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Recently, we added chunked (low-memory) readers in cudf-python for parquet and json formats.
The only place these features are documented are in the options values that globally select whether to use the chunked reader. These options are, respectively io.parquet.low_memory and io.json.low_memory.
If I were looking for information about how to control IO memory usage, I do not think that I would think to look here.
I would suggest that:
chunked reader control is mentioned in the relevant read_parquet and read_json docstrings. This is especially important because there is no keyword argument to control the behaviour, it is only controlled through the option.
It might also be good to have a high-level user guide indicating how to user cudf in low memory situations. That would include the I/O options as well as things like switching to a managed memory allocator or tips and tricks for cleaning up intermediate objects to reduce how many allocations stick around.
Recently, we added chunked (low-memory) readers in cudf-python for parquet and json formats.
The only place these features are documented are in the options values that globally select whether to use the chunked reader. These options are, respectively
io.parquet.low_memory
andio.json.low_memory
.These are shown (in an unformatted manner) as the output of
describe_options
in the user documentation as part of the description of options: https://docs.rapids.ai/api/cudf/nightly/user_guide/api_docs/options/#api-optionsIf I were looking for information about how to control IO memory usage, I do not think that I would think to look here.
I would suggest that:
read_parquet
andread_json
docstrings. This is especially important because there is no keyword argument to control the behaviour, it is only controlled through the option.The text was updated successfully, but these errors were encountered: