koenvo commented on PR #1995:
URL: https://github.com/apache/iceberg-python/pull/1995#issuecomment-2932586312
Did an update and ran a quick benchmark with different `concurrent_tasks`
settings on `to_arrow_batch_reader()`:
```python
table = catalog.get_table("some_table")
# Benchmark loop
p = table.scan().to_arrow_batch_reader(concurrent_tasks=100)
for batch in tqdm.tqdm(p):
print(pool.max_memory())
```
### Results (including `pool.max_memory()`):
- `concurrent_tasks=1` → `52it [00:06, 7.73it/s]` | Max memory: **7.4 MB**
- `concurrent_tasks=10` → `391it [00:06, 61.98it/s]` | Max memory: **36.3
MB**
- `concurrent_tasks=100` → `1030it [00:09, 106.84it/s]` | Max memory: **1.76
GB**
> Note: Performance also depends on the network connection.
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