Databricks Runtime 5.5 LTS MLDatabricks Runtime 5.5 LTS ML

Databricks は、2019年7月にこのイメージをリリースしました。Databricks released this image in July 2019.

Databricks Runtime 5.5 LTS ML は、 Databricks Runtime 5.5 LTSに基づく機械学習とデータサイエンスのための準備が整った環境を提供します。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. ML の Databricks Runtime には、PyTorch、Keras、XGBoost ストなど、多くの一般的な機械学習ライブラリが含まれています。Databricks Runtime for ML contains many popular machine learning libraries, including TensorFlow, PyTorch, Keras, and XGBoost. また、Horovod を使用した分散ディープラーニングトレーニングもサポートしています。It also supports distributed deep learning training using Horovod.

Databricks Runtime ML クラスターを作成する手順など、詳細については、 Machine Learning の Databricks Runtimeを参照してください。For more information, including instructions for creating a Databricks Runtime ML cluster, see Databricks Runtime for Machine Learning.

新機能New features

Databricks Runtime 5.5 LTS ML は Databricks Runtime 5.5 LTS の上に構築されています。Databricks Runtime 5.5 LTS ML is built on top of Databricks Runtime 5.5 LTS. Databricks Runtime 5.5 LTS の新機能の詳細については、 Databricks Runtime 5.5 LTSリリースノートを参照してください。For information on what’s new in Databricks Runtime 5.5 LTS, see the Databricks Runtime 5.5 LTS release notes.

Databricks Runtime 5.5 LTS ML では、ライブラリの更新に加えて、次の新機能が導入されています。In addition to library updates, Databricks Runtime 5.5 LTS ML introduces the following new features:

  • Mlflow 1.0 Python パッケージが追加されましたAdded the MLflow 1.0 Python package

改善策Improvements

  • アップグレードされた機械学習ライブラリUpgraded machine learning libraries

    • 1.12.0 以降から1.13.1 にアップグレードされた更新Tensorflow upgraded from 1.12.0 to 1.13.1
    • PyTorch を0.4.1 から1.1.0 にアップグレードしましたPyTorch upgraded from 0.4.1 to 1.1.0
    • scikit-learn-0.19.1 から0.20.3 にアップグレードする方法について説明します。scikit-learn upgraded from 0.19.1 to 0.20.3
  • HorovodRunnerの単一ノード操作Single-node operation for HorovodRunner

    HorovodRunner を有効にすると、ドライバーノードでのみ実行されます。Enabled HorovodRunner to run on only the driver node. 以前は、HorovodRunner を使用するには、ドライバーと少なくとも1つのワーカーノードを実行する必要がありました。Previously, to use HorovodRunner you would have to run a driver and at least one worker node. この変更により、1つのノード (つまりマルチ GPU ノード) 内にトレーニングを配布できるようになり、コンピューティングリソースをより効率的に使用できるようになりました。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.

非推奨Deprecation

Hyperoptライブラリでは、hyperopt.SparkTrials の次のプロパティは非推奨となりました。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

プロパティを次の関数に置き換えます。and replaced the properties with the following functions:

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

システム環境System environment

Databricks Runtime 5.5 LTS ML のシステム環境は、次のように Databricks Runtime 5.5 と異なります。The system environment in Databricks Runtime 5.5 LTS ML differs from Databricks Runtime 5.5 as follows:

  • Python: python 3 クラスターの場合は 3.6.5、python 2 クラスターの場合は2.7.15。Python: 3.6.5 for Python 3 clusters and 2.7.15 for Python 2 clusters.
  • DBUtils: DATABRICKS RUNTIME 5.5 LTS ML にライブラリユーティリティが含まれていません。DBUtils: Databricks Runtime 5.5 LTS ML does not contain Library utilities.
  • GPU クラスターの場合、次の NVIDIA GPU ライブラリを使用します。For GPU clusters, the following NVIDIA GPU libraries:
    • Tesla ドライバー418.40Tesla driver 418.40
    • CUDA 10.0CUDA 10.0
    • CUDNN 7.6.0CUDNN 7.6.0

ライブラリ Libraries

以下のセクションでは、Databricks Runtime 5.5 に含まれているものとは異なる Databricks Runtime 5.5 LTS ML に含まれるライブラリについて説明します。The following sections list the libraries included in Databricks Runtime 5.5 LTS ML that differ from those included in Databricks Runtime 5.5.

最上位層ライブラリTop-tier libraries

Databricks Runtime 5.5 LTS ML には、次の最上位層ライブラリが含まれています。Databricks Runtime 5.5 LTS ML includes the following top-tier libraries:

Python ライブラリPython libraries

Databricks Runtime 5.5 LTS ML では、Python パッケージ管理に Conda を使用します。Databricks Runtime 5.5 LTS ML uses Conda for Python package management. そのため、インストールされている Python ライブラリには Databricks Runtime と比較して大きな違いがあります。As a result, there are major differences in installed Python libraries compared to Databricks Runtime. 以下のセクションでは、Python 2 または3を使用した Databricks Runtime 5.5 LTS ML クラスターの Conda 環境と、CPU または GPU 対応のマシンについて説明します。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 クラスターでの 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 クラスターでの 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 クラスターでの 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 クラスターでの 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

Python モジュールを含む Spark パッケージSpark packages containing Python modules

Spark パッケージSpark Package Python モジュールPython Module VersionVersion
graphframesgraphframes graphframesgraphframes 0.7.0-spark 2.40.7.0-db1-spark2.4
spark-ディープラーニングspark-deep-learning sparkdlsparkdl db4-spark 2.41.5.0-db4-spark2.4
すべてのフレームをtensorframes すべてのフレームをtensorframes 0.7.0-s_ 2.110.7.0-s_2.11

R ライブラリR libraries

R ライブラリは、 Databricks Runtime 5.5 の r ライブラリと同じです。The R libraries are identical to the R Libraries in Databricks Runtime 5.5.

Java とスケールのライブラリ (2.11 クラスター)Java and Scala libraries (Scala 2.11 cluster)

Databricks Runtime 5.5 の Java と LTS のライブラリに加え、Databricks Runtime 5.5 の ML には次の Jar が含まれています。In addition to Java and Scala libraries in Databricks Runtime 5.5, Databricks Runtime 5.5 LTS ML contains the following JARs:

グループ IDGroup ID 成果物 IDArtifact ID VersionVersion
databrickscom.databricks spark-ディープラーニングspark-deep-learning db4-spark 2.41.5.0-db4-spark2.4
タイプセーフな. akkacom.typesafe.akka akka-actor_ 2.11akka-actor_2.11 2.3.112.3.11
combust. mleapml.combust.mleap mleap-runtime_ 2.11mleap-databricks-runtime_2.11 0.13.00.13.0
ml (dmlc)ml.dmlc xgboost4jxgboost4j 0.900.90
ml (dmlc)ml.dmlc xgboost4j-sparkxgboost4j-spark 0.900.90
org フレームorg.graphframes graphframes_ 2.11graphframes_2.11 0.7.0-spark 2.40.7.0-db1-spark2.4
組織の "転送フロー"org.tensorflow libtensorflowlibtensorflow 1.13.11.13.1
組織の "転送フロー"org.tensorflow libtensorflow_jnilibtensorflow_jni 1.13.11.13.1
組織の "転送フロー"org.tensorflow spark-connector_ 2.11spark-tensorflow-connector_2.11 1.13.11.13.1
組織の "転送フロー"org.tensorflow tensorflowtensorflow 1.13.11.13.1
組織の場合org.tensorframes すべてのフレームをtensorframes 0.7.0-s_ 2.110.7.0-s_2.11