Databricks Runtime 5.5 LTS para ML (EoS)
Observação
O suporte para esta versão do Databricks Runtime foi encerrado. Para obter a data de fim do suporte, consulte o Histórico de fim do suporte. Para todas as versões compatíveis do Databricks Runtime, consulte Versões e compatibilidade de notas sobre a versão do Databricks Runtime.
O Databricks lançou essa versão em julho de 2019. O suporte foi encerrado em 27 de julho de 2021. Suporte estendido do Databricks Runtime 5.5 ML (EoS) estende o suporte do 5.5 ML até dezembro de 2021. Ele usa o Ubuntu 18.04.5 LTS em vez da distribuição preterida do Ubuntu 16.04.6 LTS usada no Databricks Runtime 5.5 ML LTS original. O suporte ao Ubuntu 16.04.6 LTS foi encerrado em 1º de abril de 2021.
O Databricks Runtime 5.5 LTS para Machine Learning fornece um ambiente pronto para uso em aprendizado de máquina e ciência de dados com base no Databricks Runtime 5.5 LTS (EoS). O Databricks Runtime ML contém muitas bibliotecas de aprendizado de máquina populares, inclusive TensorFlow, PyTorch, Keras e XGBoost. Ele também dá suporte ao treinamento de aprendizado profundo distribuído com o uso do Horovod.
Para obter mais informações, incluindo instruções para criar um cluster de ML do Databricks Runtime, confira IA e Machine Learning no Databricks.
Novos recursos
O Databricks Runtime 5.5 LTS para Machine Learning foi criado com base no Databricks Runtime 5.5 LTS. Para obter informações sobre as novidades do Databricks Runtime 5.5 LTS, confira as notas sobre a versão do Databricks Runtime 5.5 LTS (EoS).
Além das atualizações de bibliotecas, o Databricks Runtime 5.5 LTS para Machine Learning apresenta os seguintes novos recursos:
- Adicionado o pacote Python do MLflow 1.0
Aprimoramentos
Atualização das bibliotecas de aprendizado de máquina
- TensorFlow atualizado da 1.12.0 para a 1.13.1
- PyTorch atualizado de 0.4.1 para 1.1.0
- scikit-learn atualizado de 0.19.1 para 0.20.3
Operação de nó único para HorovodRunner
Habilitar o HorovodRunner para ser executado apenas no nó do driver. Anteriormente, para usar o HorovodRunner, você teria que executar um driver e pelo menos um nó de trabalho. Com essa alteração, agora você pode distribuir o treinamento em um único nó (ou seja, um nó de várias GPU) e, portanto, usar recursos de computação com mais eficiência.
Reprovação
Na biblioteca hyperopt, as seguintes propriedades de hyperopt.SparkTrials
foram removidas:
SparkTrials.successful_trials_count
SparkTrials.failed_trials_count
SparkTrials.cancelled_trials_count
SparkTrials.total_trials_count
e substituíram as propriedades com as seguintes funções:
SparkTrials.count_successful_trials()
SparkTrials.count_failed_trials()
SparkTrials.count_cancelled_trials()
SparkTrials.count_total_trials()
Ambiente do sistema
O ambiente do sistema no Databricks Runtime 5.5 LTS para Machine Learning difere do Databricks Runtime 5.5 nestes pontos:
- Python: 3.6.5 para os clusters do Python 3 e 2.7.15 para os clusters do Python 2.
- DBUtils: Não contém Utilitário de biblioteca (dbutils.library) (herdado).
- Para clusters de GPU, as seguintes bibliotecas de GPU NVIDIA:
- CUDA 10.0
- CUDNN 7.6.0
Bibliotecas
As seções a seguir listam as bibliotecas incluídas no Databricks Runtime 5.5 LTS for Machine Learning que diferem daquelas incluídas no Databricks Runtime 5.5.
Bibliotecas de camada superior
O Databricks Runtime 5.5 LTS for Machine Learning inclui as seguintes bibliotecas de camada superior:
Bibliotecas do Python
O Databricks Runtime 5.5 LTS para Machine Learning usa o Conda para gerenciamento de pacotes do Python. Como resultado, há grandes diferenças nas bibliotecas do Python pré-instaladas em comparação com o Databricks Runtime. As seções a seguir descrevem os ambientes do Conda para Databricks Runtime 5.5 LTS para clusters Machine Learning usando Python 2 ou 3 e máquinas habilitadas para CPU ou GPU.
Python 3 em clusters de CPU
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 em clusters de GPU
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 em clusters de CPU
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 em clusters de GPU
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
Pacotes do Spark que contêm módulos do Python
Pacote do Spark | Módulo do Python | Versão |
---|---|---|
graphframes | graphframes | 0.7.0-db1-spark2.4 |
spark-deep-learning | sparkdl | 1.5.0-db4-spark2.4 |
tensorframes | tensorframes | 0.7.0-s_2.11 |
Bibliotecas do R
As bibliotecas do R são idênticas às Bibliotecas do R no Databricks Runtime 5.5.
Bibliotecas do Java e do Scala (cluster do Scala 2.11)
Além das bibliotecas do Java e do Scala no Databricks Runtime 5.5, o Databricks Runtime 5.5 LTS para Machine Learning contém os seguintes JARs:
ID do Grupo | Artifact ID | Versão |
---|---|---|
com.databricks | spark-deep-learning | 1.5.0-db4-spark2.4 |
com.typesafe.akka | akka-actor_2.11 | 2.3.11 |
ml.combust.mleap | mleap-databricks-runtime_2.11 | 0.13.0 |
ml.dmlc | xgboost4j | 0,90 |
ml.dmlc | xgboost4j-spark | 0,90 |
org.graphframes | graphframes_2.11 | 0.7.0-db1-spark2.4 |
org.tensorflow | libtensorflow | 1.13.1 |
org.tensorflow | libtensorflow_jni | 1.13.1 |
org.tensorflow | spark-tensorflow-connector_2.11 | 1.13.1 |
org.tensorflow | tensorflow | 1.13.1 |
org.tensorframes | tensorframes | 0.7.0-s_2.11 |