Databricks Runtime 8.3 för ML (stöds inte)

  • Artikel

Databricks släppte den här bilden i juni 2021.

Databricks Runtime 8.3 för Machine Learning tillhandahåller en färdig miljö för maskininlärning och datavetenskap baserat på Databricks Runtime 8.3 (stöds inte). Databricks Runtime ML innehåller många populära maskininlärningsbibliotek, inklusive TensorFlow, PyTorch och XGBoost. Den stöder även distribuerad djupinlärningsträning med Horovod.

Mer information, inklusive instruktioner för att skapa ett Databricks Runtime ML-kluster, finns i AI och Machine Learning på Databricks.

Nya funktioner och förbättringar

Databricks Runtime 8.3 ML bygger på Databricks Runtime 8.3. Information om nyheter i Databricks Runtime 8.3, inklusive Apache Spark MLlib och SparkR, finns i viktig information om Databricks Runtime 8.3 (stöds inte).

Databricks Runtime 8.3 ML innehåller även följande nya paket:

Större ändringar i Databricks Runtime ML Python-miljön

Se Databricks Runtime 8.3 (stöds inte) för större ändringar i Databricks Runtime Python-miljön. En fullständig lista över installerade Python-paket och deras versioner finns i Python-bibliotek.

Uppgraderade Python-paket

  • koalas 1.7.0 -> 1.8.0
  • mlflow 1.15.0 -> 1.17.0
  • pandas 1.1.3 -> 1.1.5
  • petastorm 0.9.8 -> 0.10.0
  • xgboost 1.3.3 -> 1.4.1

Python-paket har lagts till

  • helgdagar: 0.10.5.2

Använda Shiny inside R Notebooks

Nu kan du utveckla, vara värd för och dela Shiny-program direkt från en Azure Databricks R-anteckningsbok, på samma sätt som värdbaserade RStudio. Mer information finns i Shiny på Azure Databricks.

Utfasningar

Conda-miljöer, tillsammans med %conda kommandot, är nu inaktuella till förmån pip för och virtualenv kommer att tas bort i en kommande större version. Dessutom stöds anpassade avbildningar med Conda-baserade miljöer med Databricks Container Services fortfarande, men har inte biblioteksfunktioner med notebook-omfattning. Databricks rekommenderar att du använder virtualenv-baserade miljöer med Databricks Container Services och %pip för alla bibliotek med notebook-omfång.

Systemmiljö

Systemmiljön i Databricks Runtime 8.3 ML skiljer sig från Databricks Runtime 8.3 på följande sätt:

Bibliotek

I följande avsnitt visas de bibliotek som ingår i Databricks Runtime 8.3 ML som skiljer sig från de som ingår i Databricks Runtime 8.3.

I detta avsnitt:

Bibliotek på den översta nivån

Databricks Runtime 8.3 ML innehåller följande bibliotek på den översta nivån:

Python-bibliotek

Databricks Runtime 8.3 ML använder Conda för Python-pakethantering och innehåller många populära ML-paket.

Förutom de paket som anges i Conda-miljöerna i följande avsnitt innehåller Databricks Runtime 8.3 ML även följande paket:

  • hyperopt 0.2.5.db1
  • sparkdl 2.1.0.db4
  • feature_store 0.3.1
  • automl 1.0.0

