Databricks Runtime 5.5 LTS MLDatabricks Runtime 5.5 LTS ML

Databricks 于 2019 年 7 月发布了此映像。Databricks released this image in July 2019.

Databricks Runtime 5.5 LTS ML 基于 Databricks Runtime 5.5 LTS,它为机器学习和数据科学提供了现成可用的环境。Databricks Runtime 5.5 LTS ML provides a ready-to-go environment for machine learning and data science based on Databricks Runtime 5.5 LTS. 用于 ML 的 Databricks Runtime 包含许多常用的机器学习库,包括 TensorFlow、PyTorch、Keras 和 XGBoost。Databricks Runtime for ML contains many popular machine learning libraries, including TensorFlow, PyTorch, Keras, and XGBoost. 它还支持使用 Horovod 进行分布式深度学习训练。It also supports distributed deep learning training using Horovod.

有关详细信息,包括有关创建 Databricks Runtime ML 群集的说明,请参阅用于机器学习的 Databricks RuntimeFor more information, including instructions for creating a Databricks Runtime ML cluster, see Databricks Runtime for Machine Learning.

新增功能New features

Databricks Runtime 5.5 LTS ML 是基于 Databricks Runtime 5.5 LTS 构建的。Databricks Runtime 5.5 LTS ML is built on top of Databricks Runtime 5.5 LTS. 若要了解 Databricks Runtime 5.5 LTS 中的新增功能,请参阅 Databricks Runtime 5.5 LTS 发行说明。For information on what’s new in Databricks Runtime 5.5 LTS, see the Databricks Runtime 5.5 LTS release notes.

除了库更新,Databricks Runtime 5.5 LTS ML 还引入了以下新功能:In addition to library updates, Databricks Runtime 5.5 LTS ML introduces the following new features:

  • 添加了 MLflow 1.0 Python 包Added the MLflow 1.0 Python package

改进Improvements

  • 升级了机器学习库Upgraded machine learning libraries

    • Tensorflow 已从 1.12.0 升级到 1.13.1Tensorflow upgraded from 1.12.0 to 1.13.1
    • PyTorch 已从 0.4.1 升级到 1.1.0PyTorch upgraded from 0.4.1 to 1.1.0
    • scikit-learn 已从 0.19.1 升级到 0.20.3scikit-learn upgraded from 0.19.1 to 0.20.3
  • HorovodRunner 的单节点操作Single-node operation for HorovodRunner

    已启用 HorovodRunner,以便只在驱动程序节点上运行。Enabled HorovodRunner to run on only the driver node. 以前,若要使用 HorovodRunner,必须运行驱动程序和至少一个工作器节点。Previously, to use HorovodRunner you would have to run a driver and at least one worker node. 而通过本次更改,你现可在单个节点(即多 GPU 节点)中分发训练,从而更有效地使用计算资源。With this change, you can now distribute training within a single node (that is, a multi-GPU node) and thus use compute resources more efficiently.

弃用Deprecation

Hyperopt 库中,我们弃用了 hyperopt.SparkTrials 的以下属性:In the hyperopt library, we deprecated the following properties of hyperopt.SparkTrials:

  • SparkTrials.successful_trials_count
  • SparkTrials.failed_trials_count
  • SparkTrials.cancelled_trials_count
  • SparkTrials.total_trials_count

并将这些属性替换为以下函数:and replaced the properties with the following functions:

  • SparkTrials.count_successful_trials()
  • SparkTrials.count_failed_trials()
  • SparkTrials.count_cancelled_trials()
  • SparkTrials.count_total_trials()

系统环境System environment

Databricks Runtime 5.5 LTS ML 中的系统环境与 Databricks Runtime 5.5 不同,如下所示:The system environment in Databricks Runtime 5.5 LTS ML differs from Databricks Runtime 5.5 as follows:

  • Python:Python 3 群集使用 3.6.5,Python 2 群集使用 2.7.15。Python: 3.6.5 for Python 3 clusters and 2.7.15 for Python 2 clusters.
  • DBUtils:不包含库实用工具DBUtils: Does not contain Library utilities.
  • 对于 GPU 群集,以下 NVIDIA GPU 库:For GPU clusters, the following NVIDIA GPU libraries:
    • CUDA 10.0CUDA 10.0
    • CUDNN 7.6.0CUDNN 7.6.0

Libraries

以下部分列出了 Databricks Runtime 5.5 LTS ML 中包含的库,这些库与 Databricks Runtime 5.5 中包含的不同。The following sections list the libraries included in Databricks Runtime 5.5 LTS ML that differ from those included in Databricks Runtime 5.5.

顶层库Top-tier libraries

Databricks Runtime 5.5 LTS ML 包含以下顶层Databricks Runtime 5.5 LTS ML includes the following top-tier libraries:

Python 库Python libraries

Databricks Runtime 5.5 LTS ML 使用 Conda 进行 Python 包管理。Databricks Runtime 5.5 LTS ML uses Conda for Python package management. 因此,已安装的 Python 库相对于 Databricks Runtime 有很大区别。As a result, there are major differences in installed Python libraries compared to Databricks Runtime. 以下部分介绍了使用 Python 2 或 3 的 Databricks Runtime 5.5 LTS ML 群集的 Conda 环境,以及支持 CPU 或 GPU 的计算机。The following sections describe the Conda environments for Databricks Runtime 5.5 LTS ML clusters using Python 2 or 3, and CPU or GPU-enabled machines.

CPU 群集上的 Python 3Python 3 on CPU clusters

name: null
channels:
  - pytorch
  - defaults
dependencies:
  - _libgcc_mutex=0.1=main
  - _py-xgboost-mutex=2.0=cpu_0
  - _tflow_select=2.3.0=mkl
  - absl-py=0.7.1=py36_0
  - asn1crypto=0.24.0=py36_0
  - astor=0.7.1=py36_0
  - backcall=0.1.0=py36_0
  - backports=1.0=py_2
  - bcrypt=3.1.6=py36h7b6447c_0
  - blas=1.0=mkl
  - bleach=2.1.3=py36_0
  - boto=2.48.0=py36_1
  - boto3=1.7.62=py36h28b3542_1
  - botocore=1.10.62=py36h28b3542_0
  - ca-certificates=2018.03.07=0
  - certifi=2018.4.16=py36_0
  - cffi=1.11.5=py36he75722e_1
  - chardet=3.0.4=py36_1
  - click=7.0=py36_0
  - cloudpickle=0.8.0=py36_0
  - colorama=0.3.9=py36h489cec4_0
  - configparser=3.7.3=py36_1
  - cryptography=2.2.2=py36h14c3975_0
  - cycler=0.10.0=py36h93f1223_0
  - cython=0.28.2=py36h14c3975_0
  - decorator=4.3.0=py36_0
  - docutils=0.14=py36hb0f60f5_0
  - entrypoints=0.2.3=py36_2
  - et_xmlfile=1.0.1=py36hd6bccc3_0
  - flask=1.0.2=py36_1
  - freetype=2.8=hab7d2ae_1
  - gast=0.2.2=py36_0
  - gitdb2=2.0.5=py36_0
  - gitpython=2.1.11=py36_0
  - gmp=6.1.2=h6c8ec71_1
  - grpcio=1.12.1=py36hdbcaa40_0
  - gunicorn=19.9.0=py36_0
  - h5py=2.8.0=py36h989c5e5_3
  - hdf5=1.10.2=hba1933b_1
  - html5lib=1.0.1=py36_0
  - icu=58.2=h9c2bf20_1
  - idna=2.6=py36h82fb2a8_1
  - intel-openmp=2018.0.0=8
  - ipython=6.4.0=py36_1
  - ipython_genutils=0.2.0=py36_0
  - itsdangerous=0.24=py36_1
  - jdcal=1.4=py36_0
  - jedi=0.12.0=py36_1
  - jinja2=2.10=py36_0
  - jmespath=0.9.4=py_0
  - jpeg=9b=h024ee3a_2
  - jsonschema=2.6.0=py36_0
  - jupyter_client=5.2.3=py36_0
  - jupyter_core=4.4.0=py36_0
  - keras=2.2.4=0
  - keras-applications=1.0.8=py_0
  - keras-base=2.2.4=py36_0
  - keras-preprocessing=1.1.0=py_1
  - krb5=1.16.1=hc83ff2d_6
  - libedit=3.1.20170329=h6b74fdf_2
  - libffi=3.2.1=hd88cf55_4
  - libgcc-ng=7.3.0=hdf63c60_0
  - libgfortran-ng=7.2.0=hdf63c60_3
  - libpng=1.6.34=hb9fc6fc_0
  - libpq=10.4=h1ad7b7a_0
  - libprotobuf=3.8.0=hd408876_0
  - libsodium=1.0.16=h1bed415_0
  - libstdcxx-ng=7.3.0=hdf63c60_0
  - libtiff=4.0.9=he85c1e1_2
  - libxgboost=0.90=he6710b0_0
  - libxml2=2.9.8=h26e45fe_1
  - libxslt=1.1.32=h1312cb7_0
  - llvmlite=0.23.1=py36hdbcaa40_0
  - lxml=4.2.1=py36h23eabaa_0
  - mako=1.0.10=py_0
  - markdown=3.1.1=py36_0
  - markupsafe=1.0=py36h14c3975_1
  - mistune=0.8.3=py36h14c3975_1
  - mkl=2019.4=243
  - mkl_fft=1.0.12=py36ha843d7b_0
  - mkl_random=1.0.2=py36hd81dba3_0
  - mock=3.0.5=py36_0
  - msgpack-python=0.5.6=py36h6bb024c_1
  - nbconvert=5.3.1=py36_0
  - nbformat=4.4.0=py36h31c9010_0
  - ncurses=6.1=he6710b0_1
  - ninja=1.9.0=py36hfd86e86_0
  - numba=0.38.0=py36h637b7d7_0
  - numpy=1.16.2=py36h7e9f1db_0
  - numpy-base=1.16.2=py36hde5b4d6_0
  - olefile=0.45.1=py36_0
  - openpyxl=2.5.3=py36_0
  - openssl=1.0.2o=h14c3975_1
  - pandas=0.23.0=py36h637b7d7_0
  - pandocfilters=1.4.2=py36_1
  - paramiko=2.4.2=py36_0
  - parso=0.2.0=py36_0
  - pathlib2=2.3.2=py36_0
  - patsy=0.5.0=py36_0
  - pexpect=4.5.0=py36_0
  - pickleshare=0.7.4=py36_0
  - pillow=5.1.0=py36h3deb7b8_0
  - pip=10.0.1=py36_0
  - ply=3.11=py36_0
  - prompt_toolkit=1.0.15=py36h17d85b1_0
  - protobuf=3.8.0=py36he6710b0_0
  - psycopg2=2.7.5=py36hb7f436b_0
  - ptyprocess=0.5.2=py36h69acd42_0
  - py-xgboost=0.90=py36he6710b0_0
  - py-xgboost-cpu=0.90=py36_0
  - pyasn1=0.4.5=py_0
  - pycparser=2.18=py36_1
  - pygments=2.2.0=py36_0
  - pynacl=1.3.0=py36h7b6447c_0
  - pyopenssl=18.0.0=py36_0
  - pyparsing=2.2.0=py36_1
  - pysocks=1.6.8=py36_0
  - python=3.6.5=hc3d631a_2
  - python-dateutil=2.7.3=py36_0
  - python-editor=1.0.4=py_0
  - pytz=2018.4=py36_0
  - pyyaml=5.1=py36h7b6447c_0
  - pyzmq=17.0.0=py36h14c3975_3
  - readline=7.0=h7b6447c_5
  - requests=2.18.4=py36he2e5f8d_1
  - s3transfer=0.1.13=py36_0
  - scikit-learn=0.20.3=py36hd81dba3_0
  - scipy=1.1.0=py36h7c811a0_2
  - setuptools=39.1.0=py36_0
  - simplegeneric=0.8.1=py36_2
  - simplejson=3.16.0=py36h14c3975_0
  - singledispatch=3.4.0.3=py36_0
  - six=1.11.0=py36_1
  - smmap2=2.0.5=py36_0
  - sqlite=3.23.1=he433501_0
  - sqlparse=0.3.0=py_0
  - statsmodels=0.9.0=py36h035aef0_0
  - tabulate=0.8.3=py36_0
  - tensorboard=1.13.1=py36hf484d3e_0
  - tensorflow=1.13.1=mkl_py36h27d456a_0
  - tensorflow-base=1.13.1=mkl_py36h7ce6ba3_0
  - tensorflow-estimator=1.13.0=py_0
  - tensorflow-mkl=1.13.1=h4fcabd2_0
  - termcolor=1.1.0=py36_1
  - testpath=0.3.1=py36h8cadb63_0
  - tk=8.6.7=hc745277_3
  - tornado=5.0.2=py36h14c3975_0
  - traitlets=4.3.2=py36_0
  - urllib3=1.22=py36hbe7ace6_0
  - virtualenv=16.0.0=py36_0
  - wcwidth=0.1.7=py36hdf4376a_0
  - webencodings=0.5.1=py36_1
  - werkzeug=0.14.1=py36_0
  - wheel=0.31.1=py36_0
  - wrapt=1.11.1=py36h7b6447c_0
  - xz=5.2.4=h14c3975_4
  - yaml=0.1.7=had09818_2
  - zeromq=4.2.5=hf484d3e_1
  - zlib=1.2.11=h7b6447c_3
  - pytorch-cpu=1.1.0=py3.6_cpu_0
  - torchvision-cpu=0.3.0=py36_cuNone_1
  - pip:
    - databricks-cli==0.8.7
    - docker==4.0.2
    - fusepy==2.0.4
    - future==0.17.1
    - horovod==0.16.4
    - hyperopt==0.1.2.db6
    - kiwisolver==1.1.0
    - matplotlib==2.2.2
    - mleap==0.8.1
    - mlflow==1.0.0
    - msgpack==0.5.6
    - networkx==2.2
    - nose==1.3.7
    - nose-exclude==0.5.0
    - psutil==5.6.3
    - pyarrow==0.13.0
    - pymongo==3.8.0
    - querystring-parser==1.2.3
    - seaborn==0.8.1
    - tensorboardx==1.7
    - torchvision==0.3.0
    - tqdm==4.32.2
    - websocket-client==0.56.0
prefix: /databricks/python3

GPU 群集上的 Python 3Python 3 on GPU clusters

name: null
channels:
  - pytorch
  - Databricks
  - defaults
dependencies:
  - tensorflow=1.13.1.db1=gpu_py36h2903d8e_0
  - tensorflow-base=1.13.1.db1=gpu_py36he292aa2_0
  - tensorflow-gpu=1.13.1.db1=h0d30ee6_0
  - _libgcc_mutex=0.1=main
  - _py-xgboost-mutex=1.0=gpu_0
  - _tflow_select=2.1.0=gpu
  - absl-py=0.7.1=py36_0
  - asn1crypto=0.24.0=py36_0
  - astor=0.7.1=py36_0
  - backcall=0.1.0=py36_0
  - backports=1.0=py_2
  - bcrypt=3.1.6=py36h7b6447c_0
  - blas=1.0=mkl
  - bleach=2.1.3=py36_0
  - boto=2.48.0=py36_1
  - boto3=1.7.62=py36h28b3542_1
  - botocore=1.10.62=py36h28b3542_0
  - ca-certificates=2018.03.07=0
  - certifi=2018.4.16=py36_0
  - cffi=1.11.5=py36he75722e_1
  - chardet=3.0.4=py36_1
  - click=7.0=py36_0
  - cloudpickle=0.8.0=py36_0
  - colorama=0.3.9=py36h489cec4_0
  - configparser=3.7.3=py36_1
  - cryptography=2.2.2=py36h14c3975_0
  - cudnn=7.6.0=cuda10.0_0
  - cupti=10.0.130=0
  - cycler=0.10.0=py36_0
  - cython=0.28.2=py36h14c3975_0
  - decorator=4.3.0=py36_0
  - docutils=0.14=py36_0
  - entrypoints=0.2.3=py36_2
  - et_xmlfile=1.0.1=py36hd6bccc3_0
  - flask=1.0.2=py36_1
  - freetype=2.8=hab7d2ae_1
  - gast=0.2.2=py36_0
  - gitdb2=2.0.5=py36_0
  - gitpython=2.1.11=py36_0
  - gmp=6.1.2=h6c8ec71_1
  - grpcio=1.12.1=py36hdbcaa40_0
  - gunicorn=19.9.0=py36_0
  - h5py=2.8.0=py36h989c5e5_3
  - hdf5=1.10.2=hba1933b_1
  - html5lib=1.0.1=py36_0
  - icu=58.2=h9c2bf20_1
  - idna=2.6=py36h82fb2a8_1
  - intel-openmp=2018.0.0=8
  - ipython=6.4.0=py36_1
  - ipython_genutils=0.2.0=py36hb52b0d5_0
  - itsdangerous=0.24=py36_1
  - jdcal=1.4=py36_0
  - jedi=0.12.0=py36_1
  - jinja2=2.10=py36_0
  - jmespath=0.9.4=py_0
  - jpeg=9b=h024ee3a_2
  - jsonschema=2.6.0=py36_0
  - jupyter_client=5.2.3=py36_0
  - jupyter_core=4.4.0=py36_0
  - keras=2.2.4=0
  - keras-applications=1.0.8=py_0
  - keras-base=2.2.4=py36_0
  - keras-preprocessing=1.1.0=py_1
  - krb5=1.16.1=hc83ff2d_6
  - libedit=3.1.20170329=h6b74fdf_2
  - libffi=3.2.1=hd88cf55_4
  - libgcc-ng=7.3.0=hdf63c60_0
  - libgfortran-ng=7.2.0=hdf63c60_3
  - libpng=1.6.34=hb9fc6fc_0
  - libpq=10.4=h1ad7b7a_0
  - libprotobuf=3.8.0=hd408876_0
  - libsodium=1.0.16=h1bed415_0
  - libstdcxx-ng=7.3.0=hdf63c60_0
  - libtiff=4.0.9=he85c1e1_2
  - libxgboost=0.90=h688424c_0
  - libxml2=2.9.8=h26e45fe_1
  - libxslt=1.1.32=h1312cb7_0
  - llvmlite=0.23.1=py36hdbcaa40_0
  - lxml=4.2.1=py36h23eabaa_0
  - mako=1.0.10=py_0
  - markdown=3.1.1=py36_0
  - markupsafe=1.0=py36h14c3975_1
  - mistune=0.8.3=py36h14c3975_1
  - mkl=2019.4=243
  - mkl_fft=1.0.12=py36ha843d7b_0
  - mkl_random=1.0.2=py36hd81dba3_0
  - mock=3.0.5=py36_0
  - msgpack-python=0.5.6=py36h6bb024c_1
  - nbconvert=5.3.1=py36_0
  - nbformat=4.4.0=py36h31c9010_0
  - ncurses=6.1=he6710b0_1
  - ninja=1.9.0=py36hfd86e86_0
  - numba=0.38.0=py36h637b7d7_0
  - numpy=1.16.2=py36h7e9f1db_0
  - numpy-base=1.16.2=py36hde5b4d6_0
  - olefile=0.45.1=py36_0
  - openpyxl=2.5.3=py36_0
  - openssl=1.0.2o=h14c3975_1
  - pandas=0.23.0=py36h637b7d7_0
  - pandocfilters=1.4.2=py36_1
  - paramiko=2.4.2=py36_0
  - parso=0.2.0=py36_0
  - pathlib2=2.3.2=py36_0
  - patsy=0.5.0=py36_0
  - pexpect=4.5.0=py36_0
  - pickleshare=0.7.4=py36h63277f8_0
  - pillow=5.1.0=py36h3deb7b8_0
  - pip=10.0.1=py36_0
  - ply=3.11=py36_0
  - prompt_toolkit=1.0.15=py36_0
  - protobuf=3.8.0=py36he6710b0_0
  - psycopg2=2.7.5=py36hb7f436b_0
  - ptyprocess=0.5.2=py36h69acd42_0
  - py-xgboost=0.90=py36h688424c_0
  - py-xgboost-gpu=0.90=py36h28bbb66_0
  - pyasn1=0.4.5=py_0
  - pycparser=2.18=py36_1
  - pygments=2.2.0=py36_0
  - pynacl=1.3.0=py36h7b6447c_0
  - pyopenssl=18.0.0=py36_0
  - pyparsing=2.2.0=py36_1
  - pysocks=1.6.8=py36_0
  - python=3.6.5=hc3d631a_2
  - python-dateutil=2.7.3=py36_0
  - python-editor=1.0.4=py_0
  - pytz=2018.4=py36_0
  - pyyaml=5.1=py36h7b6447c_0
  - pyzmq=17.0.0=py36h14c3975_3
  - readline=7.0=h7b6447c_5
  - requests=2.18.4=py36he2e5f8d_1
  - s3transfer=0.1.13=py36_0
  - scikit-learn=0.20.3=py36hd81dba3_0
  - scipy=1.1.0=py36h7c811a0_2
  - setuptools=39.1.0=py36_0
  - simplegeneric=0.8.1=py36_2
  - simplejson=3.16.0=py36h14c3975_0
  - singledispatch=3.4.0.3=py36h7a266c3_0
  - six=1.11.0=py36_1
  - smmap2=2.0.5=py36_0
  - sqlite=3.23.1=he433501_0
  - sqlparse=0.3.0=py_0
  - statsmodels=0.9.0=py36h035aef0_0
  - tabulate=0.8.3=py36_0
  - tensorboard=1.13.1=py36hf484d3e_0
  - tensorflow-estimator=1.13.0=py_0
  - termcolor=1.1.0=py36_1
  - testpath=0.3.1=py36_0
  - tk=8.6.7=hc745277_3
  - tornado=5.0.2=py36h14c3975_0
  - traitlets=4.3.2=py36h674d592_0
  - urllib3=1.22=py36hbe7ace6_0
  - virtualenv=16.0.0=py36_0
  - wcwidth=0.1.7=py36hdf4376a_0
  - webencodings=0.5.1=py36_1
  - werkzeug=0.14.1=py36_0
  - wheel=0.31.1=py36_0
  - wrapt=1.11.1=py36h7b6447c_0
  - xz=5.2.4=h14c3975_4
  - yaml=0.1.7=had09818_2
  - zeromq=4.2.5=hf484d3e_1
  - zlib=1.2.11=h7b6447c_3
  - pytorch=1.1.0=py3.6_cuda10.0.130_cudnn7.5.1_0
  - torchvision=0.3.0=py36_cu10.0.130_1
  - pip:
    - databricks-cli==0.8.7
    - docker==4.0.2
    - fusepy==2.0.4
    - future==0.17.1
    - horovod==0.16.4
    - hyperopt==0.1.2.db6
    - kiwisolver==1.1.0
    - matplotlib==2.2.2
    - mleap==0.8.1
    - mlflow==1.0.0
    - msgpack==0.5.6
    - networkx==2.2
    - nose==1.3.7
    - nose-exclude==0.5.0
    - psutil==5.6.3
    - pyarrow==0.13.0
    - pymongo==3.8.0
    - querystring-parser==1.2.3
    - seaborn==0.8.1
    - tensorboardx==1.7
    - tqdm==4.32.2
    - websocket-client==0.56.0
prefix: /databricks/python3

CPU 群集上的 Python 2Python 2 on CPU clusters

name: null
channels:
  - pytorch
  - defaults
dependencies:
  - _libgcc_mutex=0.1=main
  - _py-xgboost-mutex=2.0=cpu_0
  - _tflow_select=2.3.0=mkl
  - absl-py=0.7.1=py27_0
  - asn1crypto=0.24.0=py27_0
  - astor=0.7.1=py27_0
  - backports=1.0=py_2
  - backports.shutil_get_terminal_size=1.0.0=py27_2
  - backports.weakref=1.0.post1=py_1
  - backports_abc=0.5=py_0
  - bcrypt=3.1.6=py27h7b6447c_0
  - blas=1.0=mkl
  - bleach=2.1.3=py27_0
  - boto=2.48.0=py27_1
  - boto3=1.7.62=py27h28b3542_1
  - botocore=1.10.62=py27h28b3542_0
  - ca-certificates=2018.03.07=0
  - certifi=2018.4.16=py27_0
  - cffi=1.11.5=py27he75722e_1
  - chardet=3.0.4=py27_1
  - click=7.0=py27_0
  - cloudpickle=0.8.0=py27_0
  - colorama=0.3.9=py27h5cde069_0
  - configparser=3.7.3=py27_1
  - cryptography=2.2.2=py27h14c3975_0
  - cycler=0.10.0=py27hc7354d3_0
  - cython=0.28.2=py27h14c3975_0
  - decorator=4.3.0=py27_0
  - docutils=0.14=py27_0
  - entrypoints=0.2.3=py27_2
  - enum34=1.1.6=py27_1
  - et_xmlfile=1.0.1=py27_0
  - flask=1.0.2=py27_1
  - freetype=2.8=hab7d2ae_1
  - funcsigs=1.0.2=py27_0
  - functools32=3.2.3.2=py27_1
  - future=0.17.1=py27_0
  - futures=3.2.0=py27_0
  - gast=0.2.2=py27_0
  - gitdb2=2.0.5=py27_0
  - gitpython=2.1.11=py27_0
  - gmp=6.1.2=h6c8ec71_1
  - grpcio=1.12.1=py27hdbcaa40_0
  - gunicorn=19.9.0=py27_0
  - h5py=2.8.0=py27h989c5e5_3
  - hdf5=1.10.2=hba1933b_1
  - html5lib=1.0.1=py27_0
  - icu=58.2=h9c2bf20_1
  - idna=2.6=py27h5722d68_1
  - intel-openmp=2018.0.0=8
  - ipaddress=1.0.22=py27_0
  - ipython=5.7.0=py27_0
  - ipython_genutils=0.2.0=py27_0
  - itsdangerous=0.24=py27_1
  - jdcal=1.4=py27_0
  - jinja2=2.10=py27_0
  - jmespath=0.9.4=py_0
  - jpeg=9b=h024ee3a_2
  - jsonschema=2.6.0=py27h7ed5aa4_0
  - jupyter_client=5.2.3=py27_0
  - jupyter_core=4.4.0=py27_0
  - keras=2.2.4=0
  - keras-applications=1.0.8=py_0
  - keras-base=2.2.4=py27_0
  - keras-preprocessing=1.1.0=py_1
  - krb5=1.16.1=hc83ff2d_6
  - libedit=3.1.20170329=h6b74fdf_2
  - libffi=3.2.1=hd88cf55_4
  - libgcc-ng=7.3.0=hdf63c60_0
  - libgfortran-ng=7.2.0=hdf63c60_3
  - libpng=1.6.34=hb9fc6fc_0
  - libpq=10.4=h1ad7b7a_0
  - libprotobuf=3.8.0=hd408876_0
  - libsodium=1.0.16=h1bed415_0
  - libstdcxx-ng=7.3.0=hdf63c60_0
  - libtiff=4.0.9=he85c1e1_2
  - libxgboost=0.90=he6710b0_0
  - libxml2=2.9.8=h26e45fe_1
  - libxslt=1.1.32=h1312cb7_0
  - linecache2=1.0.0=py27_0
  - llvmlite=0.23.1=py27hdbcaa40_0
  - lxml=4.2.1=py27h23eabaa_0
  - mako=1.0.10=py_0
  - markdown=3.1.1=py27_0
  - markupsafe=1.0=py27h14c3975_1
  - mistune=0.8.3=py27h14c3975_1
  - mkl=2019.4=243
  - mkl_fft=1.0.12=py27ha843d7b_0
  - mkl_random=1.0.2=py27hd81dba3_0
  - mock=3.0.5=py27_0
  - msgpack-python=0.5.6=py27h6bb024c_1
  - nbconvert=5.3.1=py27_0
  - nbformat=4.4.0=py27hed7f2b2_0
  - ncurses=6.1=he6710b0_1
  - ninja=1.9.0=py27hfd86e86_0
  - numba=0.38.0=py27h637b7d7_0
