Databricks Runtime 8.1 for ML (EoS)

Artikkeli
09/03/2024

Note

Support for this Databricks Runtime version has ended. For the end-of-support date, see End-of-support history. For all supported Databricks Runtime versions, see Databricks Runtime release notes versions and compatibility.

Databricks released this version in March 2021.

Databricks Runtime 8.1 for Machine Learning provides a ready-to-go environment for machine learning and data science based on Databricks Runtime 8.1 (EoS). Databricks Runtime ML contains many popular machine learning libraries, including TensorFlow, PyTorch, and XGBoost. It also supports distributed deep learning training using Horovod.

For more information, including instructions for creating a Databricks Runtime ML cluster, see AI and machine learning on Databricks.

New features and major changes

Databricks Runtime 8.1 ML is built on top of Databricks Runtime 8.1. For information on what’s new in Databricks Runtime 8.1, including Apache Spark MLlib and SparkR, see the Databricks Runtime 8.1 (EoS) release notes.

Packages removed in the GPU clusters

The following CUDA packages are removed in the GPU clusters:

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

Major changes to Databricks Runtime ML Python environment

See Databricks Runtime 8.1 (EoS) for the major changes to the Databricks Runtime Python environment. For a full list of installed Python packages and their versions, see Python libraries.

Python packages upgraded

mlflow 1.13.1 -> 1.14.1
plotly 4.14.1 -> 4.14.3
pytz 2020.1 -> 2020.5
shap 0.37.0 -> 0.38.1
tensorflow 2.4.0 -> 2.4.1
torchvision 0.8.1 -> 0.8.2
xgboost 1.3.1 -> 1.3.3

System environment

The system environment in Databricks Runtime 8.1 ML differs from Databricks Runtime 8.1 as follows:

DBUtils: Databricks Runtime ML does not include Library utility (dbutils.library) (legacy). Use %pip and %conda commands instead. See Notebook-scoped Python libraries.
For GPU clusters, Databricks Runtime ML includes the following NVIDIA GPU libraries:
- CUDA 11.0
- cuDNN 8.0.4.30
- NCCL 2.7.8
- TensorRT 7.1.3

Libraries

The following sections list the libraries included in Databricks Runtime 8.1 ML that differ from those included in Databricks Runtime 8.1.

In this section:

Top-tier libraries
Python libraries
R libraries
Java and Scala libraries (Scala 2.12 cluster)

Top-tier libraries

Databricks Runtime 8.1 ML includes the following top-tier libraries:

Python libraries

Databricks Runtime 8.1 ML uses Conda for Python package management and includes many popular ML packages.

In addition to the packages specified in the Conda environments in the following sections, Databricks Runtime 8.1 ML also includes the following packages:

hyperopt 0.2.5.db1
sparkdl 2.1.0.db4

Python libraries on CPU clusters

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
  - 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
  - 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
  - gunicorn=20.0.4=py38_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
  - libuv=1.40.0=h7b6447c_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
  - 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
  - openssl=1.1.1k=h27cfd23_0 # (updated from 1.1.1j 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=1.7.1=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=0.3.4=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=0.8.2=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
  - 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:
    - astunparse==1.6.3
    - azure-core==1.11.0
    - azure-storage-blob==12.7.1
    - databricks-cli==0.14.1
    - diskcache==5.2.1
    - docker==4.4.4
    - flatbuffers==1.12
    - gast==0.3.3
    - grpcio==1.32.0
    - horovod==0.21.1
    - joblibspark==0.3.0
    - keras-preprocessing==1.1.2
    - koalas==1.6.0
    - llvmlite==0.35.0
    - mleap==0.16.1
    - mlflow==1.14.1
    - msrest==0.6.21
    - numba==0.52.0
    - opt-einsum==3.3.0
    - petastorm==0.9.8
    - pyarrow==1.0.1
    - pyyaml==5.4.1
    - querystring-parser==1.2.4
    - seaborn==0.10.0
    - shap==0.38.1
    - slicer==0.0.7
    - spark-tensorflow-distributor==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
    - xgboost==1.3.3
prefix: /databricks/conda/envs/databricks-ml

Python libraries on GPU clusters

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=py38_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=0.3.4=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:
    - astunparse==1.6.3
    - azure-core==1.11.0
    - azure-storage-blob==12.7.1
    - databricks-cli==0.14.1
    - diskcache==5.2.1
    - docker==4.4.4
    - flatbuffers==1.12
    - gast==0.3.3
    - horovod==0.21.1
    - joblibspark==0.3.0
    - keras-preprocessing==1.1.2
    - koalas==1.6.0
    - llvmlite==0.35.0
    - mleap==0.16.1
    - mlflow==1.14.1
    - msrest==0.6.21
    - numba==0.52.0
    - opt-einsum==3.3.0
    - petastorm==0.9.8
    - pyarrow==1.0.1
    - pyyaml==5.4.1
    - querystring-parser==1.2.4
    - seaborn==0.10.0
    - shap==0.38.1
    - slicer==0.0.7
    - spark-tensorflow-distributor==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
    - torch==1.7.1
    - torchvision==0.8.2
    - xgboost==1.3.3
prefix: /databricks/conda/envs/databricks-ml-gpu

Spark packages containing Python modules

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

R libraries

The R libraries are identical to the R Libraries in Databricks Runtime 8.1.

Java and Scala libraries (Scala 2.12 cluster)

In addition to Java and Scala libraries in Databricks Runtime 8.1, Databricks Runtime 8.1 ML contains the following JARs:

CPU clusters

Group ID	Artifact 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	1.3.1
ml.dmlc	xgboost4j_2.12	1.3.1
org.mlflow	mlflow-client	1.14.1
org.scala-lang.modules	scala-java8-compat_2.12	0.8.0
org.tensorflow	spark-tensorflow-connector_2.12	1.15.0

GPU clusters

Group ID	Artifact 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	1.3.1
ml.dmlc	xgboost4j-gpu_2.12	1.3.1
org.mlflow	mlflow-client	1.14.1
org.scala-lang.modules	scala-java8-compat_2.12	0.8.0
org.tensorflow	spark-tensorflow-connector_2.12	1.15.0

Jaa