Databricks Runtime 8.2 pour ML (non pris en charge)

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Databricks a publié cette image en avril 2021.

Databricks Runtime 8.2 for Machine Learning fournit un environnement prêt à l'emploi pour l'apprentissage automatique et la science des données basé sur Databricks Runtime 8.2 (non pris en charge). Databricks Runtime ML contient de nombreuses bibliothèques populaires de Machine Learning, notamment TensorFlow, PyTorch et XGBoost. Il prend également en charge la formation de Deep Learning distribué avec Horovod.

Pour plus d’informations, notamment les instructions relatives à la création d’un cluster Databricks Runtime ML, consultez IA et Machine Learning sur Databricks.

Nouvelles fonctionnalités et modifications majeures

Databricks Runtime 8.2 ML s’appuie sur Databricks Runtime 8.2 . Pour plus d'informations sur les nouveautés de Databricks Runtime 8.2, y compris Apache Spark MLlib et SparkR, consultez les notes de publication de Databricks Runtime 8.2 (non pris en charge).

Changements importants apportés à l’environnement Python de Databricks Runtime ML

Consultez Databricks Runtime 8.2 (non pris en charge) pour connaître les modifications majeures apportées à l’environnement Databricks Runtime Python. Pour obtenir la liste complète des packages python installés et leurs versions, consultez les bibliothèques python.

Mise à niveau des packages Python

  • databricks-cli 0.14.1 -> 0.14.3
  • horovod 0.21.1 -> 0.21.3
  • koalas 1.6.0 -> 1.7.0
  • mlflow 1.14.1 -> 1.15.0
  • shap 0.38.1 -> 0.39.0
  • torch 1.7.1 -> 1.8.1
  • torchvision 0.8.2 -> 0.9.1

Ajout de packages Python

  • pandas-profiling: 2.11.0

Environnement du système

L’environnement système de Databricks Runtime 8.2 ML diffère de Databricks Runtime 8.2 comme suit :

Bibliothèques

Les sections suivantes répertorient les bibliothèques incluses dans Databricks Runtime ML 8.2 qui diffèrent de celles incluses dans Databricks Runtime 8.2.

Dans cette section :

Bibliothèques de niveau supérieur

Databricks Runtime 8.2 ML comprend les bibliothèquesde niveau supérieur suivantes :

Bibliothèques Python

Databricks Runtime 8.2 ML utilise conda pour la gestion des packages Python et comprend de nombreux packages ML populaires.

En plus des packages spécifiés dans les environnements conda dans les sections suivantes, Databricks Runtime 8.2 ML comprend également les packages suivants :

