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rapidsai / cudf

cuDF - GPU DataFrame Library
https://docs.rapids.ai/api/cudf/stable/
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[BUG] Specifying out-of-range column index for `usecols` in `read_csv()` causes illegal memory access #9015

Open charlesbluca opened 2 years ago

charlesbluca commented 2 years ago

Describe the bug When specifying an out of range column index for usecols when using read_csv() (e.g. usecols=[2] for a 2 column CSV file), an illegal memory access occurs - this can sometimes lead to segfault.

Steps/Code to reproduce bug Follow this guide http://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports to craft a minimal bug report. This helps us reproduce the issue you're having and resolve the issue more quickly.

import cudf

filename = 'foo.csv'
lines = [
  "num,text",
  "123,abc",
  "456,def",
  "789,ghi"
]

with open(filename, 'w') as fp:
    fp.write('\n'.join(lines)+'\n')

cudf.read_csv(filename, usecols=[2])
MemoryError                               Traceback (most recent call last)
<ipython-input-6-df792974f123> in <module>
----> 1 cudf.read_csv(filename, usecols=[100])

~/compose/etc/conda/cuda_11.2/envs/rapids/lib/python3.8/contextlib.py in inner(*args, **kwds)
     73         def inner(*args, **kwds):
     74             with self._recreate_cm():
---> 75                 return func(*args, **kwds)
     76         return inner
     77 

~/cudf/python/cudf/cudf/io/csv.py in read_csv(filepath_or_buffer, lineterminator, quotechar, quoting, doublequote, header, mangle_dupe_cols, usecols, sep, delimiter, delim_whitespace, skipinitialspace, names, dtype, skipfooter, skiprows, dayfirst, compression, thousands, decimal, true_values, false_values, nrows, byte_range, skip_blank_lines, parse_dates, comment, na_values, keep_default_na, na_filter, prefix, index_col, **kwargs)
     68         na_values = [na_values]
     69 
---> 70     return libcudf.csv.read_csv(
     71         filepath_or_buffer,
     72         lineterminator=lineterminator,

~/cudf/python/cudf/cudf/_lib/csv.pyx in cudf._lib.csv.read_csv()
    392     cdef table_with_metadata c_result
    393     with nogil:
--> 394         c_result = move(cpp_read_csv(read_csv_options_c))
    395 
    396     meta_names = [name.decode() for name in c_result.metadata.column_names]

MemoryError: std::bad_alloc: CUDA error at: ../include/rmm/mr/device/cuda_memory_resource.hpp:69: cudaErrorIllegalAddress an illegal memory access was encountered

Expected behavior I would expect a ValueError, similar to what Pandas throws in the same scenario:

ValueError                                Traceback (most recent call last)
<ipython-input-3-5b5ea1ba4d89> in <module>
----> 1 pd.read_csv(filename, usecols=[2])

~/compose/etc/conda/cuda_11.2/envs/rapids/lib/python3.8/site-packages/pandas/io/parsers.py in read_csv(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, squeeze, prefix, mangle_dupe_cols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, skipfooter, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, dayfirst, cache_dates, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, doublequote, escapechar, comment, encoding, dialect, error_bad_lines, warn_bad_lines, delim_whitespace, low_memory, memory_map, float_precision, storage_options)
    608     kwds.update(kwds_defaults)
    609 
--> 610     return _read(filepath_or_buffer, kwds)
    611 
    612 

~/compose/etc/conda/cuda_11.2/envs/rapids/lib/python3.8/site-packages/pandas/io/parsers.py in _read(filepath_or_buffer, kwds)
    460 
    461     # Create the parser.
--> 462     parser = TextFileReader(filepath_or_buffer, **kwds)
    463 
    464     if chunksize or iterator:

~/compose/etc/conda/cuda_11.2/envs/rapids/lib/python3.8/site-packages/pandas/io/parsers.py in __init__(self, f, engine, **kwds)
    817             self.options["has_index_names"] = kwds["has_index_names"]
    818 
--> 819         self._engine = self._make_engine(self.engine)
    820 
    821     def close(self):

~/compose/etc/conda/cuda_11.2/envs/rapids/lib/python3.8/site-packages/pandas/io/parsers.py in _make_engine(self, engine)
   1048             )
   1049         # error: Too many arguments for "ParserBase"
-> 1050         return mapping[engine](self.f, **self.options)  # type: ignore[call-arg]
   1051 
   1052     def _failover_to_python(self):