  - numpy=1.16.2=py27h7e9f1db_0
  - numpy-base=1.16.2=py27hde5b4d6_0
  - olefile=0.45.1=py27_0
  - openpyxl=2.5.3=py27_0
  - openssl=1.0.2o=h14c3975_1
  - pandas=0.23.0=py27h637b7d7_0
  - pandocfilters=1.4.2=py27_1
  - paramiko=2.4.2=py27_0
  - pathlib2=2.3.2=py27_0
  - patsy=0.5.0=py27_0
  - pexpect=4.5.0=py27_0
  - pickleshare=0.7.4=py27_0
  - pillow=5.1.0=py27h3deb7b8_0
  - pip=10.0.1=py27_0
  - ply=3.11=py27_0
  - prompt_toolkit=1.0.15=py27_0
  - protobuf=3.8.0=py27he6710b0_0
  - psycopg2=2.7.5=py27hb7f436b_0
  - ptyprocess=0.5.2=py27h4ccb14c_0
  - py-xgboost=0.90=py27he6710b0_0
  - py-xgboost-cpu=0.90=py27_0
  - pyasn1=0.4.5=py_0
  - pycparser=2.18=py27_1
  - pygments=2.2.0=py27_0
  - pynacl=1.3.0=py27h7b6447c_0
  - pyopenssl=18.0.0=py27_0
  - pyparsing=2.2.0=py27_1
  - pysocks=1.6.8=py27_0
  - python=2.7.15=h1571d57_0
  - python-dateutil=2.7.3=py27_0
  - python-editor=1.0.4=py_0
  - pytz=2018.4=py27_0
  - pyyaml=5.1=py27h7b6447c_0
  - pyzmq=17.0.0=py27h14c3975_3
  - readline=7.0=h7b6447c_5
  - requests=2.18.4=py27hc5b0589_1
  - s3transfer=0.1.13=py27_0
  - scandir=1.7=py27h14c3975_0
  - scikit-learn=0.20.3=py27hd81dba3_0
  - scipy=1.1.0=py27h7c811a0_2
  - setuptools=39.1.0=py27_0
  - simplegeneric=0.8.1=py27_2
  - simplejson=3.16.0=py27h14c3975_0
  - singledispatch=3.4.0.3=py27_0
  - six=1.11.0=py27_1
  - smmap2=2.0.5=py27_0
  - sqlite=3.23.1=he433501_0
  - sqlparse=0.3.0=py_0
  - statsmodels=0.9.0=py27h035aef0_0
  - tabulate=0.8.3=py27_0
  - tensorboard=1.13.1=py27hf484d3e_0
  - tensorflow=1.13.1=mkl_py27h74ee40f_0
  - tensorflow-base=1.13.1=mkl_py27h7ce6ba3_0
  - tensorflow-estimator=1.13.0=py_0
  - tensorflow-mkl=1.13.1=h4fcabd2_0
  - termcolor=1.1.0=py27_1
  - testpath=0.3.1=py27hc38d2c4_0
  - tk=8.6.7=hc745277_3
  - tornado=5.0.2=py27h14c3975_0
  - traceback2=1.4.0=py27_0
  - traitlets=4.3.2=py27_0
  - unittest2=1.1.0=py27_0
  - urllib3=1.22=py27ha55213b_0
  - virtualenv=16.0.0=py27_0
  - wcwidth=0.1.7=py27h9e3e1ab_0
  - webencodings=0.5.1=py27_1
  - werkzeug=0.14.1=py27_0
  - wheel=0.31.1=py27_0
  - wrapt=1.11.1=py27h7b6447c_0
  - xz=5.2.4=h14c3975_4
  - yaml=0.1.7=had09818_2
  - zeromq=4.2.5=hf484d3e_1
  - zlib=1.2.11=h7b6447c_3
  - pytorch-cpu=1.1.0=py2.7_cpu_0
  - torchvision-cpu=0.3.0=py27_cuNone_1
  - pip:
    - backports.functools-lru-cache==1.5
    - backports.ssl-match-hostname==3.7.0.1
    - databricks-cli==0.8.7
    - docker==4.0.2
    - fusepy==2.0.4
    - horovod==0.16.4
    - hyperopt==0.1.2.db6
    - kiwisolver==1.1.0
    - matplotlib==2.2.2
    - mleap==0.8.1
    - mlflow==1.0.0
    - msgpack==0.5.6
    - networkx==2.2
    - nose==1.3.7
    - nose-exclude==0.5.0
    - psutil==5.6.3
    - pyarrow==0.13.0
    - pymongo==3.8.0
    - querystring-parser==1.2.3
    - seaborn==0.8.1
    - subprocess32==3.5.4
    - tensorboardx==1.7
    - torchvision==0.3.0
    - tqdm==4.32.2
    - websocket-client==0.56.0
prefix: /databricks/python2