  • hyperopt 0.2.5.db1
  • sparkdl 2.1.0.db4

Bibliothèques Python sur les clusters UC

name: databricks-ml
channels:
  - pytorch
  - defaults
dependencies:
  - _libgcc_mutex=0.1=main
  - absl-py=0.11.0=pyhd3eb1b0_1
  - aiohttp=3.7.4=py38h27cfd23_1
  - asn1crypto=1.4.0=py_0
  - astor=0.8.1=py38h06a4308_0
  - async-timeout=3.0.1=py38h06a4308_0
  - attrs=20.3.0=pyhd3eb1b0_0
  - backcall=0.2.0=pyhd3eb1b0_0
  - bcrypt=3.2.0=py38h7b6447c_0
  - blas=1.0=mkl
  - blinker=1.4=py38h06a4308_0
  - boto3=1.16.7=pyhd3eb1b0_0
  - botocore=1.19.7=pyhd3eb1b0_0
  - brotlipy=0.7.0=py38h27cfd23_1003
  - bzip2=1.0.8=h7b6447c_0
  - c-ares=1.17.1=h27cfd23_0
  - ca-certificates=2021.4.13=h06a4308_1 # (updated from 2021.1.19 in May 26, 2021 maintenance update)
  - cachetools=4.2.1=pyhd3eb1b0_0
  - certifi=2020.12.5=py38h06a4308_0
  - cffi=1.14.3=py38h261ae71_2
  - chardet=3.0.4=py38h06a4308_1003
  - click=7.1.2=pyhd3eb1b0_0
  - cloudpickle=1.6.0=py_0
  - configparser=5.0.1=py_0
  - cpuonly=1.0=0
  - cryptography=3.1.1=py38h1ba5d50_0
  - cycler=0.10.0=py38_0
  - cython=0.29.21=py38h2531618_0
  - decorator=4.4.2=pyhd3eb1b0_0
  - dill=0.3.2=py_0
  - docutils=0.15.2=py38h06a4308_1
  - entrypoints=0.3=py38_0
  - ffmpeg=4.2.2=h20bf706_0
  - flask=1.1.2=pyhd3eb1b0_0
  - freetype=2.10.4=h5ab3b9f_0
  - future=0.18.2=py38_1
  - gitdb=4.0.5=py_0
  - gitpython=3.1.12=pyhd3eb1b0_1
  - gmp=6.1.2=h6c8ec71_1
  - gnutls=3.6.5=h71b1129_1002
  - google-auth=1.22.1=py_0
  - google-auth-oauthlib=0.4.2=pyhd3eb1b0_2
  - google-pasta=0.2.0=py_0
  - gunicorn=20.0.4=py38h06a4308_0
  - h5py=2.10.0=py38h7918eee_0
  - hdf5=1.10.4=hb1b8bf9_0
  - icu=58.2=he6710b0_3
  - idna=2.10=pyhd3eb1b0_0
  - importlib-metadata=2.0.0=py_1
  - intel-openmp=2019.4=243
  - ipykernel=5.3.4=py38h5ca1d4c_0
  - ipython=7.19.0=py38hb070fc8_1
  - ipython_genutils=0.2.0=pyhd3eb1b0_1
  - isodate=0.6.0=py_1
  - itsdangerous=1.1.0=pyhd3eb1b0_0
  - jedi=0.17.2=py38h06a4308_1
  - jinja2=2.11.2=pyhd3eb1b0_0
  - jmespath=0.10.0=py_0
  - joblib=0.17.0=py_0
  - jpeg=9b=h024ee3a_2
  - jupyter_client=6.1.7=py_0
  - jupyter_core=4.6.3=py38_0
  - kiwisolver=1.3.0=py38h2531618_0
  - krb5=1.17.1=h173b8e3_0
  - lame=3.100=h7b6447c_0
  - lcms2=2.11=h396b838_0
  - ld_impl_linux-64=2.33.1=h53a641e_7
  - libedit=3.1.20191231=h14c3975_1
  - libffi=3.3=he6710b0_2
  - libgcc-ng=9.1.0=hdf63c60_0
  - libgfortran-ng=7.3.0=hdf63c60_0
  - libopus=1.3.1=h7b6447c_0
  - libpng=1.6.37=hbc83047_0