~/compose/etc/conda/cuda_11.2/envs/rapids/lib/python3.8/site-packages/pandas/io/parsers.py in __init__(self, src, **kwds)
   1932 
   1933             if len(self.names) < len(usecols):
-> 1934                 _validate_usecols_names(usecols, self.names)
   1935 
   1936         self._validate_parse_dates_presence(self.names)

~/compose/etc/conda/cuda_11.2/envs/rapids/lib/python3.8/site-packages/pandas/io/parsers.py in _validate_usecols_names(usecols, names)
   1160     missing = [c for c in usecols if c not in names]
   1161     if len(missing) > 0:
-> 1162         raise ValueError(
   1163             f"Usecols do not match columns, columns expected but not found: {missing}"
   1164         )

ValueError: Usecols do not match columns, columns expected but not found: [2]

Environment overview (please complete the following information)

Environment details

Click here to see environment details

     **git***
     commit 7d892d11736a6cfb0d4bd6109cbe72570379aa02 (HEAD -> branch-21.10, upstream/branch-21.10, origin/branch-21.10, origin/HEAD)
     Author: Ashwin Srinath <3190405+shwina@users.noreply.github.com>
     Date:   Tue Aug 10 14:19:23 2021 -0400

     Add groupby first and last aggregations (#9004)

     Authors:
     - Ashwin Srinath (https://github.com/shwina)

     Approvers:
     - Sheilah Kirui (https://github.com/skirui-source)
     - Christopher Harris (https://github.com/cwharris)
     - Richard (Rick) Zamora (https://github.com/rjzamora)

     URL: https://github.com/rapidsai/cudf/pull/9004
     **git submodules***

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     ***GPU Information***
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     | NVIDIA-SMI 460.39       Driver Version: 460.39       CUDA Version: 11.2     |
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     | GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
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     |                               |                      |                  N/A |
     +-------------------------------+----------------------+----------------------+
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     | N/A   33C    P0    57W / 300W |    818MiB / 32510MiB |      0%      Default |
     |                               |                      |                  N/A |
     +-------------------------------+----------------------+----------------------+
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     | N/A   28C    P0    41W / 300W |      3MiB / 32510MiB |      0%      Default |
     |                               |                      |                  N/A |
     +-------------------------------+----------------------+----------------------+
     |   3  Tesla V100-SXM2...  On   | 00000000:0B:00.0 Off |                    0 |
     | N/A   28C    P0    41W / 300W |      3MiB / 32510MiB |      0%      Default |
     |                               |                      |                  N/A |
     +-------------------------------+----------------------+----------------------+
     |   4  Tesla V100-SXM2...  On   | 00000000:85:00.0 Off |                    0 |
     | N/A   30C    P0    42W / 300W |      3MiB / 32510MiB |      0%      Default |
     |                               |                      |                  N/A |
     +-------------------------------+----------------------+----------------------+
     |   5  Tesla V100-SXM2...  On   | 00000000:86:00.0 Off |                    0 |
     | N/A   30C    P0    41W / 300W |      3MiB / 32510MiB |      0%      Default |
     |                               |                      |                  N/A |
     +-------------------------------+----------------------+----------------------+
     |   6  Tesla V100-SXM2...  On   | 00000000:89:00.0 Off |                    0 |
     | N/A   32C    P0    43W / 300W |      3MiB / 32510MiB |      0%      Default |
     |                               |                      |                  N/A |
     +-------------------------------+----------------------+----------------------+
     |   7  Tesla V100-SXM2...  On   | 00000000:8A:00.0 Off |                    0 |
     | N/A   29C    P0    41W / 300W |      3MiB / 32510MiB |      0%      Default |
     |                               |                      |                  N/A |
     +-------------------------------+----------------------+----------------------+

     +-----------------------------------------------------------------------------+
     | Processes:                                                                  |
     |  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
     |        ID   ID                                                   Usage      |
     |=============================================================================|
     +-----------------------------------------------------------------------------+

     ***CPU***
     Architecture:        x86_64
     CPU op-mode(s):      32-bit, 64-bit
     Byte Order:          Little Endian
     CPU(s):              80
     On-line CPU(s) list: 0-79
     Thread(s) per core:  2
     Core(s) per socket:  20
     Socket(s):           2
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     CPU family:          6
     Model:               79
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     CPU max MHz:         3600.0000
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     L3 cache:            51200K
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     NUMA node1 CPU(s):   20-39,60-79
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     ***CMake***
     /raid/charlesb/dev/rapids/compose/etc/conda/cuda_11.2/envs/rapids/bin/cmake
     cmake version 3.21.1

     CMake suite maintained and supported by Kitware (kitware.com/cmake).