GPU 群集上的 Python 2Python 2 on GPU clusters

name: null
channels:
  - Databricks
  - pytorch
  - defaults
dependencies:
  - tensorflow=1.13.1.db1=gpu_py27h8e347d7_0
  - tensorflow-base=1.13.1.db1=gpu_py27he292aa2_0
  - tensorflow-gpu=1.13.1.db1=h0d30ee6_0
  - _libgcc_mutex=0.1=main
  - _py-xgboost-mutex=1.0=gpu_0
  - _tflow_select=2.1.0=gpu
  - absl-py=0.7.1=py27_0
  - asn1crypto=0.24.0=py27_0
  - astor=0.7.1=py27_0
  - backports=1.0=py_2
  - backports.shutil_get_terminal_size=1.0.0=py27_2
  - backports.weakref=1.0.post1=py_1
  - backports_abc=0.5=py_0
  - bcrypt=3.1.6=py27h7b6447c_0
  - blas=1.0=mkl
  - bleach=2.1.3=py27_0
  - boto=2.48.0=py27_1
  - boto3=1.7.62=py27h28b3542_1
  - botocore=1.10.62=py27h28b3542_0
  - ca-certificates=2018.03.07=0
  - certifi=2018.4.16=py27_0
  - cffi=1.11.5=py27he75722e_1
  - chardet=3.0.4=py27_1
  - click=7.0=py27_0
  - cloudpickle=0.8.0=py27_0
  - colorama=0.3.9=py27_0
  - configparser=3.7.3=py27_1
  - cryptography=2.2.2=py27h14c3975_0
  - cudnn=7.6.0=cuda10.0_0
  - cupti=10.0.130=0
  - cycler=0.10.0=py27_0
  - cython=0.28.2=py27h14c3975_0
  - decorator=4.3.0=py27_0
  - docutils=0.14=py27hae222c1_0
  - entrypoints=0.2.3=py27_2
  - enum34=1.1.6=py27_1
  - et_xmlfile=1.0.1=py27h75840f5_0
  - flask=1.0.2=py27_1
  - freetype=2.8=hab7d2ae_1
  - funcsigs=1.0.2=py27_0
  - functools32=3.2.3.2=py27_1
  - future=0.17.1=py27_0
  - futures=3.2.0=py27_0
  - gast=0.2.2=py27_0
  - gitdb2=2.0.5=py27_0
  - gitpython=2.1.11=py27_0
  - gmp=6.1.2=h6c8ec71_1
  - grpcio=1.12.1=py27hdbcaa40_0
  - gunicorn=19.9.0=py27_0
  - h5py=2.8.0=py27h989c5e5_3
  - hdf5=1.10.2=hba1933b_1
  - html5lib=1.0.1=py27_0
  - icu=58.2=h9c2bf20_1
  - idna=2.6=py27h5722d68_1
  - intel-openmp=2018.0.0=8
  - ipaddress=1.0.22=py27_0
  - ipython=5.7.0=py27_0
  - ipython_genutils=0.2.0=py27h89fb69b_0
  - itsdangerous=0.24=py27_1
  - jdcal=1.4=py27_0
  - jinja2=2.10=py27_0
  - jmespath=0.9.4=py_0
  - jpeg=9b=h024ee3a_2
  - jsonschema=2.6.0=py27h7ed5aa4_0
  - jupyter_client=5.2.3=py27_0
  - jupyter_core=4.4.0=py27_0
  - keras=2.2.4=0
  - keras-applications=1.0.8=py_0
  - keras-base=2.2.4=py27_0
  - keras-preprocessing=1.1.0=py_1
  - krb5=1.16.1=hc83ff2d_6
  - libedit=3.1.20170329=h6b74fdf_2
  - libffi=3.2.1=hd88cf55_4
  - libgcc-ng=7.3.0=hdf63c60_0
  - libgfortran-ng=7.2.0=hdf63c60_3
  - libpng=1.6.34=hb9fc6fc_0
  - libpq=10.4=h1ad7b7a_0
  - libprotobuf=3.8.0=hd408876_0
  - libsodium=1.0.16=h1bed415_0
  - libstdcxx-ng=7.3.0=hdf63c60_0
  - libtiff=4.0.9=he85c1e1_2
  - libxgboost=0.90=h688424c_0
  - libxml2=2.9.8=h26e45fe_1
  - libxslt=1.1.32=h1312cb7_0
  - linecache2=1.0.0=py27_0
  - llvmlite=0.23.1=py27hdbcaa40_0
  - lxml=4.2.1=py27h23eabaa_0
  - mako=1.0.10=py_0
  - markdown=3.1.1=py27_0
  - markupsafe=1.0=py27h14c3975_1
  - mistune=0.8.3=py27h14c3975_1
  - mkl=2019.4=243
  - mkl_fft=1.0.12=py27ha843d7b_0
  - mkl_random=1.0.2=py27hd81dba3_0
  - mock=3.0.5=py27_0
  - msgpack-python=0.5.6=py27h6bb024c_1