  - libpq=12.2=h20c2e04_0
  - libprotobuf=3.13.0.1=hd408876_0
  - libsodium=1.0.18=h7b6447c_0
  - libstdcxx-ng=9.1.0=hdf63c60_0
  - libtiff=4.1.0=h2733197_1
  - libuv=1.40.0=h7b6447c_0
  - libvpx=1.7.0=h439df22_0
  - lightgbm=3.1.1=py38h2531618_0
  - lz4-c=1.9.2=heb0550a_3
  - mako=1.1.3=py_0
  - markdown=3.3.3=py38h06a4308_0
  - markupsafe=1.1.1=py38h7b6447c_0
  - matplotlib-base=3.2.2=py38hef1b27d_0
  - mkl=2019.4=243
  - mkl-service=2.3.0=py38he904b0f_0
  - mkl_fft=1.2.0=py38h23d657b_0
  - mkl_random=1.1.0=py38h962f231_0
  - more-itertools=8.6.0=pyhd3eb1b0_0
  - multidict=5.1.0=py38h27cfd23_2
  - ncurses=6.2=he6710b0_1
  - nettle=3.4.1=hbb512f6_0
  - networkx=2.5=py_0
  - ninja=1.10.2=py38hff7bd54_0
  - nltk=3.5=py_0
  - numpy=1.19.2=py38h54aff64_0
  - numpy-base=1.19.2=py38hfa32c7d_0
  - oauthlib=3.1.0=py_0
  - olefile=0.46=py_0
  - openh264=2.1.0=hd408876_0
  - openssl=1.1.1k=h27cfd23_0 # (updated from 1.1.1i in May 26, 2021 maintenance update)
  - packaging=20.4=py_0
  - pandas=1.1.3=py38he6710b0_0
  - paramiko=2.7.2=py_0
  - parso=0.7.0=py_0
  - patsy=0.5.1=py38_0
  - pexpect=4.8.0=pyhd3eb1b0_3
  - pickleshare=0.7.5=pyhd3eb1b0_1003
  - pillow=8.0.1=py38he98fc37_0
  - pip=20.2.4=py38h06a4308_0
  - plotly=4.14.3=pyhd3eb1b0_0
  - prompt-toolkit=3.0.8=py_0
  - prompt_toolkit=3.0.8=0
  - protobuf=3.13.0.1=py38he6710b0_1
  - psutil=5.7.2=py38h7b6447c_0
  - psycopg2=2.8.5=py38h3c74f83_1
  - ptyprocess=0.6.0=pyhd3eb1b0_2
  - pyasn1=0.4.8=py_0
  - pyasn1-modules=0.2.8=py_0
  - pycparser=2.20=py_2
  - pygments=2.7.2=pyhd3eb1b0_0
  - pyjwt=1.7.1=py38_0
  - pynacl=1.4.0=py38h7b6447c_1
  - pyodbc=4.0.30=py38he6710b0_0
  - pyopenssl=19.1.0=pyhd3eb1b0_1
  - pyparsing=2.4.7=pyhd3eb1b0_0
  - pysocks=1.7.1=py38h06a4308_0
  - python=3.8.8=hdb3f193_4 # (updated from 3.8.5 in May 26, 2021 maintenance update)
  - python-dateutil=2.8.1=pyhd3eb1b0_0
  - python-editor=1.0.4=py_0
  - pytorch=1.8.1=py3.8_cpu_0
  - pytz=2020.5=pyhd3eb1b0_0
  - pyzmq=19.0.2=py38he6710b0_1
  - readline=8.0=h7b6447c_0
  - regex=2020.10.15=py38h7b6447c_0
  - requests=2.24.0=py_0
  - requests-oauthlib=1.3.0=py_0
  - retrying=1.3.3=py_2
  - rsa=4.7.2=pyhd3eb1b0_1
  - s3transfer=0.3.6=pyhd3eb1b0_0
  - scikit-learn=0.23.2=py38h0573a6f_0
  - scipy=1.5.2=py38h0b6359f_0
  - setuptools=50.3.1=py38h06a4308_1
  - simplejson=3.17.2=py38h27cfd23_2
  - six=1.15.0=py38h06a4308_0
  - smmap=3.0.5=pyhd3eb1b0_0
  - sqlite=3.33.0=h62c20be_0
