devavret
commented
3 years ago Here are my observations:
The only difference between the extra metadata of the files written by cudf and pandas is that the one written by cudf has
"numpy_type": "float64" while the one written by pandas has
"numpy_type": "Float64"
When I added a correction code to utils.pyx:generate_pandas_metadata:
if col_meta["numpy_type"] in ("float64"):
col_meta["numpy_type"] = "Float64"it fixed this issue.
The culprit is pa.pandas_compat.construct_metadata
Another area in cudf that uses this pyarrow API also shows the same behaviour:
In [37]: gdf.to_arrow().to_pandas()
Out[37]:
a
0 1.0
1 NaN
2 NaN
galipremsagar
Describe the bug This looks like a parquet writer bug. When there is a mix of
np.nan&<NA>values in a float column, and that is written to parquet file, we are able to retrieve it correctly fromcudfbut not inpandas. Butpandasis able to write this column data correctly to a parquet file and that can be read fromcudf&pandascorrectly.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.
Expected behavior I'd expect the cudf written parquet file (i.e.,
cudf.parquet) to be able to behave similar topandas.parquetfile when read by bothcudf&pandasbackends.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 7721819eeed68115fd4d7033cba016830b0afcd8 (HEAD -> branch-21.08) Author: Conor Hoekstra <36027403+codereport@users.noreply.github.com> Date: Tue Jul 6 22:10:15 2021 -0400 Updating Clang Version to 11.0.0 (#6695) This resolves: https://github.com/rapidsai/cudf/issues/5187 PR description copied from: https://github.com/rapidsai/cuml/pull/3121 Depends on: https://github.com/rapidsai/integration/pull/304 This PR will upgrade the clang version required to 11.0.0 in order to enable us with running clang-tidy on .cu files, while running on cuda v11. See rapidsai/raft#88 for more details. CI will not pass as the underlying conda-env still uses 8.0.1. Once we have the rapids-build-env meta package updated, this should pass. ----- ### Fixes from Clang 8.0.1 to Clang 11.0.0 (that are observed in delta) * Missing spaces * Incorrect alignment when ternary expression splits across multiple lines * Comment alignment on macros * Fixed where function signatures have line breaks * Aligning macros * Always left align pointer/reference * Don't allow single line for loops ----- To do list: * [x] Update python file * [x] Update conda environment files * [x] Run formatter to apply all changes from upgrading * [x] Add changes from https://github.com/rapidsai/cudf/issues/5187 * [x] Review list of new changes from 8.0.1 to 11; choose which to incorporate * [x] Get working with RAPID compose Authors: - Conor Hoekstra (https://github.com/codereport) Approvers: - AJ Schmidt (https://github.com/ajschmidt8) - Nghia Truong (https://github.com/ttnghia) - Mark Harris (https://github.com/harrism) - Dillon Cullinan (https://github.com/dillon-cullinan) URL: https://github.com/rapidsai/cudf/pull/6695 **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*** Wed Jul 7 19:29:34 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 | 500MiB / 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 10W / 70W | 3MiB / 15109MiB | 0% Default | | | | N/A | +-------------------------------+----------------------+----------------------+ | 3 Tesla T4 On | 00000000:D8:00.0 Off | 0 | | N/A 31C 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 37327 C python 497MiB | +-----------------------------------------------------------------------------+ ***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: 3255.877 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 3.20.5 CMake suite maintained and supported by Kitware (kitware.com/cmake). ***g++*** /usr/bin/g++ g++ (Ubuntu 9.3.0-11ubuntu0~18.04.1) 9.3.0 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:/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:/nvme/0/pgali/envs/cudfdev/bin LD_LIBRARY_PATH : /usr/local/cuda/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 4.0.1 py38hf0991f3_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 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cuda_11.2_py38_geb2b991_34 rapidsai-nightly 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 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 4.0.3 pyh6c4a22f_0 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 sysroot_linux-64 2.12 h77966d4_13 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 4.8.2 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-forgeAdditional context Add any other context about the problem here.