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rapidsai / cudf

cuDF - GPU DataFrame Library
https://docs.rapids.ai/api/cudf/stable/
Apache License 2.0
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[BUG] Unable to create a struct column from an arrow dictionary array #9179

Open galipremsagar opened 2 years ago

galipremsagar commented 2 years ago

Describe the bug We currently support converting a category column in cudf to a DictionaryArray in pyarrow:

>>> import cudf
>>> s = cudf.Series([1, 2, 3], dtype='category')
>>> s.to_arrow()
<pyarrow.lib.DictionaryArray object at 0x7f7980299ba0>

-- dictionary:
  [
    1,
    2,
    3
  ]
-- indices:
  [
    0,
    1,
    2
  ]
>>> s.to_arrow().type
DictionaryType(dictionary<values=int64, indices=int8, ordered=0>)

But we don't seem to be supporting the construction of StructDtype & StructColumn from our constructors:

>>> import pyarrow as pa
>>> f = pa.array([1, 2, 3])
>>> pa.StructArray.from_arrays([s.to_arrow(), f], names=['a', 'd']).type
StructType(struct<a: dictionary<values=int64, indices=int8, ordered=0>, d: int64>)
>>> pa.StructArray.from_arrays([s.to_arrow(), f], names=['a', 'd'])
<pyarrow.lib.StructArray object at 0x7f7980055760>
-- is_valid: all not null
-- child 0 type: dictionary<values=int64, indices=int8, ordered=0>

  -- dictionary:
    [
      1,
      2,
      3
    ]
  -- indices:
    [
      0,
      1,
      2
    ]
-- child 1 type: int64
  [
    1,
    2,
    3
  ]
>>> cudf.Series.from_arrow(pa.StructArray.from_arrays([s.to_arrow(), f], names=['a', 'd']))
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/nvme/0/pgali/envs/cudfdev/lib/python3.8/site-packages/cudf/core/series.py", line 1111, in __repr__
    preprocess = self.copy()
  File "/nvme/0/pgali/envs/cudfdev/lib/python3.8/site-packages/cudf/core/frame.py", line 317, in copy
    new_frame._data = self._data.copy(deep=deep)
  File "/nvme/0/pgali/envs/cudfdev/lib/python3.8/site-packages/cudf/core/column_accessor.py", line 315, in copy
    {k: v.copy(deep=True) for k, v in self._data.items()},
  File "/nvme/0/pgali/envs/cudfdev/lib/python3.8/site-packages/cudf/core/column_accessor.py", line 315, in <dictcomp>
    {k: v.copy(deep=True) for k, v in self._data.items()},
  File "/nvme/0/pgali/envs/cudfdev/lib/python3.8/site-packages/cudf/core/column/struct.py", line 102, in copy
    result = super().copy(deep=deep)
  File "/nvme/0/pgali/envs/cudfdev/lib/python3.8/site-packages/cudf/core/column/column.py", line 419, in copy
    return cast(T, result._with_type_metadata(self.dtype))
  File "/nvme/0/pgali/envs/cudfdev/lib/python3.8/site-packages/cudf/core/column/struct.py", line 134, in _with_type_metadata
    names=dtype.fields.keys(),
  File "/nvme/0/pgali/envs/cudfdev/lib/python3.8/site-packages/cudf/core/dtypes.py", line 289, in fields
    return {
  File "/nvme/0/pgali/envs/cudfdev/lib/python3.8/site-packages/cudf/core/dtypes.py", line 290, in <dictcomp>
    field.name: cudf.utils.dtypes.cudf_dtype_from_pa_type(field.type)
  File "/nvme/0/pgali/envs/cudfdev/lib/python3.8/site-packages/cudf/utils/dtypes.py", line 233, in cudf_dtype_from_pa_type
    return pandas_dtype(typ.to_pandas_dtype())
  File "pyarrow/types.pxi", line 200, in pyarrow.lib.DataType.to_pandas_dtype
NotImplementedError: dictionary<values=int64, indices=int8, ordered=0>
>>> s
0    1
1    2
2    3
dtype: category
Categories (3, int64): [1, 2, 3]
>>> s.to_frame()
   0
0  1
1  2
2  3
>>> s.to_frame().to_struct()
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/nvme/0/pgali/envs/cudfdev/lib/python3.8/site-packages/cudf/core/dataframe.py", line 7001, in to_struct
    col = cudf.core.column.build_struct_column(
  File "/nvme/0/pgali/envs/cudfdev/lib/python3.8/site-packages/cudf/core/column/column.py", line 1655, in build_struct_column
    dtype = StructDtype(
  File "/nvme/0/pgali/envs/cudfdev/lib/python3.8/site-packages/cudf/core/dtypes.py", line 281, in __init__
    pa_fields = {
  File "/nvme/0/pgali/envs/cudfdev/lib/python3.8/site-packages/cudf/core/dtypes.py", line 282, in <dictcomp>
    k: cudf.utils.dtypes.cudf_dtype_to_pa_type(v)
  File "/nvme/0/pgali/envs/cudfdev/lib/python3.8/site-packages/cudf/utils/dtypes.py", line 211, in cudf_dtype_to_pa_type
    raise NotImplementedError()
NotImplementedError