Python-bibliotek i CPU-kluster

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
  - cachetools=4.2.2=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
  - fsspec=0.8.3=py_0
  - future=0.18.2=py38_1
  - gitdb=4.0.7=pyhd3eb1b0_0
  - gitpython=3.1.12=pyhd3eb1b0_1
  - gmp=6.1.2=h6c8ec71_1
  - gnutls=3.6.15=he1e5248_0
  - 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
  - libidn2=2.3.0=h27cfd23_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
  - libtasn1=4.16.0=h27cfd23_0
  - libtiff=4.1.0=h2733197_1
  - libunistring=0.9.10=h27cfd23_0
  - 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=3.7.2=hbbd107a_1
  - networkx=2.5.1=pyhd3eb1b0_0
  - ninja=1.10.2=hff7bd54_1
  - 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
  - packaging=20.4=py_0
  - pandas=1.1.5=py38ha9443f7_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
  - 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
    - convertdate==2.3.2
    - databricks-cli==0.14.3
    - defusedxml==0.7.1
    - diskcache==5.2.1
    - docker==4.4.4
    - facets-overview==1.0.0
    - flatbuffers==1.12
    - gast==0.3.3
    - grpcio==1.32.0
    - hijri-converter==2.1.1
    - holidays==0.10.5.2
    - 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==1.8.0
    - korean-lunar-calendar==0.2.1
    - llvmlite==0.36.0
    - missingno==0.4.2
    - mistune==0.8.4
    - mleap==0.16.1
    - mlflow-skinny==1.17.0
    - msrest==0.6.21
    - nbclient==0.5.3
    - nbconvert==6.0.7
    - nbformat==5.1.3
    - nest-asyncio==1.5.1
    - notebook==6.4.0
    - numba==0.53.1
    - opt-einsum==3.3.0
    - pandas-profiling==2.11.0
    - pandocfilters==1.4.3
    - petastorm==0.10.0
    - phik==0.11.2
    - prometheus-client==0.10.1
    - pyarrow==1.0.1
    - pymeeus==0.5.11
    - 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==0.1.0
    - 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==0.9.5
    - testpath==0.5.0
    - visions==0.6.0
    - webencodings==0.5.1
    - widgetsnbextension==3.5.1
    - xgboost==1.4.1
prefix: /databricks/conda/envs/databricks-ml

Python-bibliotek i GPU-kluster

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
  - cachetools=4.2.2=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
  - fsspec=0.8.3=py_0
  - future=0.18.2=py38_1
  - gitdb=4.0.7=pyhd3eb1b0_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=2.5.1=pyhd3eb1b0_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
  - packaging=20.4=py_0
  - pandas=1.1.5=py38ha9443f7_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
  - 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
    - convertdate==2.3.2
    - databricks-cli==0.14.3
    - defusedxml==0.7.1
    - diskcache==5.2.1
    - docker==4.4.4
    - facets-overview==1.0.0
    - flatbuffers==1.12
    - gast==0.3.3
    - hijri-converter==2.1.1
    - holidays==0.10.5.2
    - 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==1.8.0
    - korean-lunar-calendar==0.2.1
    - llvmlite==0.36.0
    - missingno==0.4.2
    - mistune==0.8.4
    - mleap==0.16.1
    - mlflow-skinny==1.17.0
    - msrest==0.6.21
    - nbclient==0.5.3
    - nbconvert==6.0.7
    - nbformat==5.1.3
    - nest-asyncio==1.5.1
    - notebook==6.4.0
    - numba==0.53.1
    - opt-einsum==3.3.0
    - pandas-profiling==2.11.0
    - pandocfilters==1.4.3
    - petastorm==0.10.0
    - phik==0.11.2
    - pyarrow==1.0.1
    - pymeeus==0.5.11
    - 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==0.1.0
    - tensorboard==2.4.1
    - tensorboard-plugin-wit==1.8.0
    - tensorflow==2.4.1
    - tensorflow-estimator==2.4.0
    - termcolor==1.1.0
    - terminado==0.9.5
    - testpath==0.5.0
    - torch==1.8.1
    - torchvision==0.9.1
    - visions==0.6.0
    - webencodings==0.5.1
    - widgetsnbextension==3.5.1
    - xgboost==1.4.1
prefix: /databricks/conda/envs/databricks-ml-gpu

Spark-paket som innehåller Python-moduler

Spark-paket Python-modul Version
graphframes graphframes 0.8.1-db3-spark3.1

R-bibliotek

R-biblioteken är identiska med R-biblioteken i Databricks Runtime 8.3.

Java- och Scala-bibliotek (Scala 2.12-kluster)

Förutom Java- och Scala-bibliotek i Databricks Runtime 8.3 innehåller Databricks Runtime 8.3 ML följande JAR:er:

CPU-kluster

Grupp-ID Artefakt-ID 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 1.4.1
ml.dmlc xgboost4j_2.12 1.4.1
org.mlflow mlflow-client 1.17.0
org.scala-lang.modules scala-java8-compat_2.12 0.8.0
org.tensorflow spark-tensorflow-connector_2.12 1.15.0

GPU-kluster

Grupp-ID Artefakt-ID 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 1.4.1
ml.dmlc xgboost4j-gpu_2.12 1.4.1
org.mlflow mlflow-client 1.17.0
org.scala-lang.modules scala-java8-compat_2.12 0.8.0
org.tensorflow spark-tensorflow-connector_2.12 1.15.0