  - sqlparse=0.4.1=py_0
  - statsmodels=0.12.0=py38h7b6447c_0
  - tabulate=0.8.7=py38h06a4308_0
  - threadpoolctl=2.1.0=pyh5ca1d4c_0
  - tk=8.6.10=hbc83047_0
  - torchvision=0.9.1=py38_cpu
  - tornado=6.0.4=py38h7b6447c_1
  - tqdm=4.50.2=py_0
  - traitlets=5.0.5=pyhd3eb1b0_0
  - typing-extensions=3.7.4.3=hd3eb1b0_0
  - typing_extensions=3.7.4.3=pyh06a4308_0
  - unixodbc=2.3.9=h7b6447c_0
  - urllib3=1.25.11=py_0
  - wcwidth=0.2.5=py_0
  - websocket-client=0.57.0=py38_2
  - werkzeug=1.0.1=pyhd3eb1b0_0
  - wheel=0.35.1=pyhd3eb1b0_0
  - wrapt=1.12.1=py38h7b6447c_1
  - x264=1!157.20191217=h7b6447c_0
  - xz=5.2.5=h7b6447c_0
  - yarl=1.6.3=py38h27cfd23_0
  - zeromq=4.3.3=he6710b0_3
  - zipp=3.4.0=pyhd3eb1b0_0
  - zlib=1.2.11=h7b6447c_3
  - zstd=1.4.5=h9ceee32_0
  - pip:
    - argon2-cffi==20.1.0
    - astunparse==1.6.3
    - async-generator==1.10
    - azure-core==1.11.0
    - azure-storage-blob==12.7.1
    - bleach==3.3.0
    - confuse==1.4.0
    - databricks-cli==0.14.3
    - defusedxml==0.7.1
    - diskcache==5.2.1
    - docker==4.4.4
    - flatbuffers==1.12
    - gast==0.3.3
    - grpcio==1.32.0
    - horovod==0.21.3
    - htmlmin==0.1.12
    - imagehash==4.2.0
    - ipywidgets==7.6.3
    - joblibspark==0.3.0
    - jsonschema==3.2.0
    - jupyterlab-pygments==0.1.2
    - jupyterlab-widgets==1.0.0
    - keras-preprocessing==1.1.2
    - koalas==1.7.0
    - llvmlite==0.36.0
    - missingno==0.4.2
    - mistune==0.8.4
    - mleap==0.16.1
    - mlflow-skinny==1.15.0
    - msrest==0.6.21
    - nbclient==0.5.3
    - nbconvert==6.0.7
    - nbformat==5.1.2
    - nest-asyncio==1.5.1
    - notebook==6.3.0
    - numba==0.53.1
    - opt-einsum==3.3.0
    - pandas-profiling==2.11.0
    - pandocfilters==1.4.3
    - petastorm==0.9.8
    - phik==0.11.2
    - prometheus-client==0.9.0
    - pyarrow==1.0.1
    - pyrsistent==0.17.3
    - pywavelets==1.1.1
    - pyyaml==5.4.1
    - querystring-parser==1.2.4
    - seaborn==0.10.0
    - send2trash==1.5.0
    - shap==0.39.0
    - slicer==0.0.7
    - spark-tensorflow-distributor==0.1.0
    - tangled-up-in-unicode==0.0.7
    - tensorboard==2.4.1
    - tensorboard-plugin-wit==1.8.0
    - tensorflow-cpu==2.4.1
    - tensorflow-estimator==2.4.0
    - termcolor==1.1.0
    - terminado==0.9.4
    - testpath==0.4.4
    - visions==0.6.0
    - webencodings==0.5.1
    - widgetsnbextension==3.5.1
    - xgboost==1.3.3
prefix: /databricks/conda/envs/databricks-ml

