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Databricks Runtime 7.6 pro Machine Learning (EoS)

  • Článek

Poznámka:

Podpora této verze Databricks Runtime skončila. Datum ukončení podpory najdete v tématu Historie ukončení podpory. Všechny podporované verze databricks Runtime najdete v poznámkách k verzi Databricks Runtime a kompatibilitu.

Databricks vydala tuto verzi v únoru 2021.

Databricks Runtime 7.6 pro Machine Learning poskytuje připravené prostředí pro strojové učení a datové vědy založené na databricks Runtime 7.6 (EoS). Databricks Runtime ML obsahuje mnoho oblíbených knihoven strojového učení, včetně TensorFlow, PyTorch a XGBoost. Podporuje také distribuované trénování hlubokého učení pomocí Horovodu.

Další informace, včetně pokynů k vytvoření clusteru Databricks Runtime ML, najdete v tématu AI a strojové učení v Databricks.

Nápovědu k migraci z Databricks Runtime 6.x najdete v průvodci migrací databricks Runtime 7.x (EoS).

Nové funkce a hlavní změny

Databricks Runtime 7.6 ML je postaven na Databricks Runtime 7.6. Informace o novinkách v Databricks Runtime 7.6, včetně knihovny Apache Spark MLlib a SparkR, najdete ve zprávě k vydání verze Databricks Runtime 7.6 (EoS ).

Zastaralé

  • Tensoflow 1.x nebude podporován v nadcházející hlavní verzi Databricks Runtime.
  • Následující balíčky CUDA jsou zastaralé a budou odebrány v nadcházející hlavní verzi Databricks Runtime:
    • cuda-command-line-tools
    • cuda-compiler
    • cuda-cudart-dev
    • cuda-cufft
    • cuda-cufft-dev
    • cuda-cuobjdump
    • cuda-cupti
    • cuda-curand
    • cuda-curand-dev
    • cuda-cusolver
    • cuda-cusolver-dev
    • cuda-cusparse
    • cuda-cusparse-dev
    • cuda-documentation
    • cuda-driver-dev
    • cuda-gdb
    • cuda-gpu-library-advisor
    • cuda-libraries-dev
    • cuda-license
    • cuda-memcheck
    • cuda-minimal-build
    • cuda-misc-headers
    • cuda-npp
    • cuda-npp-dev
    • cuda-nsight
    • cuda-nvcc
    • cuda-nvdisasm
    • cuda-nvgraph
    • cuda-nvgraph-dev
    • cuda-nvjpeg
    • cuda-nvjpeg-dev
    • cuda-nvml-dev
    • cuda-nvprune
    • cuda-nvrtc-dev
    • cuda-nvvp
    • cuda-samples
    • cuda-sanitizer-api
    • cuda-toolkit
    • cuda-tools
    • cuda-visual-tools
    • freeglut3
    • libcublas-dev
    • libcudnn7-dev
    • libdrm-dev
    • libegl1
    • libegm-mesa0
    • libgbl1-mesa-dev
    • libgbm1
    • libgles1
    • libgles2
    • libglu1-mesa
    • libglu1-mesa-dev
    • libnccl-dev
    • libnvinfer-dev
    • libnvinfer-plugin-dev
    • libopengl0
    • libwayland-server0
    • libx11-xcb-dev
    • libxcb-dri2-0-dev
    • libxcb-dri3-dev
    • libxcb-glx0-dev
    • libxcb-present-dev
    • libxcb-randr0
    • libxcb-randr0-dev
    • libxcb-render0-dev
    • libxcb-shape0-dev
    • libxcb-sync-dev
    • libxcb-xfixes0
    • libxcb-xfixes0-dev
    • libxdamage-dev
    • libxext-dev
    • libxfixes-dev
    • libxi-dev
    • libxmu-dev
    • libxmu-headers
    • libxshmfence-dev
    • libxxf86vm-dev
    • mesa-common-dev
    • nsight-compute
    • nsight-systems
    • x11proto-damage-dev
    • x11proto-fixes-dev
    • x11proto-input-dev
    • x11proto-xext-dev
    • x11proto-xf86vidmode-dev

Hlavní změny prostředí Databricks Runtime ML v Pythonu

Hlavní změny prostředí Pythonu databricks Runtime 7.6 (EoS) najdete v databricks Runtime. Úplný seznam nainstalovaných balíčků Pythonu a jejich verzí najdete v knihovnách Pythonu.

Upgradované balíčky Pythonu

  • databricks-cli 0.14.0 –> 0.14.1
  • koalas 1.4.0 -> 1.5.0
  • lightgbm 2.3.0 -> 3.1.1
  • mlflow 1.12.1 -> 1.13.1
  • plotly 4.12.0 -> 4.14.1
  • pytorch 1.7.0 -> 1.7.1
  • torchvision 0.8.1 -> 0.8.2
  • xgboost 1.2.1 -> 1.3.1

Vylepšení

Integrace PySpark xGBoost (Public Preview)

Byla vylepšena integrace XGBoost s PySparkem. sparkdl 2.1.0-db5 Balíček obsahuje dva nové estimátory PySpark ML a XgboostRegressor XgboostClassifier, které uživatelům umožňují trénovat modely XGBoost v kanálech PySpark ML.

Před touto verzí se XGBoost neintegrovanou s PySparkem. Uživatelé museli buď použít xgboost4j-spark v jazyce Scala, nebo přerušit kanál PySpark ML, shromáždit datový rámec Sparku na ovladači jako datový rámec pandas a použít balíček xgboostPython . Další podrobnosti najdete v dokumentaci k rozhraní SPARKDL API a použití XGBoost v Azure Databricks .

Prostředí systému

Systémové prostředí v Databricks Runtime 7.6 ML se liší od Databricks Runtime 7.6 následujícím způsobem:

Knihovny

Následující části obsahují seznam knihoven zahrnutých v Databricks Runtime 7.6 ML, které se liší od knihoven zahrnutých v Databricks Runtime 7.6.

V této části:

Knihovny nejvyšší úrovně

Databricks Runtime 7.6 ML obsahuje následující knihovny nejvyšší úrovně:

Knihovny Pythonu

Databricks Runtime 7.6 ML používá Ke správě balíčků Pythonu Conda a obsahuje mnoho oblíbených balíčků ML.

Kromě balíčků zadaných v prostředíCh Conda v následujících částech nainstaluje Databricks Runtime 7.6 ML také následující balíčky:

  • hyperopt 0.2.5.db1
  • sparkdl 2.1.0-db5

Knihovny Pythonu v clusterech procesorů

name: databricks-ml
channels:
  - pytorch
  - defaults
dependencies:
  - _libgcc_mutex=0.1=main
  - absl-py=0.9.0=py37_0
  - asn1crypto=1.3.0=py37_1
  - astor=0.8.0=py37_0
  - backcall=0.1.0=py37_0
  - backports=1.0=pyhd3eb1b0_2
  - bcrypt=3.2.0=py37h7b6447c_0
  - blas=1.0=mkl
  - blinker=1.4=py37_0
  - boto3=1.12.0=py_0
  - botocore=1.15.0=py_0
  - c-ares=1.17.1=h27cfd23_0
  - ca-certificates=2021.1.19=h06a4308_1 # (updated from h06a4308_0 in May 26, 2021 maintenance update)
  - cachetools=4.2.0=pyhd3eb1b0_0
  - certifi=2020.12.5=py37h06a4308_0
  - cffi=1.14.0=py37he30daa8_1 # (updated from py37h2e261b9_0 in May 26, 2021 maintenance update)
  - chardet=3.0.4=py37h06a4308_1003
  - click=7.0=py37_0
  - cloudpickle=1.4.1=py_0
  - configparser=3.7.4=py37_0
  - cpuonly=1.0=0
  - cryptography=2.8=py37h1ba5d50_0
  - cycler=0.10.0=py37_0
  - cython=0.29.15=py37he6710b0_0
  - decorator=4.4.1=py_0
  - dill=0.3.1.1=py37_1
  - docutils=0.15.2=py37_0
  - entrypoints=0.3=py37_0
  - flask=1.1.1=py_1
  - freetype=2.9.1=h8a8886c_1
  - future=0.18.2=py37_1
  - gast=0.3.3=py_0
  - gitdb=4.0.5=py_0
  - gitpython=3.1.0=py_0
  - google-auth=1.11.2=py_0
  - google-auth-oauthlib=0.4.1=py_2
  - google-pasta=0.2.0=py_0
  - grpcio=1.27.2=py37hf8bcb03_0
  - gunicorn=20.0.4=py37_0
  - h5py=2.10.0=py37h7918eee_0
  - hdf5=1.10.4=hb1b8bf9_0
  - icu=58.2=he6710b0_3
  - idna=2.8=py37_0
  - intel-openmp=2020.0=166
  - ipykernel=5.1.4=py37h39e3cac_0
  - ipython=7.12.0=py37h5ca1d4c_0
  - ipython_genutils=0.2.0=pyhd3eb1b0_1
  - isodate=0.6.0=py_1
  - itsdangerous=1.1.0=py37_0
  - jedi=0.17.2=py37h06a4308_1
  - jinja2=2.11.1=py_0
  - jmespath=0.10.0=py_0
  - joblib=0.14.1=py_0
  - jpeg=9b=h024ee3a_2
  - jupyter_client=5.3.4=py37_0
  - jupyter_core=4.6.1=py37_0
  - kiwisolver=1.1.0=py37he6710b0_0
  - krb5=1.17.1=h173b8e3_0 # (updated from 1.16.4 in May 26, 2021 maintenance update)
  - ld_impl_linux-64=2.33.1=h53a641e_7
  - libedit=3.1.20181209=hc058e9b_0
  - libffi=3.3=he6710b0_2 # (updated from 3.2.1 in May 26, 2021 maintenance update)
  - 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 # (updated from 11.2 in May 26, 2021 maintenance update)
  - libprotobuf=3.11.4=hd408876_0
  - libsodium=1.0.16=h1bed415_0
  - libstdcxx-ng=9.1.0=hdf63c60_0
  - libtiff=4.1.0=h2733197_0
  - libuv=1.40.0=h7b6447c_0
  - lightgbm=3.1.1=py37h2531618_0
  - lz4-c=1.8.1.2=h14c3975_0
  - mako=1.1.2=py_0
  - markdown=3.1.1=py37_0
  - markupsafe=1.1.1=py37h14c3975_1
  - matplotlib-base=3.1.3=py37hef1b27d_0
  - mkl=2020.0=166
  - mkl-service=2.3.0=py37he8ac12f_0
  - mkl_fft=1.0.15=py37ha843d7b_0
  - mkl_random=1.1.0=py37hd6b4f25_0
  - ncurses=6.2=he6710b0_1
  - networkx=2.4=py_1
  - ninja=1.10.2=py37hff7bd54_0
  - nltk=3.4.5=py37_0
  - numpy=1.18.1=py37h4f9e942_0
  - numpy-base=1.18.1=py37hde5b4d6_1
  - oauthlib=3.1.0=py_0
  - olefile=0.46=py37_0