     ***g++***
     /usr/local/bin/g++
     g++ (Ubuntu 9.4.0-1ubuntu1~18.04) 9.4.0
     Copyright (C) 2019 Free Software Foundation, Inc.
     This is free software; see the source for copying conditions.  There is NO
     warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.

     ***nvcc***
     /usr/local/bin/nvcc
     nvcc: NVIDIA (R) Cuda compiler driver
     Copyright (c) 2005-2021 NVIDIA Corporation
     Built on Sun_Feb_14_21:12:58_PST_2021
     Cuda compilation tools, release 11.2, V11.2.152
     Build cuda_11.2.r11.2/compiler.29618528_0

     ***Python***
     /raid/charlesb/dev/rapids/compose/etc/conda/cuda_11.2/envs/rapids/bin/python
     Python 3.8.10

     ***Environment Variables***
     PATH                            : /raid/charlesb/dev/rapids/compose/etc/conda/cuda_11.2/envs/rapids/bin:/raid/charlesb/dev/rapids/compose/etc/conda/cuda_11.2/condabin:/raid/charlesb/dev/rapids/compose/etc/conda/cuda_11.2/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/cuda/bin
     LD_LIBRARY_PATH                 : /raid/charlesb/dev/rapids/compose/etc/conda/cuda_11.2/envs/rapids/lib:/raid/charlesb/dev/rapids/compose/etc/conda/cuda_11.2/lib:/usr/lib/x86_64-linux-gnu:/usr/lib/i386-linux-gnu:/usr/local/nvidia/lib:/usr/local/nvidia/lib64:/usr/local/nvidia/lib:/usr/local/nvidia/lib64:/usr/local/cuda/lib64:/usr/local/lib:/raid/charlesb/dev/rapids/rmm/build/release:/raid/charlesb/dev/rapids/cudf/cpp/build/release:/raid/charlesb/dev/rapids/raft/cpp/build/release:/raid/charlesb/dev/rapids/cuml/cpp/build/release:/raid/charlesb/dev/rapids/cugraph/cpp/build/release:/raid/charlesb/dev/rapids/cuspatial/cpp/build/release
     NUMBAPRO_NVVM                   :
     NUMBAPRO_LIBDEVICE              :
     CONDA_PREFIX                    : /raid/charlesb/dev/rapids/compose/etc/conda/cuda_11.2/envs/rapids
     PYTHON_PATH                     :