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.

Environment overview (please complete the following information)

Environment details Please run and paste the output of the cudf/print_env.sh script here, to gather any other relevant environment details

Click here to see environment details

     **git***
     commit 8d602b7e99c187db7063529def92a5d343a53a54 (HEAD -> 7618, upstream/branch-21.10, branch-21.10)
     Author: shaneding 
     Date:   Fri Sep 3 18:09:10 2021 -0700

     Implemented bindings for `ceil` timestamp operation (#9141)

     Closes #8682. Added python bindings for `ceil` operation implemented in #8942.

     Authors:
     - https://github.com/shaneding

     Approvers:
     - Ashwin Srinath (https://github.com/shwina)
     - https://github.com/brandon-b-miller

     URL: https://github.com/rapidsai/cudf/pull/9141
     **git submodules***

     ***OS Information***
     DISTRIB_ID=Ubuntu
     DISTRIB_RELEASE=18.04
     DISTRIB_CODENAME=bionic
     DISTRIB_DESCRIPTION="Ubuntu 18.04.4 LTS"
     NAME="Ubuntu"
     VERSION="18.04.4 LTS (Bionic Beaver)"
     ID=ubuntu
     ID_LIKE=debian
     PRETTY_NAME="Ubuntu 18.04.4 LTS"
     VERSION_ID="18.04"
     HOME_URL="https://www.ubuntu.com/"
     SUPPORT_URL="https://help.ubuntu.com/"
     BUG_REPORT_URL="https://bugs.launchpad.net/ubuntu/"
     PRIVACY_POLICY_URL="https://www.ubuntu.com/legal/terms-and-policies/privacy-policy"
     VERSION_CODENAME=bionic
     UBUNTU_CODENAME=bionic
     Linux dt07 4.15.0-76-generic #86-Ubuntu SMP Fri Jan 17 17:24:28 UTC 2020 x86_64 x86_64 x86_64 GNU/Linux

     ***GPU Information***
     Sat Sep  4 14:32:58 2021
     +-----------------------------------------------------------------------------+
     | NVIDIA-SMI 460.32.03    Driver Version: 460.32.03    CUDA Version: 11.2     |
     |-------------------------------+----------------------+----------------------+
     | GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
     | Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
     |                               |                      |               MIG M. |
     |===============================+======================+======================|
     |   0  Tesla T4            On   | 00000000:3B:00.0 Off |                    0 |
     | N/A   50C    P0    28W /  70W |    384MiB / 15109MiB |      0%      Default |
     |                               |                      |                  N/A |
     +-------------------------------+----------------------+----------------------+
     |   1  Tesla T4            On   | 00000000:5E:00.0 Off |                    0 |
     | N/A   37C    P8     9W /  70W |      3MiB / 15109MiB |      0%      Default |
     |                               |                      |                  N/A |
     +-------------------------------+----------------------+----------------------+
     |   2  Tesla T4            On   | 00000000:AF:00.0 Off |                    0 |
     | N/A   32C    P8    11W /  70W |      3MiB / 15109MiB |      0%      Default |
     |                               |                      |                  N/A |
     +-------------------------------+----------------------+----------------------+
     |   3  Tesla T4            On   | 00000000:D8:00.0 Off |                    0 |
     | N/A   32C    P8     9W /  70W |      3MiB / 15109MiB |      0%      Default |
     |                               |                      |                  N/A |
     +-------------------------------+----------------------+----------------------+