Bibliothèques Python sur les clusters GPU

name: databricks-ml-gpu
channels:
  - defaults
dependencies:
  - _libgcc_mutex=0.1=main
  - absl-py=0.11.0=pyhd3eb1b0_1
  - aiohttp=3.7.4=py38h27cfd23_1
  - asn1crypto=1.4.0=py_0
  - astor=0.8.1=py38h06a4308_0
  - async-timeout=3.0.1=py38h06a4308_0
  - attrs=20.3.0=pyhd3eb1b0_0
  - backcall=0.2.0=pyhd3eb1b0_0
  - bcrypt=3.2.0=py38h7b6447c_0
  - blas=1.0=mkl
  - blinker=1.4=py38h06a4308_0
  - boto3=1.16.7=pyhd3eb1b0_0
  - botocore=1.19.7=pyhd3eb1b0_0
  - brotlipy=0.7.0=py38h27cfd23_1003
  - c-ares=1.17.1=h27cfd23_0
  - ca-certificates=2021.4.13=h06a4308_1 # (updated from 2021.1.19 in May 26, 2021 maintenance update)
  - cachetools=4.2.1=pyhd3eb1b0_0
  - certifi=2020.12.5=py38h06a4308_0
  - cffi=1.14.3=py38h261ae71_2
  - chardet=3.0.4=py38h06a4308_1003
  - click=7.1.2=pyhd3eb1b0_0
  - cloudpickle=1.6.0=py_0
  - configparser=5.0.1=py_0
  - cryptography=3.1.1=py38h1ba5d50_0
  - cycler=0.10.0=py38_0
  - cython=0.29.21=py38h2531618_0
  - decorator=4.4.2=pyhd3eb1b0_0
  - dill=0.3.2=py_0
  - docutils=0.15.2=py38h06a4308_1
  - entrypoints=0.3=py38_0
  - flask=1.1.2=pyhd3eb1b0_0
  - freetype=2.10.4=h5ab3b9f_0
  - future=0.18.2=py38_1
  - gitdb=4.0.5=py_0
  - gitpython=3.1.12=pyhd3eb1b0_1
  - google-auth=1.22.1=py_0
  - google-auth-oauthlib=0.4.2=pyhd3eb1b0_2
  - google-pasta=0.2.0=py_0
  - grpcio=1.31.0=py38hf8bcb03_0
  - gunicorn=20.0.4=py38h06a4308_0
  - h5py=2.10.0=py38h7918eee_0
  - hdf5=1.10.4=hb1b8bf9_0
  - icu=58.2=he6710b0_3
  - idna=2.10=pyhd3eb1b0_0
  - importlib-metadata=2.0.0=py_1
  - intel-openmp=2019.4=243
  - ipykernel=5.3.4=py38h5ca1d4c_0
  - ipython=7.19.0=py38hb070fc8_1
  - ipython_genutils=0.2.0=pyhd3eb1b0_1
  - isodate=0.6.0=py_1
  - itsdangerous=1.1.0=pyhd3eb1b0_0
  - jedi=0.17.2=py38h06a4308_1
  - jinja2=2.11.2=pyhd3eb1b0_0
  - jmespath=0.10.0=py_0
  - joblib=0.17.0=py_0
  - jpeg=9b=h024ee3a_2
  - jupyter_client=6.1.7=py_0
  - jupyter_core=4.6.3=py38_0
  - kiwisolver=1.3.0=py38h2531618_0
  - krb5=1.17.1=h173b8e3_0
  - lcms2=2.11=h396b838_0
  - ld_impl_linux-64=2.33.1=h53a641e_7
  - libedit=3.1.20191231=h14c3975_1
  - libffi=3.3=he6710b0_2
  - libgcc-ng=9.1.0=hdf63c60_0
  - libgfortran-ng=7.3.0=hdf63c60_0
  - libpng=1.6.37=hbc83047_0
  - libpq=12.2=h20c2e04_0
  - libprotobuf=3.13.0.1=hd408876_0
  - libsodium=1.0.18=h7b6447c_0
  - libstdcxx-ng=9.1.0=hdf63c60_0
  - libtiff=4.1.0=h2733197_1
  - lightgbm=3.1.1=py38h2531618_0
  - lz4-c=1.9.2=heb0550a_3
  - mako=1.1.3=py_0
  - markdown=3.3.3=py38h06a4308_0
  - markupsafe=1.1.1=py38h7b6447c_0
  - matplotlib-base=3.2.2=py38hef1b27d_0
  - mkl=2019.4=243
  - mkl-service=2.3.0=py38he904b0f_0
  - mkl_fft=1.2.0=py38h23d657b_0
  - mkl_random=1.1.0=py38h962f231_0
  - more-itertools=8.6.0=pyhd3eb1b0_0
  - multidict=5.1.0=py38h27cfd23_2
  - ncurses=6.2=he6710b0_1
  - networkx=2.5=py_0
  - nltk=3.5=py_0
  - numpy=1.19.2=py38h54aff64_0
  - numpy-base=1.19.2=py38hfa32c7d_0
  - oauthlib=3.1.0=py_0
  - olefile=0.46=py_0
  - openssl=1.1.1k=h27cfd23_0 # (updated from 1.1.1i in May 26, 2021 maintenance update)
  - packaging=20.4=py_0
  - pandas=1.1.3=py38he6710b0_0
  - paramiko=2.7.2=py_0
  - parso=0.7.0=py_0
  - patsy=0.5.1=py38_0
  - pexpect=4.8.0=pyhd3eb1b0_3
  - pickleshare=0.7.5=pyhd3eb1b0_1003
  - pillow=8.0.1=py38he98fc37_0
  - pip=20.2.4=py38h06a4308_0
  - plotly=4.14.3=pyhd3eb1b0_0
  - prompt-toolkit=3.0.8=py_0
  - prompt_toolkit=3.0.8=0
  - protobuf=3.13.0.1=py38he6710b0_1
