[BUG] Creating a DataFrame from a numpy array consumes too much RAM

[NightMachinery]

Describe the bug Creating a DataFrame from a numpy array consumes too much RAM.

Steps/Code to reproduce bug

command time -f 'Max_memory: %M' python -c '
import numpy
np = numpy

n = 10**(5+4)
# a = numpy.random.default_rng().standard_normal(size=(n), dtype=np.float32)
a = np.ones((n,), dtype=np.float32)

import cudf
cudf.DataFrame(a)
' 

This will result in the following main memory (not GPU memory!) usages:

• n=10e7: 1.3GB
• n=10e8: 2.1GB
• n=10e9: 9.0GB

Expected behavior The numpy array itself occupies(you can comment the last two lines to see this):

• n=10e7: 72MB
• n=10e8: 415MB
• n=10e9: 3.8GB

The expected behavior is that the conversion should happen with some constant O(1) overhead, not an O(n) overhead.

Environment overview (please complete the following information)

• Environment location: Colab
• Method of cuDF install: conda

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

<details><summary>Click here to see environment details</summary><pre>

     **git***
     commit f1e0bb6a4ee766e68d93a9958688dd9ee0df7333 (HEAD -> branch-22.04, origin/branch-22.04, origin/HEAD)
     Merge: 57ff6f55b9 5a4c5f36f0
     Author: gpuCI <38199262+GPUtester@users.noreply.github.com>
     Date:   Fri Jan 21 14:26:43 2022 -0500

     Merge pull request #10106 from rapidsai/branch-22.02

     [gpuCI] Forward-merge branch-22.02 to branch-22.04 [skip gpuci]
     **git submodules***

     ***OS Information***
     DISTRIB_ID=Ubuntu
     DISTRIB_RELEASE=18.04
     DISTRIB_CODENAME=bionic
     DISTRIB_DESCRIPTION="Ubuntu 18.04.5 LTS"
     NAME="Ubuntu"
     VERSION="18.04.5 LTS (Bionic Beaver)"
     ID=ubuntu
     ID_LIKE=debian
     PRETTY_NAME="Ubuntu 18.04.5 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 97bea0896dfd 5.4.144+ #1 SMP Tue Dec 7 09:58:10 PST 2021 x86_64 x86_64 x86_64 GNU/Linux

     ***GPU Information***
     Fri Jan 21 21:55:38 2022
     +-----------------------------------------------------------------------------+
     | NVIDIA-SMI 495.46       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 P100-PCIE...  Off  | 00000000:00:04.0 Off |                    0 |
     | N/A   42C    P0    27W / 250W |      0MiB / 16280MiB |      0%      Default |
     |                               |                      |                  N/A |
     +-------------------------------+----------------------+----------------------+

     +-----------------------------------------------------------------------------+
     | Processes:                                                                  |
     |  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
     |        ID   ID                                                   Usage      |
     |=============================================================================|
     |  No running processes found                                                 |
     +-----------------------------------------------------------------------------+

     ***CPU***
     Architecture:        x86_64
     CPU op-mode(s):      32-bit, 64-bit
     Byte Order:          Little Endian
     CPU(s):              4
     On-line CPU(s) list: 0-3
     Thread(s) per core:  2
     Core(s) per socket:  2
     Socket(s):           1
     NUMA node(s):        1
     Vendor ID:           GenuineIntel
     CPU family:          6
     Model:               63
     Model name:          Intel(R) Xeon(R) CPU @ 2.30GHz
     Stepping:            0
     CPU MHz:             2299.998
     BogoMIPS:            4599.99
     Hypervisor vendor:   KVM
     Virtualization type: full
     L1d cache:           32K
     L1i cache:           32K
     L2 cache:            256K
     L3 cache:            46080K
     NUMA node0 CPU(s):   0-3
     Flags:               fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss ht syscall nx pdpe1gb rdtscp lm constant_tsc rep_good nopl xtopology nonstop_tsc cpuid tsc_known_freq pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand hypervisor lahf_lm abm invpcid_single ssbd ibrs ibpb stibp fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid xsaveopt arat md_clear arch_capabilities

