > > >>> > > > > >>> > > (2) if I want to cast n timestamp columns from tz-native to > tz-UTC. > > >>> What > > >>> > > is the smallest memory overhead that I can do? (0, 1 column, n > > >>> columns or > > >>> > > 100 columns?) > > >>> > > > > >>> > > Thanks! > > >>> > > Li > > >>> > > > > >>> > > > >>> > > >> > > >