  - openssl=1.1.1k=h27cfd23_0 # (updated from 1.1.1i in May 26, 2021 maintenance update)
  - packaging=20.1=py_0
  - pandas=1.0.1=py37h0573a6f_0
  - paramiko=2.7.1=py_0
  - parso=0.7.0=py_0
  - patsy=0.5.1=py37_0
  - pexpect=4.8.0=pyhd3eb1b0_3
  - pickleshare=0.7.5=pyhd3eb1b0_1003
  - pillow=7.0.0=py37hb39fc2d_0
  - pip=20.0.2=py37_3
  - plotly=4.14.1=pyhd3eb1b0_0
  - prompt_toolkit=3.0.3=py_0
  - protobuf=3.11.4=py37he6710b0_0
  - psutil=5.6.7=py37h7b6447c_0
  - psycopg2=2.8.6=py37h3c74f83_1 # (updated from 2.8.4 in May 26, 2021 maintenance update)
  - ptyprocess=0.6.0=pyhd3eb1b0_2
  - pyasn1=0.4.8=py_0
  - pyasn1-modules=0.2.8=py_0
  - pycparser=2.19=py37_0
  - pygments=2.5.2=py_0
  - pyjwt=2.0.1=py37h06a4308_0
  - pynacl=1.3.0=py37h7b6447c_0
  - pyodbc=4.0.30=py37he6710b0_0
  - pyopenssl=19.1.0=pyhd3eb1b0_1
  - pyparsing=2.4.6=py_0
  - pysocks=1.7.1=py37_1
  - python=3.7.10=hdb3f193_0 # (updated from 3.7.6 in May 26, 2021 maintenance update)
  - python-dateutil=2.8.1=py_0
  - python-editor=1.0.4=py_0
  - pytorch=1.7.1=py3.7_cpu_0
  - pytz=2019.3=py_0
  - pyzmq=18.1.1=py37he6710b0_0
  - readline=8.1=h27cfd23_0 # (updated from 7.0 in May 26, 2021 maintenance update)
  - requests=2.22.0=py37_1
  - requests-oauthlib=1.3.0=py_0
  - retrying=1.3.3=py37_2
  - rsa=4.0=py_0
  - s3transfer=0.3.4=pyhd3eb1b0_0
  - scikit-learn=0.22.1=py37hd81dba3_0
  - scipy=1.4.1=py37h0b6359f_0
  - setuptools=45.2.0=py37_0
  - simplejson=3.17.0=py37h7b6447c_0
  - six=1.14.0=py37h06a4308_0
  - smmap=3.0.4=py_0
  - sqlite=3.35.4=hdfb4753_0 # (updated from 3.31.1 in May 26, 2021 maintenance update)
  - sqlparse=0.4.1=py_0
  - statsmodels=0.11.0=py37h7b6447c_0
  - tabulate=0.8.3=py37_0
  - tk=8.6.10=hbc83047_0 # (updated from 8.6.8 in May 26, 2021 maintenance update)
  - torchvision=0.8.2=py37_cpu
  - tornado=6.0.3=py37h7b6447c_3
  - tqdm=4.42.1=py_0
  - traitlets=4.3.3=py37_0
  - typing_extensions=3.7.4.3=py_0
  - unixodbc=2.3.7=h14c3975_0
  - urllib3=1.25.8=py37_0
  - wcwidth=0.1.8=py_0
  - websocket-client=0.56.0=py37_0
  - werkzeug=1.0.0=py_0
  - wheel=0.34.2=py37_0
  - wrapt=1.11.2=py37h7b6447c_0
  - xz=5.2.5=h7b6447c_0 # (updated from 5.2.4 in May 26, 2021 maintenance update)
  - zeromq=4.3.1=he6710b0_3
  - zlib=1.2.11=h7b6447c_3
  - zstd=1.3.7=h0b5b093_0
  - pip:
    - astunparse==1.6.3
    - azure-core==1.10.0
    - azure-storage-blob==12.7.0
    - databricks-cli==0.14.1
    - diskcache==5.1.0
    - docker==4.4.1
    - gorilla==0.3.0
    - horovod==0.20.3
    - joblibspark==0.3.0
    - keras-preprocessing==1.1.2
    - koalas==1.5.0
    - mleap==0.16.1
    - mlflow==1.13.1
    - msrest==0.6.19
    - opt-einsum==3.3.0
    - petastorm==0.9.7
    - pyarrow==1.0.1
    - pyyaml==5.4
    - querystring-parser==1.2.4
    - seaborn==0.10.0
    - spark-tensorflow-distributor==0.1.0
    - tensorboard==2.3.0
    - tensorboard-plugin-wit==1.8.0
    - tensorflow-cpu==2.3.1
    - tensorflow-estimator==2.3.0
    - termcolor==1.1.0
    - xgboost==1.3.1
prefix: /databricks/conda/envs/databricks-ml