     ***CMake***
     /usr/local/bin/cmake
     cmake version 3.12.0

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

     ***g++***
     /usr/bin/g++
     g++ (Ubuntu 7.5.0-3ubuntu1~18.04) 7.5.0
     Copyright (C) 2017 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) 2005-2020 NVIDIA Corporation
     Built on Mon_Oct_12_20:09:46_PDT_2020
     Cuda compilation tools, release 11.1, V11.1.105
     Build cuda_11.1.TC455_06.29190527_0

     ***Python***
     /root/miniconda3/bin/python
     Python 3.8.10

     ***Environment Variables***
     PATH                            : /root/miniconda3/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/tools/node/bin:/tools/google-cloud-sdk/bin:/opt/bin
     LD_LIBRARY_PATH                 : /usr/lib64-nvidia
     NUMBAPRO_NVVM                   :
     NUMBAPRO_LIBDEVICE              :
     CONDA_PREFIX                    :
     PYTHON_PATH                     :

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     libzlib                   1.2.11            h36c2ea0_1013    conda-forge
     libzopfli                 1.0.3                h9c3ff4c_0    conda-forge
     llvm-openmp               12.0.1               h4bd325d_1    conda-forge
     llvmlite                  0.38.0           py38h4630a5e_0    conda-forge
     locket                    0.2.0                      py_2    conda-forge
     lz4-c                     1.9.3                h9c3ff4c_1    conda-forge
     mapclassify               2.4.3              pyhd8ed1ab_0    conda-forge
     markdown                  3.3.6              pyhd8ed1ab_0    conda-forge
     markupsafe                2.0.1            py38h497a2fe_1    conda-forge
     matplotlib-base           3.4.3            py38hf4fb855_0    conda-forge
     matplotlib-inline         0.1.3              pyhd8ed1ab_0    conda-forge
     mistune                   0.8.4           py38h497a2fe_1005    conda-forge
     msgpack-python            1.0.3            py38h1fd1430_0    conda-forge
     multidict                 5.2.0            py38h497a2fe_1    conda-forge
     multipledispatch          0.6.0                      py_0    conda-forge
     munch                     2.5.0                      py_0    conda-forge
     murmurhash                1.0.6                    pypi_0    pypi
     mypy_extensions           0.4.3            py38h578d9bd_4    conda-forge
     nbclient                  0.5.10             pyhd8ed1ab_1    conda-forge
     nbconvert                 6.4.0            py38h578d9bd_0    conda-forge
     nbformat                  5.1.3              pyhd8ed1ab_0    conda-forge
     nccl                      2.11.4.1             h17a0586_1    conda-forge
     ncurses                   6.2                  he6710b0_1
     nest-asyncio              1.5.4              pyhd8ed1ab_0    conda-forge
     networkx                  2.6.3              pyhd8ed1ab_1    conda-forge
     nodejs                    14.17.4              h92b4a50_0    conda-forge
     notebook                  6.4.7              pyha770c72_0    conda-forge
     numba                     0.55.0           py38h4bf6c61_0    conda-forge
     numpy                     1.21.5           py38h87f13fb_0    conda-forge
     nvtx                      0.2.3            py38h497a2fe_1    conda-forge
     olefile                   0.46               pyh9f0ad1d_1    conda-forge
     openjdk                   11.0.9.1             h5cc2fde_1    conda-forge
     openjpeg                  2.4.0                hb52868f_1    conda-forge
     openssl                   1.1.1l               h7f98852_0    conda-forge
     orc                       1.7.1                h1be678f_1    conda-forge
     packaging                 21.3               pyhd8ed1ab_0    conda-forge
     pandas                    1.3.5            py38h43a58ef_0    conda-forge
     pandoc                    2.17.0.1             h7f98852_0    conda-forge
     pandocfilters             1.5.0              pyhd8ed1ab_0    conda-forge
     panel                     0.12.4             pyhd8ed1ab_0    conda-forge
     param                     1.12.0             pyh6c4a22f_0    conda-forge
     parquet-cpp               1.5.1                         2    conda-forge
     parso                     0.8.3              pyhd8ed1ab_0    conda-forge
     partd                     1.2.0              pyhd8ed1ab_0    conda-forge
     pathspec                  0.9.0              pyhd8ed1ab_0    conda-forge
     pathy                     0.6.1                    pypi_0    pypi
     pcre                      8.45                 h9c3ff4c_0    conda-forge
     pexpect                   4.8.0              pyh9f0ad1d_2    conda-forge
     pickleshare               0.7.5                   py_1003    conda-forge
     pillow                    8.3.1            py38h8e6f84c_0    conda-forge
     pip                       21.3.1             pyhd8ed1ab_0    conda-forge
     pixman                    0.40.0               h36c2ea0_0    conda-forge
     platformdirs              2.3.0              pyhd8ed1ab_0    conda-forge
     pooch                     1.5.2              pyhd8ed1ab_0    conda-forge
     poppler                   21.09.0              h0e1ea10_2    conda-forge