     +-----------------------------------------------------------------------------+
     | Processes:                                                                  |
     |  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
     |        ID   ID                                                   Usage      |
     |=============================================================================|
     |    0   N/A  N/A     58965      C   ...i/envs/cudfdev/bin/python      381MiB |
     +-----------------------------------------------------------------------------+

     ***CPU***
     Architecture:        x86_64
     CPU op-mode(s):      32-bit, 64-bit
     Byte Order:          Little Endian
     CPU(s):              64
     On-line CPU(s) list: 0-63
     Thread(s) per core:  2
     Core(s) per socket:  16
     Socket(s):           2
     NUMA node(s):        2
     Vendor ID:           GenuineIntel
     CPU family:          6
     Model:               85
     Model name:          Intel(R) Xeon(R) Gold 6130 CPU @ 2.10GHz
     Stepping:            4
     CPU MHz:             2076.027
     BogoMIPS:            4200.00
     Virtualization:      VT-x
     L1d cache:           32K
     L1i cache:           32K
     L2 cache:            1024K
     L3 cache:            22528K
     NUMA node0 CPU(s):   0,2,4,6,8,10,12,14,16,18,20,22,24,26,28,30,32,34,36,38,40,42,44,46,48,50,52,54,56,58,60,62
     NUMA node1 CPU(s):   1,3,5,7,9,11,13,15,17,19,21,23,25,27,29,31,33,35,37,39,41,43,45,47,49,51,53,55,57,59,61,63
     Flags:               fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 cdp_l3 invpcid_single pti intel_ppin ssbd mba ibrs ibpb stibp tpr_shadow vnmi flexpriority ept vpid fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm cqm mpx rdt_a avx512f avx512dq rdseed adx smap clflushopt clwb intel_pt avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local dtherm ida arat pln pts pku ospke md_clear flush_l1d

     ***CMake***
     /nvme/0/pgali/envs/cudfdev/bin/cmake
     cmake version 3.21.2

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

     ***g++***
     /usr/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/cuda/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***
     /nvme/0/pgali/envs/cudfdev/bin/python
     Python 3.8.10

     ***Environment Variables***
     PATH                            : /nvme/0/pgali/envs/cudfdev/bin:/nvme/0/pgali/envs/cudfdev/bin:/nvme/0/pgali/envs/cudfdev/bin:/usr/share/swift/usr/bin:/home/nfs/pgali/bin:/home/nfs/pgali/.local/bin:/home/nfs/pgali/anaconda3/condabin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/games:/snap/bin:/usr/lib/jvm/default-java/bin:/usr/share/sbt-launcher-packaging/bin/sbt-launch.jar/bin:/usr/lib/spark/bin:/usr/lib/spark/sbin:/usr/local/cuda/bin:/usr/local/cuda/bin
     LD_LIBRARY_PATH                 : /usr/local/cuda/lib64:/usr/local/cuda/lib64::/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64
     NUMBAPRO_NVVM                   :
     NUMBAPRO_LIBDEVICE              :
     CONDA_PREFIX                    : /nvme/0/pgali/envs/cudfdev
     PYTHON_PATH                     :