     ***conda packages***
     /raid/charlesb/dev/rapids/compose/etc/conda/cuda_11.2/condabin/conda
     # packages in environment at /raid/charlesb/dev/rapids/compose/etc/conda/cuda_11.2/envs/rapids:
     #
     # Name                    Version                   Build  Channel
     _libgcc_mutex             0.1                 conda_forge    conda-forge
     _openmp_mutex             4.5                      1_llvm    conda-forge
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     lz4-c                     1.9.3                h9c3ff4c_0    conda-forge
     markdown                  3.3.4              pyhd8ed1ab_0    conda-forge
     markupsafe                2.0.1            py38h497a2fe_0    conda-forge
     matplotlib-inline         0.1.2              pyhd8ed1ab_2    conda-forge
     mccabe                    0.6.1                      py_1    conda-forge
     mimesis                   4.0.0              pyh9f0ad1d_0    conda-forge
     mistune                   0.8.4           py38h497a2fe_1004    conda-forge
     mkl                       2020.4             h726a3e6_304    conda-forge
     more-itertools            8.8.0              pyhd8ed1ab_0    conda-forge
     msgpack-python            1.0.2            py38h1fd1430_1    conda-forge
     mypy                      0.782                      py_0    conda-forge
     mypy_extensions           0.4.3            py38h578d9bd_3    conda-forge
     nbclient                  0.5.3              pyhd8ed1ab_0    conda-forge
     nbconvert                 6.1.0            py38h578d9bd_0    conda-forge
     nbformat                  5.1.3              pyhd8ed1ab_0    conda-forge
     nbsphinx                  0.8.6              pyhd8ed1ab_1    conda-forge
     ncurses                   6.2                  h58526e2_4    conda-forge
     nest-asyncio              1.5.1              pyhd8ed1ab_0    conda-forge
     ninja                     1.10.2               h4bd325d_0    conda-forge
     nodeenv                   1.6.0              pyhd8ed1ab_0    conda-forge
     notebook                  6.4.0              pyha770c72_0    conda-forge
     numba                     0.53.1           py38h8b71fd7_1    conda-forge
     numpy                     1.21.1           py38h9894fe3_0    conda-forge
     numpydoc                  1.1.0                      py_1    conda-forge
     nvtx                      0.2.3            py38h497a2fe_0    conda-forge
     olefile                   0.46               pyh9f0ad1d_1    conda-forge
     openjpeg                  2.4.0                hb52868f_1    conda-forge
     openssl                   1.1.1k               h7f98852_0    conda-forge
     orc                       1.6.9                h58a87f1_0    conda-forge
     packaging                 21.0               pyhd8ed1ab_0    conda-forge
     pandas                    1.2.5            py38h1abd341_0    conda-forge
     pandoc                    1.19.2                        0    conda-forge
     pandocfilters             1.4.2                      py_1    conda-forge
     parquet-cpp               1.5.1                         1    conda-forge
     parso                     0.8.2              pyhd8ed1ab_0    conda-forge
     partd                     1.2.0              pyhd8ed1ab_0    conda-forge
     pathspec                  0.9.0              pyhd8ed1ab_0    conda-forge
     pexpect                   4.8.0            py38h32f6830_1    conda-forge
     pickleshare               0.7.5           py38h32f6830_1002    conda-forge
     pillow                    8.3.1            py38h8e6f84c_0    conda-forge
     pip                       21.2.1             pyhd8ed1ab_0    conda-forge
     pluggy                    0.13.1           py38h578d9bd_4    conda-forge
     pre-commit                2.13.0           py38h578d9bd_0    conda-forge
     pre_commit                2.13.0               hd8ed1ab_0    conda-forge
     prometheus_client         0.11.0             pyhd8ed1ab_0    conda-forge
     prompt-toolkit            3.0.19             pyha770c72_0    conda-forge
     protobuf                  3.16.0           py38h709712a_0    conda-forge
     psutil                    5.8.0            py38h497a2fe_1    conda-forge
     ptvsd                     4.3.2                    pypi_0    pypi
     ptyprocess                0.7.0              pyhd3deb0d_0    conda-forge
     py                        1.10.0             pyhd3deb0d_0    conda-forge
     py-cpuinfo                8.0.0              pyhd8ed1ab_0    conda-forge
     pyarrow                   4.0.1           py38hb53058b_4_cuda    conda-forge
     pycodestyle               2.6.0              pyh9f0ad1d_0    conda-forge
     pycparser                 2.20               pyh9f0ad1d_2    conda-forge
     pyflakes                  2.2.0              pyh9f0ad1d_0    conda-forge
     pygments                  2.9.0              pyhd8ed1ab_0    conda-forge
     pyopenssl                 20.0.1             pyhd8ed1ab_0    conda-forge
     pyorc                     0.4.0                    pypi_0    pypi
     pyparsing                 2.4.7              pyh9f0ad1d_0    conda-forge
     pyrsistent                0.17.3           py38h497a2fe_2    conda-forge
     pysocks                   1.7.1            py38h578d9bd_3    conda-forge
     pytest                    6.2.4            py38h578d9bd_0    conda-forge
     pytest-benchmark          3.4.1              pyhd8ed1ab_0    conda-forge
     pytest-forked             1.3.0              pyhd3deb0d_0    conda-forge
     pytest-xdist              2.3.0              pyhd8ed1ab_0    conda-forge
     python                    3.8.10          h49503c6_1_cpython    conda-forge
     python-dateutil           2.8.2              pyhd8ed1ab_0    conda-forge