     poppler-data              0.4.11               hd8ed1ab_0    conda-forge
     postgresql                13.5                 h2510834_1    conda-forge
     preshed                   3.0.6                    pypi_0    pypi
     proj                      8.1.0                h277dcde_1    conda-forge
     prometheus_client         0.12.0             pyhd8ed1ab_0    conda-forge
     prompt-toolkit            3.0.24             pyha770c72_0    conda-forge
     protobuf                  3.19.3           py38h709712a_0    conda-forge
     psutil                    5.9.0            py38h497a2fe_0    conda-forge
     pthread-stubs             0.4               h36c2ea0_1001    conda-forge
     ptxcompiler               0.2.0            py38hb739d79_0    rapidsai
     ptyprocess                0.7.0              pyhd3deb0d_0    conda-forge
     pure_eval                 0.2.1              pyhd8ed1ab_1    conda-forge
     py-xgboost                1.5.0dev.rapidsai21.12  cuda11.0py38_0    rapidsai
     pyarrow                   5.0.0           py38ha746e9d_20_cuda    conda-forge
     pycosat                   0.6.3           py38h497a2fe_1009    conda-forge
     pycparser                 2.20                       py_2
     pyct                      0.4.6                      py_0    conda-forge
     pyct-core                 0.4.6                      py_0    conda-forge
     pydantic                  1.8.2                    pypi_0    pypi
     pydeck                    0.5.0              pyh9f0ad1d_0    conda-forge
     pyee                      8.1.0              pyh9f0ad1d_0    conda-forge
     pygments                  2.11.2             pyhd8ed1ab_0    conda-forge
     pynight                   0.1.0                    pypi_0    pypi
     pynvml                    11.4.1             pyhd8ed1ab_0    conda-forge
     pyopenssl                 20.0.1             pyhd3eb1b0_1
     pyparsing                 3.0.7              pyhd8ed1ab_0    conda-forge
     pyppeteer                 0.2.6              pyhd8ed1ab_0    conda-forge
     pyproj                    3.1.0            py38h3701b11_4    conda-forge
     pyrsistent                0.18.1           py38h497a2fe_0    conda-forge
     pysocks                   1.7.1            py38h578d9bd_4    conda-forge
     python                    3.8.10          h49503c6_1_cpython    conda-forge
     python-confluent-kafka    1.6.0            py38h497a2fe_1    conda-forge
     python-dateutil           2.8.2              pyhd8ed1ab_0    conda-forge
     python-tzdata             2021.5             pyhd8ed1ab_0    conda-forge
     python_abi                3.8                      2_cp38    conda-forge
     pytz                      2021.3             pyhd8ed1ab_0    conda-forge
     pytz-deprecation-shim     0.1.0.post0      py38h578d9bd_1    conda-forge
     pyviz_comms               2.1.0              pyhd8ed1ab_0    conda-forge
     pywavelets                1.2.0            py38h6c62de6_1    conda-forge
     pyyaml                    6.0              py38h497a2fe_3    conda-forge
     pyzmq                     22.3.0           py38h2035c66_1    conda-forge
     rapids                    21.12.00        cuda11.0_py38_gc46440c_94    rapidsai
     rapids-xgboost            21.12.00        cuda11.0_py38_gc46440c_94    rapidsai
     re2                       2021.11.01           h9c3ff4c_0    conda-forge
     readline                  8.1                  h27cfd23_0
     requests                  2.25.1             pyhd3eb1b0_0
     rmm                       21.12.00        cuda11_py38_g957ad04_0_no_cma    rapidsai
     rtree                     0.9.7            py38h02d302b_3    conda-forge
     ruamel_yaml               0.15.80         py38h497a2fe_1006    conda-forge
     s2n                       1.3.0                h9b69904_0    conda-forge
     scikit-image              0.18.1           py38h51da96c_0    conda-forge
     scikit-learn              1.0.2            py38h1561384_0    conda-forge
     scipy                     1.7.3            py38h56a6a73_0    conda-forge
     send2trash                1.8.0              pyhd8ed1ab_0    conda-forge
     setuptools                59.8.0           py38h578d9bd_0    conda-forge
     shapely                   1.8.0            py38hb7fe4a8_0    conda-forge
     simpervisor               0.4                pyhd8ed1ab_0    conda-forge
     six                       1.16.0             pyhd3eb1b0_0
     smart-open                5.2.1                    pypi_0    pypi
     snappy                    1.1.8                he1b5a44_3    conda-forge
     sniffio                   1.2.0            py38h578d9bd_2    conda-forge
     soalpy                    0.1.0                    pypi_0    pypi
     sortedcontainers          2.4.0              pyhd8ed1ab_0    conda-forge
     spacy                     3.2.1                    pypi_0    pypi
     spacy-legacy              3.0.8                    pypi_0    pypi
     spacy-loggers             1.0.1                    pypi_0    pypi
     spdlog                    1.8.5                h4bd325d_0    conda-forge
     sqlite                    3.36.0               hc218d9a_0
     srsly                     2.4.2                    pypi_0    pypi