     ***conda packages***
     /home/nfs/pgali/anaconda3/condabin/conda
     # packages in environment at /nvme/0/pgali/envs/cudfdev:
     #
     # Name                    Version                   Build  Channel
     _libgcc_mutex             0.1                 conda_forge    conda-forge
     _openmp_mutex             4.5                      1_llvm    conda-forge
     abseil-cpp                20210324.2           h9c3ff4c_0    conda-forge
     alabaster                 0.7.12                     py_0    conda-forge
     appdirs                   1.4.4              pyh9f0ad1d_0    conda-forge
     argon2-cffi               20.1.0           py38h497a2fe_2    conda-forge
     arrow-cpp                 5.0.0           py38h327e1ba_4_cuda    conda-forge
     arrow-cpp-proc            3.0.0                      cuda    conda-forge
     async_generator           1.10                       py_0    conda-forge
     attrs                     21.2.0             pyhd8ed1ab_0    conda-forge
     aws-c-cal                 0.5.11               h95a6274_0    conda-forge
     aws-c-common              0.6.2                h7f98852_0    conda-forge
     aws-c-event-stream        0.2.7               h3541f99_13    conda-forge
     aws-c-io                  0.10.5               hfb6a706_0    conda-forge
     aws-checksums             0.1.11               ha31a3da_7    conda-forge
     aws-sdk-cpp               1.8.186              hb4091e7_3    conda-forge
     babel                     2.9.1              pyh44b312d_0    conda-forge
     backcall                  0.2.0              pyh9f0ad1d_0    conda-forge
     backports                 1.0                        py_2    conda-forge
     backports.functools_lru_cache 1.6.4              pyhd8ed1ab_0    conda-forge
     beautifulsoup4            4.9.3              pyhb0f4dca_0    conda-forge
     binutils_impl_linux-64    2.36.1               h193b22a_2    conda-forge
     black                     19.10b0                    py_4    conda-forge
     bleach                    4.1.0              pyhd8ed1ab_0    conda-forge
     bokeh                     2.3.3            py38h578d9bd_0    conda-forge
     brotlipy                  0.7.0           py38h497a2fe_1001    conda-forge
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     c-ares                    1.17.2               h7f98852_0    conda-forge
     ca-certificates           2021.5.30            ha878542_0    conda-forge
     cachetools                4.2.2              pyhd8ed1ab_0    conda-forge
     certifi                   2021.5.30        py38h578d9bd_0    conda-forge
     cffi                      1.14.6           py38ha65f79e_0    conda-forge
     cfgv                      3.3.1              pyhd8ed1ab_0    conda-forge
     chardet                   4.0.0            py38h578d9bd_1    conda-forge
     clang                     11.0.0               ha770c72_2    conda-forge
     clang-11                  11.0.0          default_ha5c780c_2    conda-forge
     clang-tools               11.0.0          default_ha5c780c_2    conda-forge
     clangxx                   11.0.0          default_ha5c780c_2    conda-forge
     click                     8.0.1            py38h578d9bd_0    conda-forge
     cloudpickle               1.6.0                      py_0    conda-forge
     cmake                     3.21.2               h8897547_0    conda-forge
     cmake_setuptools          0.1.3                      py_0    rapidsai
     colorama                  0.4.4              pyh9f0ad1d_0    conda-forge
     commonmark                0.9.1                      py_0    conda-forge
     cryptography              3.4.7            py38ha5dfef3_0    conda-forge
     cudatoolkit               11.2.72              h2bc3f7f_0    nvidia
     cudf                      21.10.0a0+267.g8d602b7e99.dirty          pypi_0    pypi
     cupy                      9.4.0            py38h7818112_0    conda-forge
     cython                    0.29.24          py38h709712a_0    conda-forge
     cytoolz                   0.11.0           py38h497a2fe_3    conda-forge
     dask                      2021.9.0           pyhd8ed1ab_0    conda-forge
     dask-core                 2021.9.0           pyhd8ed1ab_0    conda-forge
     dask-cudf                 21.10.0a0+267.g8d602b7e99.dirty          pypi_0    pypi
     dataclasses               0.8                pyhc8e2a94_3    conda-forge
     debugpy                   1.4.1            py38h709712a_0    conda-forge
     decorator                 5.0.9              pyhd8ed1ab_0    conda-forge
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     distlib                   0.3.2              pyhd8ed1ab_0    conda-forge
     distributed               2021.9.0         py38h578d9bd_0    conda-forge
     dlpack                    0.5                  h9c3ff4c_0    conda-forge
     docutils                  0.16             py38h578d9bd_3    conda-forge
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     editdistance-s            1.0.0            py38h1fd1430_1    conda-forge
     entrypoints               0.3             pyhd8ed1ab_1003    conda-forge
     execnet                   1.9.0              pyhd8ed1ab_0    conda-forge
     expat                     2.4.1                h9c3ff4c_0    conda-forge
     fastavro                  1.4.4            py38h497a2fe_0    conda-forge
     fastrlock                 0.6              py38h709712a_1    conda-forge
     filelock                  3.0.12             pyh9f0ad1d_0    conda-forge
     flake8                    3.8.3                      py_1    conda-forge
     freetype                  2.10.4               h0708190_1    conda-forge
     fsspec                    2021.8.1           pyhd8ed1ab_0    conda-forge
     future                    0.18.2           py38h578d9bd_3    conda-forge
     gcc_impl_linux-64         11.1.0               h6b5115b_8    conda-forge
     gflags                    2.2.2             he1b5a44_1004    conda-forge
     glog                      0.5.0                h48cff8f_0    conda-forge