     python_abi                3.8                      2_cp38    conda-forge
     pytorch                   1.9.0           cpu_py38h91ab35c_0    conda-forge
     pytz                      2021.1             pyhd8ed1ab_0    conda-forge
     pyyaml                    5.4.1            py38h497a2fe_0    conda-forge
     pyzmq                     22.1.0           py38h2035c66_0    conda-forge
     rapidjson                 1.1.0             he1b5a44_1002    conda-forge
     re2                       2021.06.01           h9c3ff4c_0    conda-forge
     readline                  8.1                  h46c0cb4_0    conda-forge
     recommonmark              0.7.1              pyhd8ed1ab_0    conda-forge
     regex                     2021.7.6         py38h497a2fe_0    conda-forge
     requests                  2.26.0             pyhd8ed1ab_0    conda-forge
     rhash                     1.4.1                h7f98852_0    conda-forge
     s2n                       1.0.10               h9b69904_0    conda-forge
     sacremoses                0.0.43             pyh9f0ad1d_0    conda-forge
     send2trash                1.7.1              pyhd8ed1ab_0    conda-forge
     setuptools                49.6.0           py38h578d9bd_3    conda-forge
     six                       1.16.0             pyh6c4a22f_0    conda-forge
     sleef                     3.5.1                h7f98852_1    conda-forge
     snappy                    1.1.8                he1b5a44_3    conda-forge
     snowballstemmer           2.1.0              pyhd8ed1ab_0    conda-forge
     sortedcontainers          2.4.0              pyhd8ed1ab_0    conda-forge
     spdlog                    1.8.5                h4bd325d_0    conda-forge
     sphinx                    4.1.2              pyh6c4a22f_1    conda-forge
     sphinx-copybutton         0.4.0              pyhd8ed1ab_0    conda-forge
     sphinx-markdown-tables    0.0.15             pyhd3deb0d_0    conda-forge
     sphinx_rtd_theme          0.5.2              pyhd8ed1ab_1    conda-forge
     sphinxcontrib-applehelp   1.0.2                      py_0    conda-forge
     sphinxcontrib-devhelp     1.0.2                      py_0    conda-forge
     sphinxcontrib-htmlhelp    2.0.0              pyhd8ed1ab_0    conda-forge
     sphinxcontrib-jsmath      1.0.1                      py_0    conda-forge
     sphinxcontrib-qthelp      1.0.3                      py_0    conda-forge
     sphinxcontrib-serializinghtml 1.1.5              pyhd8ed1ab_0    conda-forge
     sphinxcontrib-websupport  1.2.4              pyh9f0ad1d_0    conda-forge
     sqlite                    3.36.0               h9cd32fc_0    conda-forge
     streamz                   0.6.2              pyh44b312d_0    conda-forge
     tblib                     1.7.0              pyhd8ed1ab_0    conda-forge
     terminado                 0.10.1           py38h578d9bd_0    conda-forge
     testpath                  0.5.0              pyhd8ed1ab_0    conda-forge
     tk                        8.6.10               h21135ba_1    conda-forge
     tokenizers                0.10.1           py38hb63a372_0    conda-forge
     toml                      0.10.2             pyhd8ed1ab_0    conda-forge
     toolz                     0.11.1                     py_0    conda-forge
     tornado                   6.1              py38h497a2fe_1    conda-forge
     tqdm                      4.61.2             pyhd8ed1ab_1    conda-forge
     traitlets                 5.0.5                      py_0    conda-forge
     transformers              4.9.0              pyhd8ed1ab_0    conda-forge
     typed-ast                 1.4.3            py38h497a2fe_0    conda-forge
     typing-extensions         3.10.0.0             hd8ed1ab_0    conda-forge
     typing_extensions         3.10.0.0           pyha770c72_0    conda-forge
     urllib3                   1.26.6             pyhd8ed1ab_0    conda-forge
     virtualenv                20.4.7           py38h578d9bd_0    conda-forge
     wcwidth                   0.2.5              pyh9f0ad1d_2    conda-forge
     webencodings              0.5.1                      py_1    conda-forge
     wheel                     0.36.2             pyhd3deb0d_0    conda-forge
     xz                        5.2.5                h516909a_1    conda-forge
     yaml                      0.2.5                h516909a_0    conda-forge
     zeromq                    4.3.4                h9c3ff4c_0    conda-forge
     zict                      2.0.0                      py_0    conda-forge
     zipp                      3.5.0              pyhd8ed1ab_0    conda-forge
     zlib                      1.2.11            h516909a_1010    conda-forge
     zstd                      1.5.0                ha95c52a_0    conda-forge

Additional context I encountered this bug while looking into #8973

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This issue has been labeled inactive-90d due to no recent activity in the past 90 days. Please close this issue if no further response or action is needed. Otherwise, please respond with a comment indicating any updates or changes to the original issue and/or confirm this issue still needs to be addressed.

mattf commented 1 year ago

this reproduces with cudf 22.12.01

(rapids) root@184d4f7274bc:/rapids/notebooks# python 
Python 3.8.15 | packaged by conda-forge | (default, Nov 22 2022, 08:46:39) 
[GCC 10.4.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import cudf
>>> 
>>> filename = 'foo.csv'
>>> lines = [
...   "num,text",
...   "123,abc",
...   "456,def",
...   "789,ghi"
... ]
>>> 
>>> with open(filename, 'w') as fp:
...     fp.write('\n'.join(lines)+'\n')
... 
33
>>> cudf.read_csv(filename, usecols=[2])
Segmentation fault (core dumped)