Databricks Runtime 5,5 LTS MLDatabricks Runtime 5.5 LTS ML

Databricks a publié cette image en juillet 2019.Databricks released this image in July 2019.

Databricks Runtime 5,5 LTS pour Machine Learning fournit un environnement prêt à l’emploi pour les Machine Learning et la science des données basée sur Databricks Runtime 5,5 LTS.Databricks Runtime 5.5 LTS for Machine Learning provides a ready-to-go environment for machine learning and data science based on Databricks Runtime 5.5 LTS. Databricks Runtime pour ML contient de nombreuses bibliothèques de Machine Learning populaires, notamment TensorFlow, PyTorch, keras et XGBoost.Databricks Runtime for ML contains many popular machine learning libraries, including TensorFlow, PyTorch, Keras, and XGBoost. Il prend également en charge la formation distribuée d’apprentissage profond à l’aide de Horovod.It also supports distributed deep learning training using Horovod.

Pour plus d’informations, y compris pour obtenir des instructions sur la création d’un cluster Databricks Runtime ML, consultez Databricks Runtime pour machine learning.For more information, including instructions for creating a Databricks Runtime ML cluster, see Databricks Runtime for Machine Learning.

Nouvelles fonctionnalitésNew features

Databricks Runtime 5,5 LTS ML est basé sur Databricks Runtime 5,5 LTS.Databricks Runtime 5.5 LTS ML is built on top of Databricks Runtime 5.5 LTS. Pour plus d’informations sur les nouveautés de Databricks Runtime 5,5 LTS, consultez les notes de publication Databricks Runtime 5,5 LTS .For information on what’s new in Databricks Runtime 5.5 LTS, see the Databricks Runtime 5.5 LTS release notes.

Outre les mises à jour de bibliothèque, DATABRICKS Runtime 5,5 LTS ml introduit les nouvelles fonctionnalités suivantes :In addition to library updates, Databricks Runtime 5.5 LTS ML introduces the following new features:

  • Ajout du package Python MLflow 1,0Added the MLflow 1.0 Python package

AméliorationsImprovements

  • Bibliothèques de Machine Learning mises à niveauUpgraded machine learning libraries

    • Tensorflow mis à niveau de 1.12.0 vers 1.13.1Tensorflow upgraded from 1.12.0 to 1.13.1
    • PyTorch mis à niveau de 0.4.1 vers la 1.1.0PyTorch upgraded from 0.4.1 to 1.1.0
    • scikit-formation mise à niveau de 0.19.1 vers 0.20.3scikit-learn upgraded from 0.19.1 to 0.20.3
  • Opération à nœud unique pour HorovodRunnerSingle-node operation for HorovodRunner

    Activation de HorovodRunner pour qu’il s’exécute uniquement sur le nœud du pilote.Enabled HorovodRunner to run on only the driver node. Auparavant, pour utiliser HorovodRunner, vous devez exécuter un pilote et au moins un nœud Worker.Previously, to use HorovodRunner you would have to run a driver and at least one worker node. Avec cette modification, vous pouvez désormais distribuer la formation au sein d’un nœud unique (autrement dit, un nœud à plusieurs GPU) et ainsi utiliser les ressources de calcul plus efficacement.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.

DépréciationDeprecation

Dans la bibliothèque hyperopt , nous avons déconseillé les propriétés suivantes de hyperopt.SparkTrials :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

et remplacé les propriétés par les fonctions suivantes :and replaced the properties with the following functions:

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

Environnement du systèmeSystem environment

L’environnement système de Databricks Runtime 5,5 LTS ML diffère de Databricks Runtime 5,5, comme suit :The system environment in Databricks Runtime 5.5 LTS ML differs from Databricks Runtime 5.5 as follows:

  • Python: 3.6.5 pour les clusters python 3 et 2.7.15 pour les clusters Python 2.Python: 3.6.5 for Python 3 clusters and 2.7.15 for Python 2 clusters.
  • DBUtils: ne contient pas d' utilitaires de bibliothèque.DBUtils: Does not contain Library utilities.
  • Pour les clusters GPU, les bibliothèques GPU NVIDIA suivantes :For GPU clusters, the following NVIDIA GPU libraries:
    • CUDA 10,0CUDA 10.0
    • CUDNN 7.6.0CUDNN 7.6.0

Bibliothèques Libraries

Les sections suivantes répertorient les bibliothèques incluses dans Databricks Runtime 5,5 LTS ML qui diffèrent de celles incluses dans Databricks Runtime 5,5.The following sections list the libraries included in Databricks Runtime 5.5 LTS ML that differ from those included in Databricks Runtime 5.5.

Bibliothèques de niveau supérieurTop-tier libraries

Databricks Runtime 5,5 LTS ML comprend les bibliothèquesde niveau supérieur suivantes :Databricks Runtime 5.5 LTS ML includes the following top-tier libraries:

Bibliothèques PythonPython libraries

Databricks Runtime 5,5 LTS ML utilise Conda pour la gestion des packages Python.Databricks Runtime 5.5 LTS ML uses Conda for Python package management. Par conséquent, il existe des différences majeures dans les bibliothèques python installées par rapport à Databricks Runtime.As a result, there are major differences in installed Python libraries compared to Databricks Runtime. Les sections suivantes décrivent les environnements Conda pour les clusters Databricks Runtime 5,5 LTS ML à l’aide de Python 2 ou 3, ainsi que des machines virtuelles ou GPU.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.

Python 3 sur les clusters UCPython 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

Python 3 sur des clusters GPUPython 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

Python 2 sur les clusters UCPython 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

Python 2 sur les clusters GPUPython 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

Packages Spark contenant des modules pythonSpark packages containing Python modules

Package SparkSpark Package Module pythonPython Module VersionVersion
graphframesgraphframes graphframesgraphframes 0.7.0-DB1-Spark 2.40.7.0-db1-spark2.4
Spark-apprentissage profondspark-deep-learning sparkdlsparkdl 1.5.0-est renommé db4-Spark 2.41.5.0-db4-spark2.4
tensorframestensorframes tensorframestensorframes 0.7.0-s_2.110.7.0-s_2.11

Bibliothèques RR libraries

Les bibliothèques R sont identiques aux bibliothèques r dans Databricks Runtime 5,5.The R libraries are identical to the R Libraries in Databricks Runtime 5.5.

Bibliothèques Java et scalaire (cluster Scala 2,11)Java and Scala libraries (Scala 2.11 cluster)

En plus des bibliothèques Java et Scala dans Databricks Runtime 5,5, Databricks Runtime 5,5 LTS ML contient les fichiers JAR suivants :In addition to Java and Scala libraries in Databricks Runtime 5.5, Databricks Runtime 5.5 LTS ML contains the following JARs:

ID de groupeGroup ID ID d’artefactArtifact ID VersionVersion
com. databrickscom.databricks Spark-apprentissage profondspark-deep-learning 1.5.0-est renommé db4-Spark 2.41.5.0-db4-spark2.4
com. sécurisé. Akka Streamscom.typesafe.akka Akka Streams-actor_2.11akka-actor_2.11 2.3.112.3.11
ml. chambre d’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-Spark 2.40.7.0-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