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     heapdict                  1.0.1                      py_0    conda-forge
     huggingface_hub           0.0.16             pyhd8ed1ab_0    conda-forge
     hypothesis                6.17.4             pyhd8ed1ab_0    conda-forge
     identify                  2.2.13             pyhd8ed1ab_0    conda-forge
     idna                      2.10               pyh9f0ad1d_0    conda-forge
     imagesize                 1.2.0                      py_0    conda-forge
     importlib-metadata        4.8.1            py38h578d9bd_0    conda-forge
     importlib_metadata        4.8.1                hd8ed1ab_0    conda-forge
     iniconfig                 1.1.1              pyh9f0ad1d_0    conda-forge
     ipykernel                 6.3.1            py38he5a9106_0    conda-forge
     ipython                   7.27.0           py38he5a9106_0    conda-forge
     ipython_genutils          0.2.0                      py_1    conda-forge
     isort                     5.6.4                      py_0    conda-forge
     jbig                      2.1               h7f98852_2003    conda-forge
     jedi                      0.18.0           py38h578d9bd_2    conda-forge
     jinja2                    3.0.1              pyhd8ed1ab_0    conda-forge
     joblib                    1.0.1              pyhd8ed1ab_0    conda-forge
     jpeg                      9d                   h36c2ea0_0    conda-forge
     jsonschema                3.2.0              pyhd8ed1ab_3    conda-forge
     jupyter_client            7.0.2              pyhd8ed1ab_0    conda-forge
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     jupyterlab_pygments       0.1.2              pyh9f0ad1d_0    conda-forge
     kernel-headers_linux-64   2.6.32              he073ed8_14    conda-forge
     krb5                      1.19.2               hcc1bbae_0    conda-forge
     lcms2                     2.12                 hddcbb42_0    conda-forge
     ld_impl_linux-64          2.36.1               hea4e1c9_2    conda-forge
     lerc                      2.2.1                h9c3ff4c_0    conda-forge
     libblas                   3.9.0                     8_mkl    conda-forge
     libbrotlicommon           1.0.9                h7f98852_5    conda-forge
     libbrotlidec              1.0.9                h7f98852_5    conda-forge
     libbrotlienc              1.0.9                h7f98852_5    conda-forge
     libcblas                  3.9.0                     8_mkl    conda-forge
     libclang-cpp11            11.0.0          default_ha5c780c_2    conda-forge
     libcurl                   7.78.0               h2574ce0_0    conda-forge
     libdeflate                1.7                  h7f98852_5    conda-forge
     libedit                   3.1.20191231         he28a2e2_2    conda-forge
     libev                     4.33                 h516909a_1    conda-forge
     libevent                  2.1.10               hcdb4288_3    conda-forge
     libffi                    3.3                  h58526e2_2    conda-forge
     libgcc-devel_linux-64     11.1.0               h80e7780_8    conda-forge
     libgcc-ng                 11.1.0               hc902ee8_8    conda-forge
     libgomp                   11.1.0               hc902ee8_8    conda-forge
     liblapack                 3.9.0                     8_mkl    conda-forge
     libllvm10                 10.0.1               he513fc3_3    conda-forge
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     libpng                    1.6.37               h21135ba_2    conda-forge
     libprotobuf               3.16.0               h780b84a_0    conda-forge
     librmm                    21.10.00a210904 cuda11.2_g8527317_28    rapidsai-nightly
     libsanitizer              11.1.0               h56837e0_8    conda-forge
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     libssh2                   1.10.0               ha56f1ee_0    conda-forge
     libstdcxx-ng              11.1.0               h56837e0_8    conda-forge
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     mypy                      0.782                      py_0    conda-forge
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     py                        1.10.0             pyhd3deb0d_0    conda-forge
     py-cpuinfo                8.0.0              pyhd8ed1ab_0    conda-forge
     pyarrow                   5.0.0           py38hed47224_4_cuda    conda-forge
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     pyopenssl                 20.0.1             pyhd8ed1ab_0    conda-forge
     pyorc                     0.4.0                    pypi_0    pypi
     pyparsing                 2.4.7              pyh9f0ad1d_0    conda-forge
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     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
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     rapidjson                 1.1.0             he1b5a44_1002    conda-forge
     re2                       2021.09.01           h9c3ff4c_0    conda-forge
     readline                  8.1                  h46c0cb4_0    conda-forge
     recommonmark              0.7.1              pyhd8ed1ab_0    conda-forge
     regex                     2021.8.28        py38h497a2fe_0    conda-forge
     requests                  2.25.1             pyhd3deb0d_0    conda-forge
     rhash                     1.4.1                h7f98852_0    conda-forge
     rmm                       21.10.00a210904 cuda_11.2_py38_g8527317_28    rapidsai-nightly
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     sysroot_linux-64          2.12                he073ed8_14    conda-forge
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     terminado                 0.11.1           py38h578d9bd_0    conda-forge
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     tk                        8.6.11               h27826a3_1    conda-forge
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     zlib                      1.2.11            h516909a_1010    conda-forge
     zstd                      1.5.0                ha95c52a_0    conda-forge