  - nbconvert=5.3.1=py27_0
  - nbformat=4.4.0=py27hed7f2b2_0
  - ncurses=6.1=he6710b0_1
  - ninja=1.9.0=py27hfd86e86_0
  - numba=0.38.0=py27h637b7d7_0
  - numpy=1.16.2=py27h7e9f1db_0
  - numpy-base=1.16.2=py27hde5b4d6_0
  - olefile=0.45.1=py27_0
  - openpyxl=2.5.3=py27_0
  - openssl=1.0.2o=h14c3975_1
  - pandas=0.23.0=py27h637b7d7_0
  - pandocfilters=1.4.2=py27_1
  - paramiko=2.4.2=py27_0
  - pathlib2=2.3.2=py27_0
  - patsy=0.5.0=py27_0
  - pexpect=4.5.0=py27_0
  - pickleshare=0.7.4=py27h09770e1_0
  - pillow=5.1.0=py27h3deb7b8_0
  - pip=10.0.1=py27_0
  - ply=3.11=py27_0
  - prompt_toolkit=1.0.15=py27_0
  - protobuf=3.8.0=py27he6710b0_0
  - psycopg2=2.7.5=py27hb7f436b_0
  - ptyprocess=0.5.2=py27h4ccb14c_0
  - py-xgboost=0.90=py27h688424c_0
  - py-xgboost-gpu=0.90=py27h28bbb66_0
  - pyasn1=0.4.5=py_0
  - pycparser=2.18=py27_1
  - pygments=2.2.0=py27_0
  - pynacl=1.3.0=py27h7b6447c_0
  - pyopenssl=18.0.0=py27_0
  - pyparsing=2.2.0=py27_1
  - pysocks=1.6.8=py27_0
  - python=2.7.15=h1571d57_0
  - python-dateutil=2.7.3=py27_0
  - python-editor=1.0.4=py_0
  - pytz=2018.4=py27_0
  - pyyaml=5.1=py27h7b6447c_0
  - pyzmq=17.0.0=py27h14c3975_3
  - readline=7.0=h7b6447c_5
  - requests=2.18.4=py27hc5b0589_1
  - s3transfer=0.1.13=py27_0
  - scandir=1.7=py27h14c3975_0
  - scikit-learn=0.20.3=py27hd81dba3_0
  - scipy=1.1.0=py27h7c811a0_2
  - setuptools=39.1.0=py27_0
  - simplegeneric=0.8.1=py27_2
  - simplejson=3.16.0=py27h14c3975_0
  - singledispatch=3.4.0.3=py27h9bcb476_0
  - six=1.11.0=py27_1
  - smmap2=2.0.5=py27_0
  - sqlite=3.23.1=he433501_0
  - sqlparse=0.3.0=py_0
  - statsmodels=0.9.0=py27h035aef0_0
  - tabulate=0.8.3=py27_0
  - tensorboard=1.13.1=py27hf484d3e_0
  - tensorflow-estimator=1.13.0=py_0
  - termcolor=1.1.0=py27_1
  - testpath=0.3.1=py27_0
  - tk=8.6.7=hc745277_3
  - tornado=5.0.2=py27h14c3975_0
  - traceback2=1.4.0=py27_0
  - traitlets=4.3.2=py27hd6ce930_0
  - unittest2=1.1.0=py27_0
  - urllib3=1.22=py27ha55213b_0
  - virtualenv=16.0.0=py27_0
  - wcwidth=0.1.7=py27_0
  - webencodings=0.5.1=py27_1
  - werkzeug=0.14.1=py27_0
  - wheel=0.31.1=py27_0
  - wrapt=1.11.1=py27h7b6447c_0
  - xz=5.2.4=h14c3975_4
  - yaml=0.1.7=had09818_2
  - zeromq=4.2.5=hf484d3e_1
  - zlib=1.2.11=h7b6447c_3
  - pytorch=1.1.0=py2.7_cuda10.0.130_cudnn7.5.1_0
  - torchvision=0.3.0=py27_cu10.0.130_1
  - pip:
    - backports.functools-lru-cache==1.5
    - backports.ssl-match-hostname==3.7.0.1
    - databricks-cli==0.8.7
    - docker==4.0.2
    - fusepy==2.0.4
    - horovod==0.16.4
    - hyperopt==0.1.2.db6
    - kiwisolver==1.1.0
    - matplotlib==2.2.2
    - mleap==0.8.1
    - mlflow==1.0.0
    - msgpack==0.5.6
    - networkx==2.2
    - nose==1.3.7
    - nose-exclude==0.5.0
    - psutil==5.6.3
    - pyarrow==0.13.0
    - pymongo==3.8.0
    - querystring-parser==1.2.3
    - seaborn==0.8.1
    - subprocess32==3.5.4
    - tensorboardx==1.7
    - tqdm==4.32.2
    - websocket-client==0.56.0
prefix: /databricks/python2

