lamarrr
commented
4 years ago I've done a little digging into the reader's type inference functions and it seems int64 is the only supported integer type ATM. I suppose it attempts to use an int64 for it and an overflow occurred.
https://github.com/rapidsai/cudf/blob/67c203435ec64762265061b0c63dca33153aee82/cpp/src/io/csv/reader_impl.cu#L590 https://github.com/rapidsai/cudf/blob/67c203435ec64762265061b0c63dca33153aee82/cpp/src/io/csv/reader_impl.cu#L591
cc: @jrhemstad @harrism
vuule
kaatish
Describe the bug When there are unsigned types(say
uint64) in a csv, pandas reads the series correctly but in cudf the dtype of the series being inferred toint64thus leading to data corruption after loading a csv file. A smaller version of csv file is attached here generated in fuzz test: short-data.csv.zipSteps/Code to reproduce bug
Expected behavior
cudf.read_csvshould be able to read data correctly and infer unsigned types as well.Environment overview (please complete the following information)
Environment details Please run and paste the output of the
cudf/print_env.shscript here, to gather any other relevant environment detailsClick here to see environment details
**git*** commit dc410e014419fb1eb0342dfa2e5fd1aa73b16a0a (HEAD -> 6001, origin/6001) Author: galipremsagar
Date: Fri Sep 18 18:13:22 2020 -0700
change default max_rows to 100000
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Additional context Surfaced while running fuzz tests #6001