Additional context Add any other context about the problem here.

isVoid commented 2 years ago

Cudf supports constructing a StructColumn from a StructArray.

In [14]: pa_struct = pa.StructArray.from_arrays([pa.array([1, 2, 3]), pa.array(['a', 'b', 'c'])], names=['num', 'str'])

In [16]: cudf.Series.from_arrow(pa_struct)
Out[16]: 
0    {'num': 1, 'str': 'a'}
1    {'num': 2, 'str': 'b'}
2    {'num': 3, 'str': 'c'}
dtype: struct

I believe the error you see here has to do with having DictionaryArray as one of the fields in the StructArray.

In [5]: r = cudf.Series.from_arrow(pa.StructArray.from_arrays([s.to_arrow(), f], names=['a', 'd']))

In [6]: type(r)
Out[6]: cudf.core.series.Series

In [8]: r._column.children
Out[8]: 
(<cudf.core.column.categorical.CategoricalColumn object at 0x7f6459ceda70>

 -- dictionary:
   [
     1,
     2,
     3
   ]
 -- indices:
   [
     0,
     1,
     2
   ]
 dtype: category,
 <cudf.core.column.numerical.NumericalColumn object at 0x7f645a5a53b0>
 [
   1,
   2,
   3
 ]
 dtype: int64)

The result is well formed. But cannot convert the column back to arrow:

In [11]: r.to_arrow()
---------------------------------------------------------------------------
NotImplementedError                       Traceback (most recent call last)
<ipython-input-11-77c2df0309ec> in <module>
----> 1 r.to_arrow()

~/cudf/python/cudf/cudf/core/single_column_frame.py in to_arrow(self)
    213         ]
    214         """
--> 215         return self._column.to_arrow()
    216 
    217     @property

~/cudf/python/cudf/cudf/core/column/struct.py in to_arrow(self)
     68             {
     69                 field: child.type
---> 70                 for field, child in zip(self.dtype.fields, children)
     71             }
     72         )

~/cudf/python/cudf/cudf/core/dtypes.py in fields(self)
    289         return {
    290             field.name: cudf.utils.dtypes.cudf_dtype_from_pa_type(field.type)
--> 291             for field in self._typ
    292         }
    293 

~/cudf/python/cudf/cudf/core/dtypes.py in <dictcomp>(.0)
    289         return {
    290             field.name: cudf.utils.dtypes.cudf_dtype_from_pa_type(field.type)
--> 291             for field in self._typ
    292         }
    293 

~/cudf/python/cudf/cudf/utils/dtypes.py in cudf_dtype_from_pa_type(typ)
    215         return cudf.core.dtypes.Decimal64Dtype.from_arrow(typ)
    216     else:
--> 217         return cudf.api.types.pandas_dtype(typ.to_pandas_dtype())
    218 
    219 

~/compose/etc/conda/cuda_11.2/envs/rapids/lib/python3.7/site-packages/pyarrow/types.pxi in pyarrow.lib.DataType.to_pandas_dtype()

NotImplementedError: dictionary<values=int64, indices=int8, ordered=0>
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