  - psutil=5.7.2=py38h7b6447c_0
  - psycopg2=2.8.5=py38h3c74f83_1
  - ptyprocess=0.6.0=pyhd3eb1b0_2
  - pyasn1=0.4.8=py_0
  - pyasn1-modules=0.2.8=py_0
  - pycparser=2.20=py_2
  - pygments=2.7.2=pyhd3eb1b0_0
  - pyjwt=1.7.1=py38_0
  - pynacl=1.4.0=py38h7b6447c_1
  - pyodbc=4.0.30=py38he6710b0_0
  - pyopenssl=19.1.0=pyhd3eb1b0_1
  - pyparsing=2.4.7=pyhd3eb1b0_0
  - pysocks=1.7.1=py38h06a4308_0
  - python=3.8.8=hdb3f193_4 # (updated from 3.8.5 in May 26, 2021 maintenance update)
  - python-dateutil=2.8.1=pyhd3eb1b0_0
  - python-editor=1.0.4=py_0
  - pytz=2020.5=pyhd3eb1b0_0
  - pyzmq=19.0.2=py38he6710b0_1
  - readline=8.0=h7b6447c_0
  - regex=2020.10.15=py38h7b6447c_0
  - requests=2.24.0=py_0
  - requests-oauthlib=1.3.0=py_0
  - retrying=1.3.3=py_2
  - rsa=4.7.2=pyhd3eb1b0_1
  - s3transfer=0.3.6=pyhd3eb1b0_0
  - scikit-learn=0.23.2=py38h0573a6f_0
  - scipy=1.5.2=py38h0b6359f_0
  - setuptools=50.3.1=py38h06a4308_1
  - simplejson=3.17.2=py38h27cfd23_2
  - six=1.15.0=py38h06a4308_0
  - smmap=3.0.5=pyhd3eb1b0_0
  - sqlite=3.33.0=h62c20be_0
  - sqlparse=0.4.1=py_0
  - statsmodels=0.12.0=py38h7b6447c_0
  - tabulate=0.8.7=py38h06a4308_0
  - threadpoolctl=2.1.0=pyh5ca1d4c_0
  - tk=8.6.10=hbc83047_0
  - tornado=6.0.4=py38h7b6447c_1
  - tqdm=4.50.2=py_0
  - traitlets=5.0.5=pyhd3eb1b0_0
  - typing-extensions=3.7.4.3=hd3eb1b0_0
  - typing_extensions=3.7.4.3=pyh06a4308_0
  - unixodbc=2.3.9=h7b6447c_0
  - urllib3=1.25.11=py_0
  - wcwidth=0.2.5=py_0
  - websocket-client=0.57.0=py38_2
  - werkzeug=1.0.1=pyhd3eb1b0_0
  - wheel=0.35.1=pyhd3eb1b0_0
  - wrapt=1.12.1=py38h7b6447c_1
  - xz=5.2.5=h7b6447c_0
  - yarl=1.6.3=py38h27cfd23_0
  - zeromq=4.3.3=he6710b0_3
  - zipp=3.4.0=pyhd3eb1b0_0
  - zlib=1.2.11=h7b6447c_3
  - zstd=1.4.5=h9ceee32_0
  - pip:
    - argon2-cffi==20.1.0
    - astunparse==1.6.3
    - async-generator==1.10
    - azure-core==1.11.0
    - azure-storage-blob==12.7.1
    - bleach==3.3.0
    - confuse==1.4.0
    - databricks-cli==0.14.3
    - defusedxml==0.7.1
    - diskcache==5.2.1
    - docker==4.4.4
    - flatbuffers==1.12
    - gast==0.3.3
    - horovod==0.21.3
    - htmlmin==0.1.12
    - imagehash==4.2.0
    - ipywidgets==7.6.3
    - joblibspark==0.3.0
    - jsonschema==3.2.0
    - jupyterlab-pygments==0.1.2
    - jupyterlab-widgets==1.0.0
    - keras-preprocessing==1.1.2
    - koalas==1.7.0
    - llvmlite==0.36.0
    - missingno==0.4.2
    - mistune==0.8.4
    - mleap==0.16.1
    - mlflow-skinny==1.15.0
    - msrest==0.6.21
    - nbclient==0.5.3
    - nbconvert==6.0.7
    - nbformat==5.1.2
    - nest-asyncio==1.5.1
    - notebook==6.3.0
    - numba==0.53.1
    - opt-einsum==3.3.0
    - pandas-profiling==2.11.0
    - pandocfilters==1.4.3
    - petastorm==0.9.8
    - phik==0.11.2
    - pyarrow==1.0.1
    - pyrsistent==0.17.3
    - pywavelets==1.1.1
    - pyyaml==5.4.1
    - querystring-parser==1.2.4
    - seaborn==0.10.0
    - send2trash==1.5.0
    - shap==0.39.0
    - slicer==0.0.7
    - spark-tensorflow-distributor==0.1.0
    - tangled-up-in-unicode==0.0.7
    - tensorboard==2.4.1
    - tensorboard-plugin-wit==1.8.0
    - tensorflow==2.4.1
    - tensorflow-estimator==2.4.0
    - termcolor==1.1.0
    - terminado==0.9.4
    - testpath==0.4.4
    - torch==1.8.1
    - torchvision==0.9.1
    - visions==0.6.0
    - webencodings==0.5.1
    - widgetsnbextension==3.5.1
    - xgboost==1.3.3
prefix: /databricks/conda/envs/databricks-ml-gpu

