rok commented on issue #50667:
URL: https://github.com/apache/arrow/issues/50667#issuecomment-5102500436

   This is a large regression. Could you help narrow it down by:
   - Trying pd.read_parquet(path, engine="pyarrow", pre_buffer=False) and 
pre_buffer=True, and reporting the timings? The ParquetFile default changed 
between 24 and 25, although pd.read_parquet ultimately uses pq.read_table, 
whose default was already True in Arrow 24.
   - Reporting the pandas version and whether the DateTimeIndex is 
timezone-aware? Arrow 25 changed reconstructed named timezones from pytz to 
zoneinfo.ZoneInfo with pandas 3. If the cache compares timezone objects 
directly, cached ranges could be rejected even though the timestamps are 
equivalent. It would be useful to print type(df.index.tz), repr(df.index.tz), 
and the corresponding values for the requested timezone.
   - Clarifying whether “Query Length (s)” is operation duration or the time 
range requested from the upstream API? If it is the latter, this may indicate 
changed cache-hit behavior rather than slower Parquet I/O.


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