When reading a Parquet file using PyArrow, there is some metadata
stored in the Parquet file to either make it a large type (eg
`large_string`, or a normal type (`string`). The difference is that
the large types use a 64 bit offset to encode their arrays.
This is not always needed, and we can could first check all the
in the types of which it is stored, and let PyArrow decide here:

https://github.com/apache/iceberg-python/blob/300b8405a0fe7d0111321e5644d704026af9266b/pyiceberg/io/pyarrow.py#L1579

In PyArrow today we just bump everything to a large type, which
might lead to additional memory consumption because it allocates
a int64 array to allocate the offsets, instead of an int32.

I thought we would be good to go for this now with the new lower
bound of PyArrow to 17. But, it looks like we still have to wait
for Arrow 18 to fix the issue with the `date` types:

apache/arrow#43183

Fixes: #1049

…-types

…-types