用于 ML 的 Databricks Runtime 8.3 (EoS)
注意
对此 Databricks Runtime 版本的支持已结束。 有关终止支持日期,请参阅终止支持历史记录。 有关所有受支持的 Databricks Runtime 版本,请参阅 Databricks Runtime 发行说明版本和兼容性。
Databricks 于 2021 年 6 月发布了此版本。
用于机器学习的 Databricks Runtime 8.3 基于 Databricks Runtime 8.3 (EoS),为机器学习和数据科学提供了随时可用的环境。 Databricks Runtime ML 包含许多常用的机器学习库,包括 TensorFlow、PyTorch 和 XGBoost。 它还支持使用 Horovod 进行分布式深度学习训练。
有关详细信息,包括有关如何创建 Databricks Runtime ML 群集的说明,请参阅 Databricks 上的 AI 和机器学习。
新增功能和改进
Databricks Runtime 8.3 ML 基于 Databricks Runtime 8.3 构建。 若要了解 Databricks Runtime 8.3 中的新增功能,包括 Apache Spark MLlib 和 SparkR,请参阅 Databricks Runtime 8.3 (EoS) 发行说明。
Databricks Runtime 8.3 ML 还包括以下新包:
Databricks Runtime ML Python 环境的主要更改
请参阅 Databricks Runtime 8.3 (EoS) 以了解 Databricks Runtime Python 环境的主要更改。 如需查看已安装的 Python 包及其版本的完整列表,请参阅 Python 库。
升级的 Python 包
- 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
添加的 Python 包
- holidays: 0.10.5.2
在 R 笔记本中使用 Shiny
现在可以直接从 Azure Databricks R 笔记本开发、托管和共享 Shiny 应用程序,与托管 RStudio 类似。 有关详细信息,请参阅 Azure Databricks 上的 Shiny。
弃用
Conda 环境以及 %conda
命令已弃用,并且将在即将发布的主版本中被删除,现在支持 pip
和 virtualenv
。
此外,结合使用基于 Conda 的环境和 Databricks 容器服务的自定义映像仍将受支持,但不会具有笔记本范围的库功能。
Databricks 建议将基于 virtualenv
的环境与 Databricks 容器服务和 %pip
一起用于所有笔记本范围的库。
系统环境
Databricks Runtime 8.3 ML 中的系统环境在以下方面不同于 Databricks Runtime 8.3:
- DBUtils:Databricks Runtime ML 不包含库实用工具 (dbutils.library)(旧版)。
改用
%pip
和%conda
命令。 请参阅作用域为笔记本的 Python 库。 - 对于 GPU 群集,Databricks Runtime ML 包含以下 NVIDIA GPU 库:
- CUDA 11.0
- cuDNN 8.0.4.30
- NCCL 2.7.8
- TensorRT 7.1.3
库
以下部分列出了 Databricks Runtime 8.3 ML 中包含的库,这些库不同于 Databricks Runtime 8.3 中包含的库。
本节内容:
顶层库
Databricks Runtime 8.3 ML 包含以下顶层库:
- GraphFrames
- Horovod 和 HorovodRunner
- MLflow
- PyTorch
- spark-tensorflow-connector
- TensorFlow
- TensorBoard
Python 库
Databricks Runtime 8.3 ML 使用 Conda 进行 Python 包管理,并且包含许多常用的 ML 包。
除了在以下部分的 Conda 环境中指定的包,Databricks Runtime 8.3 ML 还包含以下包:
- hyperopt 0.2.5.db1
- sparkdl 2.1.0.db4
- feature_store 0.3.1
- automl 1.0.0
CPU 群集上的 Python 库
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
GPU 群集上的 Python 库
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
包含 Python 模块的 Spark 包
Spark 包 | Python 模块 | 版本 |
---|---|---|
graphframes | graphframes | 0.8.1-db3-spark3.1 |
R 库
R 库与 Databricks Runtime 8.3 中的 R 库完全相同。
Java 库和 Scala 库(Scala 2.12 群集)
除了 Databricks Runtime 8.3 中的 Java 库和 Scala 库,Databricks Runtime 8.3 ML 还包含以下 JAR:
CPU 群集
组 ID | 项目 ID | 版本 |
---|---|---|
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 群集
组 ID | 项目 ID | 版本 |
---|---|---|
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 |