Knihovny Pythonu v clusterech GPU

name: databricks-ml-gpu
channels:
  - pytorch
  - defaults
dependencies:
  - _libgcc_mutex=0.1=main
  - absl-py=0.9.0=py37_0
  - asn1crypto=1.3.0=py37_1
  - astor=0.8.0=py37_0
  - backcall=0.1.0=py37_0
  - backports=1.0=pyhd3eb1b0_2
  - bcrypt=3.2.0=py37h7b6447c_0
  - blas=1.0=mkl
  - blinker=1.4=py37_0
  - boto3=1.12.0=py_0
  - botocore=1.15.0=py_0
  - c-ares=1.17.1=h27cfd23_0
  - ca-certificates=2021.1.19=h06a4308_1 # (updated from h06a4308_0 in May 26, 2021 maintenance update)
  - cachetools=4.2.0=pyhd3eb1b0_0
  - certifi=2020.12.5=py37h06a4308_0
  - cffi=1.14.0=py37he30daa8_1 # (updated from py37h2e261b9_0 in May 26, 2021 maintenance update)
  - chardet=3.0.4=py37h06a4308_1003
  - click=7.0=py37_0
  - cloudpickle=1.4.1=py_0
  - configparser=3.7.4=py37_0
  - cryptography=2.8=py37h1ba5d50_0
  - cudatoolkit=10.1.243=h6bb024c_0
  - cycler=0.10.0=py37_0
  - cython=0.29.15=py37he6710b0_0
  - decorator=4.4.1=py_0
  - dill=0.3.1.1=py37_1
  - docutils=0.15.2=py37_0
  - entrypoints=0.3=py37_0
  - flask=1.1.1=py_1
  - freetype=2.9.1=h8a8886c_1
  - future=0.18.2=py37_1
  - gast=0.3.3=py_0
  - gitdb=4.0.5=py_0
  - gitpython=3.1.0=py_0
  - google-auth=1.11.2=py_0
  - google-auth-oauthlib=0.4.1=py_2
  - google-pasta=0.2.0=py_0
  - grpcio=1.27.2=py37hf8bcb03_0
  - gunicorn=20.0.4=py37_0
  - h5py=2.10.0=py37h7918eee_0
  - hdf5=1.10.4=hb1b8bf9_0
  - icu=58.2=he6710b0_3
  - idna=2.8=py37_0
  - intel-openmp=2020.0=166
  - ipykernel=5.1.4=py37h39e3cac_0
  - ipython=7.12.0=py37h5ca1d4c_0
  - ipython_genutils=0.2.0=pyhd3eb1b0_1
  - isodate=0.6.0=py_1
  - itsdangerous=1.1.0=py37_0
  - jedi=0.17.2=py37h06a4308_1
  - jinja2=2.11.1=py_0
  - jmespath=0.10.0=py_0
  - joblib=0.14.1=py_0
  - jpeg=9b=h024ee3a_2
  - jupyter_client=5.3.4=py37_0
  - jupyter_core=4.6.1=py37_0
  - kiwisolver=1.1.0=py37he6710b0_0
  - krb5=1.17.1=h173b8e3_0 # (updated from 1.16.4 in May 26, 2021 maintenance update)
  - ld_impl_linux-64=2.33.1=h53a641e_7
  - libedit=3.1.20181209=hc058e9b_0
  - libffi=3.3=he6710b0_2 # (updated from 3.2.1 in May 26, 2021 maintenance update)
  - 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 # (updated from 11.2 in May 26, 2021 maintenance update)
  - libprotobuf=3.11.4=hd408876_0
  - libsodium=1.0.16=h1bed415_0
  - libstdcxx-ng=9.1.0=hdf63c60_0
  - libtiff=4.1.0=h2733197_0
  - libuv=1.40.0=h7b6447c_0
  - lightgbm=3.1.1=py37h2531618_0
  - lz4-c=1.8.1.2=h14c3975_0
  - mako=1.1.2=py_0
  - markdown=3.1.1=py37_0
  - markupsafe=1.1.1=py37h14c3975_1
  - matplotlib-base=3.1.3=py37hef1b27d_0
  - mkl=2020.0=166
  - mkl-service=2.3.0=py37he8ac12f_0
  - mkl_fft=1.0.15=py37ha843d7b_0
  - mkl_random=1.1.0=py37hd6b4f25_0
  - ncurses=6.2=he6710b0_1
  - networkx=2.4=py_1
  - ninja=1.10.2=py37hff7bd54_0
  - nltk=3.4.5=py37_0
  - numpy=1.18.1=py37h4f9e942_0
  - numpy-base=1.18.1=py37hde5b4d6_1
  - oauthlib=3.1.0=py_0
  - olefile=0.46=py37_0
  - openssl=1.1.1k=h27cfd23_0 # (updated from 1.1.1i in May 26, 2021 maintenance update)
  - packaging=20.1=py_0
  - pandas=1.0.1=py37h0573a6f_0
  - paramiko=2.7.1=py_0
  - parso=0.7.0=py_0
  - patsy=0.5.1=py37_0
  - pexpect=4.8.0=pyhd3eb1b0_3
  - pickleshare=0.7.5=pyhd3eb1b0_1003
  - pillow=7.0.0=py37hb39fc2d_0
  - pip=20.0.2=py37_3
  - plotly=4.14.1=pyhd3eb1b0_0
  - prompt_toolkit=3.0.3=py_0
  - protobuf=3.11.4=py37he6710b0_0
  - psutil=5.6.7=py37h7b6447c_0
  - psycopg2=2.8.6=py37h3c74f83_1 # (updated from 2.8.4 in May 26, 2021 maintenance update)
