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Databricks Runtime 8.2 para ML (EoS)

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Nota

O suporte para esta versão do Databricks Runtime terminou. Para obter a data de fim do suporte, consulte Histórico de fim do suporte. Para todas as versões suportadas do Databricks Runtime, consulte Versões e compatibilidade das notas de versão do Databricks Runtime.

A Databricks lançou esta versão em abril de 2021.

O Databricks Runtime 8.2 for Machine Learning fornece um ambiente pronto para uso para aprendizado de máquina e ciência de dados com base no Databricks Runtime 8.2 (EoS). O Databricks Runtime ML contém muitas bibliotecas populares de aprendizado de máquina, incluindo TensorFlow, PyTorch e XGBoost. Ele também suporta treinamento distribuído de aprendizagem profunda usando Horovod.

Para obter mais informações, incluindo instruções para criar um cluster de ML do Databricks Runtime, consulte IA e aprendizado de máquina no Databricks.

Novos recursos e grandes mudanças

O Databricks Runtime 8.2 ML é construído sobre o Databricks Runtime 8.2. Para obter informações sobre o que há de novo no Databricks Runtime 8.2, incluindo Apache Spark MLlib e SparkR, consulte as notas de versão do Databricks Runtime 8.2 (EoS ).

Principais alterações no ambiente Python do Databricks Runtime ML

Consulte Databricks Runtime 8.2 (EoS) para obter as principais alterações no ambiente Python do Databricks Runtime. Para obter uma lista completa dos pacotes Python instalados e suas versões, consulte Bibliotecas Python.

Pacotes Python atualizados

  • Databricks-CLI 0.14.1 -> 0.14.3
  • Horovod 0.21.1 -> 0.21.3
  • coalas 1.6.0 -> 1.7.0
  • mlflow 1.14.1 -> 1.15.0
  • SAP 0.38.1 -> 0.39.0
  • Tocha 1.7.1 -> 1.8.1
  • Torchvision 0.8.2 -> 0.9.1

Pacotes Python adicionados

  • Perfil dos pandas: 2.11.0

Ambiente do sistema

O ambiente do sistema no Databricks Runtime 8.2 ML difere do Databricks Runtime 8.2 da seguinte maneira:

Bibliotecas

As seções a seguir listam as bibliotecas incluídas no Databricks Runtime 8.2 ML que diferem daquelas incluídas no Databricks Runtime 8.2.

Nesta secção:

Bibliotecas de nível superior

O Databricks Runtime 8.2 ML inclui as seguintes bibliotecas de camada superior:

Bibliotecas Python

O Databricks Runtime 8.2 ML usa o Conda para gerenciamento de pacotes Python e inclui muitos pacotes ML populares.

Além dos pacotes especificados nos ambientes Conda nas seções a seguir, o Databricks Runtime 8.2 ML também inclui os seguintes pacotes:

  • hiperopt 0.2.5.db1
  • faísca 2.1.0.db4

Bibliotecas Python em clusters de CPU

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

Bibliotecas Python em 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

Pacotes Spark contendo módulos Python

Pacote Spark Módulo Python Versão
quadros gráficos quadros gráficos 0.8.1-db2-faísca3.1

Bibliotecas R

As bibliotecas R são idênticas às bibliotecas R no Databricks Runtime 8.2.

Bibliotecas Java e Scala (cluster Scala 2.12)

Além das bibliotecas Java e Scala no Databricks Runtime 8.2, o Databricks Runtime 8.2 ML contém os seguintes JARs:

Clusters de CPU

ID do Grupo ID do Artefacto Versão
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-cliente 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 do Grupo ID do Artefacto Versão
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-faísca-gpu_2.12 1.3.1
ml.dmlc xgboost4j-gpu_2,12 1.3.1
org.mlflow mlflow-cliente 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