willbowditch commented on issue #12653:
URL: https://github.com/apache/arrow/issues/12653#issuecomment-1159030345
Finding the same thing in `pyarrow 8.0.0` converting from a CSV to Parquet -
I've tried various batch sizes on the scanner and various min/max rows/groups
on the writer.
Running in a container the memory usage increases to maximum and eventually
crashes.
```py
from pathlib import Path
import pyarrow.csv as csv
import pyarrow.dataset as ds
tsv_directory_path = Path("/dir/with/tsv")
read_schema = pa.schema([...])
input_tsv_dataset = ds.dataset(
tsv_directory_path,
read_schema,
format=ds.CsvFileFormat(
parse_options=csv.ParseOptions(delimiter="\t", quote_char=False)
),
)
scanner = input_tsv_dataset.scanner(batch_size=100)
ds.write_dataset(
scanner,
"output_directory.parquet",
format="parquet",
max_rows_per_file=10000,
max_rows_per_group=10000,
min_rows_per_group=10,
)
```
Using the `csv.open_csv` and `pq.ParquetWriter` to write batches to a single
file works fine, but results in a single large file.
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