wingkitlee0 commented on issue #39808:
URL: https://github.com/apache/arrow/issues/39808#issuecomment-2954260310
Sharing a plot that I made a little while ago, using pyarrow 20.x and the
following options in `to_batches` (or `scanner`):
```
batch_readahead=0,
cache_metadata=False, # new
fragment_scan_options=pyarrow.dataset.ParquetFragmentScanOptions(
use_buffered_stream=True,
pre_buffer=False,
cache_options=pa.CacheOptions(lazy=True, prefetch_limit=0),
),
```
I used the 2.3gb parquet file earlier in the thread, which has about 10 row
groups. In the figure, the blue lines are default option, orange/green are
using `cache_metadata=False` etc. `b5000` etc are the batch size. The top panel
shows the memory used by the current batch. The middle and bottom panels are
pa.total_allocated_bytes and rss (from psutil), respectively.
There are 9-10 spikes, which seem to be at the beginning of each row group.
The memory usage is still rising with the extra options, though much slower.
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