     stack_data                0.1.4              pyhd8ed1ab_0    conda-forge
     starlette                 0.17.1             pyhd8ed1ab_0    conda-forge
     streamz                   0.6.3              pyh6c4a22f_0    conda-forge
     tabulate                  0.8.9              pyhd8ed1ab_0    conda-forge
     tblib                     1.7.0              pyhd8ed1ab_0    conda-forge
     terminado                 0.12.1           py38h578d9bd_1    conda-forge
     testpath                  0.5.0              pyhd8ed1ab_0    conda-forge
     thinc                     8.0.13                   pypi_0    pypi
     threadpoolctl             3.0.0              pyh8a188c0_0    conda-forge
     tifffile                  2021.11.2          pyhd8ed1ab_0    conda-forge
     tiledb                    2.3.4                he87e0bf_0    conda-forge
     tk                        8.6.10               hbc83047_0
     tomli                     1.2.2              pyhd8ed1ab_0    conda-forge
     toolz                     0.11.2             pyhd8ed1ab_0    conda-forge
     torch                     1.10.1                   pypi_0    pypi
     torchvision               0.11.2                   pypi_0    pypi
     tornado                   6.1              py38h497a2fe_2    conda-forge
     tqdm                      4.61.2             pyhd3eb1b0_1
     traitlets                 5.1.1              pyhd8ed1ab_0    conda-forge
     treelite                  2.1.0            py38hdd725b4_0    conda-forge
     treelite-runtime          2.1.0                    pypi_0    pypi
     typed-ast                 1.5.1            py38h497a2fe_0    conda-forge
     typer                     0.4.0                    pypi_0    pypi
     typing-extensions         4.0.1                hd8ed1ab_0    conda-forge
     typing_extensions         4.0.1              pyha770c72_0    conda-forge
     tzcode                    2021e                h7f98852_0    conda-forge
     tzdata                    2021a                h52ac0ba_0
     tzlocal                   4.1              py38h578d9bd_1    conda-forge
     ucx                       1.11.2+gef2bbcf      cuda11.0_0    rapidsai
     ucx-proc                  1.0.0                       gpu    rapidsai
     ucx-py                    0.23.0          py38_gef2bbcf_0    rapidsai
     urllib3                   1.26.6             pyhd3eb1b0_1
     uvicorn                   0.17.0           py38h578d9bd_0    conda-forge
     wasabi                    0.9.0                    pypi_0    pypi
     wcwidth                   0.2.5              pyh9f0ad1d_2    conda-forge
     webencodings              0.5.1                      py_1    conda-forge
     websocket-client          1.2.3              pyhd8ed1ab_0    conda-forge
     websockets                9.1              py38h497a2fe_0    conda-forge
     wheel                     0.36.2             pyhd3eb1b0_0
     widgetsnbextension        3.5.2            py38h578d9bd_1    conda-forge
     xarray                    0.20.2             pyhd8ed1ab_0    conda-forge
     xerces-c                  3.2.3                h9d8b166_3    conda-forge
     xgboost                   1.5.0dev.rapidsai21.12  cuda11.0py38_0    rapidsai
     xorg-fixesproto           5.0               h7f98852_1002    conda-forge
     xorg-inputproto           2.3.2             h7f98852_1002    conda-forge
     xorg-kbproto              1.0.7             h7f98852_1002    conda-forge
     xorg-libice               1.0.10               h7f98852_0    conda-forge
     xorg-libsm                1.2.3             hd9c2040_1000    conda-forge
     xorg-libx11               1.7.2                h7f98852_0    conda-forge
     xorg-libxau               1.0.9                h7f98852_0    conda-forge
     xorg-libxdmcp             1.1.3                h7f98852_0    conda-forge
     xorg-libxext              1.3.4                h7f98852_1    conda-forge
     xorg-libxfixes            5.0.3             h7f98852_1004    conda-forge
     xorg-libxi                1.7.10               h7f98852_0    conda-forge
     xorg-libxrender           0.9.10            h7f98852_1003    conda-forge
     xorg-libxtst              1.2.3             h7f98852_1002    conda-forge
     xorg-recordproto          1.14.2            h7f98852_1002    conda-forge
     xorg-renderproto          0.11.1            h7f98852_1002    conda-forge
     xorg-xextproto            7.3.0             h7f98852_1002    conda-forge
     xorg-xproto               7.0.31            h7f98852_1007    conda-forge
     xz                        5.2.5                h7b6447c_0
     yaml                      0.2.5                h7b6447c_0
     yarl                      1.7.2            py38h497a2fe_1    conda-forge
     zeromq                    4.3.4                h9c3ff4c_1    conda-forge
     zfp                       0.5.5                h9c3ff4c_8    conda-forge
     zict                      2.0.0                      py_0    conda-forge
     zipp                      3.7.0              pyhd8ed1ab_0    conda-forge
     zlib                      1.2.11            h36c2ea0_1013    conda-forge
     zstd                      1.5.2                ha95c52a_0    conda-forge