Packages Spark contenant des modules Python

Package Spark Module Python Version
graphframes graphframes 0.8.1-db2-spark3.1

Bibliothèques R

Les bibliothèques R sont identiques aux bibliothèques R dans Databricks Runtime 8.2.

Bibliothèques Java et Scala (cluster Scala 2.12)

En plus des bibliothèques Java et Scala dans Databricks Runtime 8.2, Databricks Runtime 8.2 ML contient les fichiers jar suivants :

Clusters UC

ID de groupe ID d’artefact Version
com.typesafe.akka akka-actor_2.12 2.5.23
ml.combust.mleap mleap-databricks-runtime_2.12 0.17.3-4882dc3
ml.dmlc xgboost4j-spark_2.12 1.3.1
ml.dmlc xgboost4j_2.12 1.3.1
org.mlflow mlflow-client 1.15.0
org.scala-lang.modules scala-java8-compat_2.12 0.8.0
org.tensorflow spark-tensorflow-connector_2.12 1.15.0

Clusters GPU

ID de groupe ID d’artefact Version
com.typesafe.akka akka-actor_2.12 2.5.23
ml.combust.mleap mleap-databricks-runtime_2.12 0.17.3-4882dc3
ml.dmlc xgboost4j-spark-gpu_2.12 1.3.1
ml.dmlc xgboost4j-gpu_2.12 1.3.1
org.mlflow mlflow-client 1.15.0
org.scala-lang.modules scala-java8-compat_2.12 0.8.0
org.tensorflow spark-tensorflow-connector_2.12 1.15.0