gli-chris-hao commented on issue #1223:
URL:
https://github.com/apache/iceberg-python/issues/1223#issuecomment-2566622940
We have the same use case and concerns about loading too much data into
memory for counting, the way I'm doing it to use
`DataScan.to_arrow_batch_reader`, and then count number of rows by iterating
the batches, this should avoid memory issue for large datascan:
```
count = 0
for batch in datascan.to_arrow_batch_reader():
count += batch.num_rows
```
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