[Python][Parquet] ParquetWriter cannot use the C++ writer's parallel column encoding

[anniegracehu]

Describe the enhancement requested

parquet::arrow::FileWriter can encode a row group's columns in parallel
(ArrowWriterProperties::set_use_threads, GH-33655), but only via
NewBufferedRowGroup + WriteRecordBatch. pyarrow only binds WriteTable,
which encodes columns serially, and ParquetWriter has no use_threads
argument, so every Parquet write from Python is single-threaded
(write_table, ParquetWriter, pandas to_parquet).

Measured against 23.0.1 on a 37-column flat table (18 string, 8 double, 6 bool,
5 int64), zstd, 1M rows: 2.5 s with write_table; 1.1 s with use_threads at
65,536-row groups; 0.4 s at 262,144-row groups. Rows read back identical, same
row groups and statistics.

Proposed: ParquetWriter(..., use_threads=False) sets
ArrowWriterProperties::set_use_threads, and write_table then writes one
buffered row group per row_group_size rows through WriteRecordBatch, so the
file layout is unchanged and nothing changes unless the flag is passed.
Python-side only, ~80 lines plus tests; patch ready. The alternative would be a
use_threads-style option on C++ WriteTable so the dataset writer gets it
too. Happy to send either; which shape do you prefer?

Component(s)

Parquet