Weston Pace created ARROW-13611:
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Summary: [C++][Python] Scanning datasets in pyarrow does not
enforce back pressure
Key: ARROW-13611
URL: https://issues.apache.org/jira/browse/ARROW-13611
Project: Apache Arrow
Issue Type: Bug
Components: C++
Affects Versions: 4.0.1, 5.0.0, 4.0.0
Reporter: Weston Pace
Fix For: 6.0.0
At the moment I'm not sure if the issue is in the C++ layer or the python
layer. I have a simple test case where I scan the batches of a 4GB dataset and
print out the currently used memory:
{code:python}
import pyarrow as pa
import pyarrow.dataset as ds
dataset = ds.dataset('/home/pace/dev/data/dataset/csv/5_big', format='csv')
num_rows = 0
for batch in dataset.to_batches():
print(pa.total_allocated_bytes())
num_rows += batch.num_rows
print(num_rows)
{code}
In pyarrow 3.0.0 this consumes just over 5MB. In pyarrow 4.0.0 and 5.0.0 this
consumes multiple GB of RAM.
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