</pre></details>

[beckernick]

This is likely coming from cupy's asarray, which is used in the DataFrame constructor when you pass a numpy array.

Would you be open to filing this issue instead at https://github.com/cupy/cupy/issues/ to consolidate discussion?

%load_ext memory_profiler
​
import numpy as np
import cupy
​
for n in (7, 8, 9):
    a = np.ones((10**n,), dtype=np.float32)
    %memit cupy.asarray(a)
peak memory: 514.58 MiB, increment: 350.82 MiB
peak memory: 1369.92 MiB, increment: 512.01 MiB
peak memory: 8899.16 MiB, increment: 4096.00 MiB

[NightMachinery]

@beckernick I filed an issue there, but this can only explain about half of the excess memory consumption.

[beckernick]

Thanks. The differences in the tests above for smaller data sizes (but same result for 9GB) is probably related to how CuPy uses pool allocators for performance.

Is CuPy's use of CPU memory affecting a cuDF or Dask workload negatively?

[github-actions[bot]]

This issue has been labeled inactive-30d due to no recent activity in the past 30 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. This issue will be labeled inactive-90d if there is no activity in the next 60 days.

[beckernick]

Closing this issue, as this is generally expected behavior and implementing a cap for CPU pinned memory that affects other libraries by default is out of scope for cuDF. Please take further discussion to the CuPy issue linked above.