  - ptyprocess=0.6.0=pyhd3eb1b0_2
  - pyasn1=0.4.8=py_0
  - pyasn1-modules=0.2.8=py_0
  - pycparser=2.19=py37_0
  - pygments=2.5.2=py_0
  - pyjwt=2.0.1=py37h06a4308_0
  - pynacl=1.3.0=py37h7b6447c_0
  - pyodbc=4.0.30=py37he6710b0_0
  - pyopenssl=19.1.0=pyhd3eb1b0_1
  - pyparsing=2.4.6=py_0
  - pysocks=1.7.1=py37_1
  - python=3.7.10=hdb3f193_0 # (updated from 3.7.6 in May 26, 2021 maintenance update)
  - python-dateutil=2.8.1=py_0
  - python-editor=1.0.4=py_0
  - pytorch=1.7.1=py3.7_cuda10.1.243_cudnn7.6.3_0
  - pytz=2019.3=py_0
  - pyzmq=18.1.1=py37he6710b0_0
  - readline=8.1=h27cfd23_0 # (updated from 7.0 in May 26, 2021 maintenance update)
  - requests=2.22.0=py37_1
  - requests-oauthlib=1.3.0=py_0
  - retrying=1.3.3=py37_2
  - rsa=4.0=py_0
  - s3transfer=0.3.4=pyhd3eb1b0_0
  - scikit-learn=0.22.1=py37hd81dba3_0
  - scipy=1.4.1=py37h0b6359f_0
  - setuptools=45.2.0=py37_0
  - simplejson=3.17.0=py37h7b6447c_0
  - six=1.14.0=py37h06a4308_0
  - smmap=3.0.4=py_0
  - sqlite=3.35.4=hdfb4753_0 # (updated from 3.31.1 in May 26, 2021 maintenance update)
  - sqlparse=0.4.1=py_0
  - statsmodels=0.11.0=py37h7b6447c_0
  - tabulate=0.8.3=py37_0
  - tk=8.6.10=hbc83047_0 # (updated from 8.6.8 in May 26, 2021 maintenance update)
  - torchvision=0.8.2=py37_cu101
  - tornado=6.0.3=py37h7b6447c_3
  - tqdm=4.42.1=py_0
  - traitlets=4.3.3=py37_0
  - typing_extensions=3.7.4.3=py_0
  - unixodbc=2.3.7=h14c3975_0
  - urllib3=1.25.8=py37_0
  - wcwidth=0.1.8=py_0
  - websocket-client=0.56.0=py37_0
  - werkzeug=1.0.0=py_0
  - wheel=0.34.2=py37_0
  - wrapt=1.11.2=py37h7b6447c_0
  - xz=5.2.5=h7b6447c_0 # (updated from 5.2.4 in May 26, 2021 maintenance update)
  - zeromq=4.3.1=he6710b0_3
  - zlib=1.2.11=h7b6447c_3
  - zstd=1.3.7=h0b5b093_0
  - pip:
    - astunparse==1.6.3
    - azure-core==1.10.0
    - azure-storage-blob==12.7.0
    - databricks-cli==0.14.1
    - diskcache==5.1.0
    - docker==4.4.1
    - gorilla==0.3.0
    - horovod==0.20.3
    - joblibspark==0.3.0
    - keras-preprocessing==1.1.2
    - koalas==1.5.0
    - mleap==0.16.1
    - mlflow==1.13.1
    - msrest==0.6.19
    - opt-einsum==3.3.0
    - petastorm==0.9.7
    - pyarrow==1.0.1
    - pyyaml==5.4
    - querystring-parser==1.2.4
    - seaborn==0.10.0
    - spark-tensorflow-distributor==0.1.0
    - tensorboard==2.3.0
    - tensorboard-plugin-wit==1.8.0
    - tensorflow==2.3.1
    - tensorflow-estimator==2.3.0
    - termcolor==1.1.0
    - xgboost==1.3.1
prefix: /databricks/conda/envs/databricks-ml-gpu

Balíčky Spark obsahující moduly Pythonu

Balíček Spark Modul Pythonu Verze
graphframes graphframes 0.8.1-db1-spark3.0

Knihovny jazyka R

Knihovny jazyka R jsou identické s knihovnami jazyka R v Databricks Runtime 7.6.

Knihovny Java a Scala (cluster Scala 2.12)

Kromě knihoven Java a Scala v Databricks Runtime 7.6 obsahuje Databricks Runtime 7.6 ML následující jary:

Clustery procesoru

ID skupiny ID artefaktu Verze
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 1.2.0
ml.dmlc xgboost4j_2.12 1.2.0
org.mlflow mlflow-client 1.13.1
org.scala-lang.modules scala-java8-compat_2.12 0.8.0
org.tensorflow spark-tensorflow-connector_2.12 1.15.0

Clustery GPU

ID skupiny ID artefaktu Verze
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 1.2.0
ml.dmlc xgboost4j-gpu_2.12 1.2.0
org.mlflow mlflow-client 1.13.1
org.scala-lang.modules scala-java8-compat_2.12 0.8.0
org.tensorflow spark-tensorflow-connector_2.12 1.15.0