包含 Python 模块的 Spark 包Spark packages containing Python modules

Spark 包Spark Package Python 模块Python Module 版本Version
graphframesgraphframes graphframesgraphframes 0.7.0-db1-spark2.40.7.0-db1-spark2.4
spark-deep-learningspark-deep-learning sparkdlsparkdl 1.5.0-db4-spark2.41.5.0-db4-spark2.4
tensorframestensorframes tensorframestensorframes 0.7.0-s_2.110.7.0-s_2.11

R 库R libraries

R 库与 Databricks Runtime 5.5 中的 R 库完全相同。The R libraries are identical to the R Libraries in Databricks Runtime 5.5.

Java 库和 Scala 库(Scala 2.11 群集)Java and Scala libraries (Scala 2.11 cluster)

除了 Databricks Runtime 5.5 中的 Java 库和 Scala 库之外,Databricks Runtime 5.5 LTS ML 还包含以下 JAR:In addition to Java and Scala libraries in Databricks Runtime 5.5, Databricks Runtime 5.5 LTS ML contains the following JARs:

组 IDGroup ID 项目 IDArtifact ID 版本Version
com.databrickscom.databricks spark-deep-learningspark-deep-learning 1.5.0-db4-spark2.41.5.0-db4-spark2.4
com.typesafe.akkacom.typesafe.akka akka-actor_2.11akka-actor_2.11 2.3.112.3.11
ml.combust.mleapml.combust.mleap mleap-databricks-runtime_2.11mleap-databricks-runtime_2.11 0.13.00.13.0
ml.dmlcml.dmlc xgboost4jxgboost4j 0.900.90
ml.dmlcml.dmlc xgboost4j-sparkxgboost4j-spark 0.900.90
org.graphframesorg.graphframes graphframes_2.11graphframes_2.11 0.7.0-db1-spark2.40.7.0-db1-spark2.4
org.tensorfloworg.tensorflow libtensorflowlibtensorflow 1.13.11.13.1
org.tensorfloworg.tensorflow libtensorflow_jnilibtensorflow_jni 1.13.11.13.1
org.tensorfloworg.tensorflow spark-tensorflow-connector_2.11spark-tensorflow-connector_2.11 1.13.11.13.1
org.tensorfloworg.tensorflow tensorflowtensorflow 1.13.11.13.1
org.tensorframesorg.tensorframes tensorframestensorframes 0.7.0-s_2.110.7.0-s_2.11