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Databricks Runtime 7.3 para aprendizado de máquina (EoS) LTS

nota

O suporte para essa versão do Databricks Runtime foi encerrado. Para saber a data do fim do suporte, consulte Histórico do fim do suporte. Para conhecer todas as versões compatíveis do site Databricks Runtime, consulte Databricks Runtime notas sobre as versões e a compatibilidade.

A Databricks lançou essa versão em setembro de 2020. Ele foi declarado Long Term Support (LTS) em outubro de 2020.

O Databricks Runtime 7.3 LTS for Machine Learning oferece um ambiente pronto para uso para aprendizado de máquina e ciência de dados com base no Databricks Runtime 7.3 LTS (EoS). Databricks Runtime ML Contém muitas bibliotecas populares de aprendizado de máquina, incluindo TensorFlow, PyTorch, e XGBoost. Ele também oferece suporte ao treinamento de aprendizagem profunda distribuída usando o Horovod.

Para obter mais informações, incluindo instruções para criar um cluster Databricks Runtime ML , consulte AI e aprendizado de máquina em Databricks.

Para obter ajuda com a migração do Databricks Runtime 6.x, consulte o guia de migração do Databricks Runtime 7.x (EoS).

Novo recurso e grandes mudanças

O Databricks Runtime 7.3 LTS for Machine Learning foi desenvolvido com base no Databricks Runtime 7.3 LTS. Para obter informações sobre as novidades do Databricks Runtime 7.3 LTS, incluindo Apache Spark MLlib e SparkR, , consulte as notas sobre a versão Databricks Runtime 7.3 LTS (EoS).

Principais mudanças no ambiente do Databricks Runtime ML Python

Conda ativação no trabalhador

Anteriormente, quando o senhor atualizava o ambiente do Notebook usando %conda, o novo ambiente não era ativado nos processos do worker Python . Isso causava problemas se uma função PySpark UDF chamasse uma função de terceiros que usasse um recurso instalado no ambiente Conda. Essa limitação não existe mais.

O senhor também deve analisar as principais alterações no ambiente Python do Databricks Runtime no Databricks Runtime 7.3 LTS (EoS). Para obter uma lista completa do pacote Python instalado e suas versões, consulte Python biblioteca.

Python pacote atualizado

  • mlflow 1.9.1 - > 1.11.0
  • tensorflow 2.2.0 - > 2.3.0
  • TensorBoard 2.2.2 -> 2.3.0
  • PyTorch 1.5.1 -> 1.6.0
  • torchvision 0.6.1 - > 0.7.0
  • petastorm 0.9.2 - > 0.9.5

Ambiente do sistema

O ambiente do sistema no Databricks Runtime 7.3 LTS para Machine Learning difere do Databricks Runtime 7.3 LTS da seguinte forma:

biblioteca

As seções a seguir listam as bibliotecas incluídas em Databricks Runtime 7.3 LTS para Machine Learning que diferem daquelas incluídas em Databricks Runtime 7.3 LTS.

Nesta secção:

Biblioteca de primeira linha

Databricks Runtime 7.3 O site LTS for Machine Learning inclui as seguintes bibliotecas de primeira linha:

Python biblioteca

Databricks Runtime 7.3 O LTS for Machine Learning usa o Conda para o gerenciamento do pacote Python e inclui muitos pacotes populares ML.

Além do pacote especificado nos ambientes Conda nas seções a seguir, o Databricks Runtime 7.3 LTS for Machine Learning também instala o seguinte pacote:

  • Hyperopt 0.2.4.db2
  • sparkdl 2.1.0-db1

Python biblioteca sobre clustering de CPU

YAML
name: databricks-ml
channels:
- pytorch
- defaults
dependencies:
- _libgcc_mutex=0.1=main
- absl-py=0.9.0=py37_0
- asn1crypto=1.3.0=py37_1
- astor=0.8.0=py37_0
- backcall=0.1.0=py37_0
- backports=1.0=py_2
- bcrypt=3.2.0=py37h7b6447c_0
- blas=1.0=mkl
- blinker=1.4=py37_0
- boto3=1.12.0=py_0
- botocore=1.15.0=py_0
- c-ares=1.15.0=h7b6447c_1001
- ca-certificates=2020.7.22=0
- cachetools=4.1.1=py_0
- certifi=2020.6.20=pyhd3eb1b0_3 # (updated from py37_0 in June 15, 2021 maintenance update)
- cffi=1.14.0=py37he30daa8_1 # (updated from py37h2e261b9_0 in June 15, 2021 maintenance update)
- chardet=3.0.4=py37_1003
- click=7.0=py37_0
- cloudpickle=1.3.0=py_0
- configparser=3.7.4=py37_0
- cpuonly=1.0=0
- cryptography=2.8=py37h1ba5d50_0
- cycler=0.10.0=py37_0
- cython=0.29.15=py37he6710b0_0
- decorator=4.4.1=py_0
- dill=0.3.1.1=py37_1
- docutils=0.15.2=py37_0
- entrypoints=0.3=py37_0
- flask=1.1.1=py_1
- freetype=2.9.1=h8a8886c_1
- future=0.18.2=py37_1
- gast=0.3.3=py_0
- gitdb=4.0.5=py_0
- gitpython=3.1.0=py_0
- google-auth=1.11.2=py_0
- google-auth-oauthlib=0.4.1=py_2
- google-pasta=0.2.0=py_0
- grpcio=1.27.2=py37hf8bcb03_0
- gunicorn=20.0.4=py37_0
- h5py=2.10.0=py37h7918eee_0
- hdf5=1.10.4=hb1b8bf9_0
- icu=58.2=he6710b0_3
- idna=2.8=py37_0
- intel-openmp=2020.0=166
- ipykernel=5.1.4=py37h39e3cac_0
- ipython=7.12.0=py37h5ca1d4c_0
- ipython_genutils=0.2.0=py37_0
- isodate=0.6.0=py_1
- itsdangerous=1.1.0=py37_0
- jedi=0.14.1=py37_0
- jinja2=2.11.1=py_0
- jmespath=0.10.0=py_0
- joblib=0.14.1=py_0
- jpeg=9b=h024ee3a_2
- jupyter_client=5.3.4=py37_0
- jupyter_core=4.6.1=py37_0
- kiwisolver=1.1.0=py37he6710b0_0
- krb5=1.17.1=h173b8e3_0 # (updated from 1.16.4 in June 15, 2021 maintenance update)
- ld_impl_linux-64=2.33.1=h53a641e_7
- libedit=3.1.20181209=hc058e9b_0
- libffi=3.3=he6710b0_2 # (updated from 3.2.1 in June 15, 2021 maintenance update)
- libgcc-ng=9.1.0=hdf63c60_0
- libgfortran-ng=7.3.0=hdf63c60_0
- libpng=1.6.37=hbc83047_0
- libpq=12.2=h20c2e04_0 # (updated from 11.2 in June 15, 2021 maintenance update)
- libprotobuf=3.11.4=hd408876_0
- libsodium=1.0.16=h1bed415_0
- libstdcxx-ng=9.1.0=hdf63c60_0
- libtiff=4.1.0=h2733197_0
- lightgbm=2.3.0=py37he6710b0_0
- lz4-c=1.8.1.2=h14c3975_0
- mako=1.1.2=py_0
- markdown=3.1.1=py37_0
- markupsafe=1.1.1=py37h14c3975_1
- matplotlib-base=3.1.3=py37hef1b27d_0
- mkl=2020.0=166
- mkl-service=2.3.0=py37he904b0f_0
- mkl_fft=1.0.15=py37ha843d7b_0
- mkl_random=1.1.0=py37hd6b4f25_0
- ncurses=6.2=he6710b0_1
- networkx=2.4=py_1
- ninja=1.10.0=py37hfd86e86_0
- nltk=3.4.5=py37_0
- numpy=1.18.1=py37h4f9e942_0
- numpy-base=1.18.1=py37hde5b4d6_1
- oauthlib=3.1.0=py_0
- olefile=0.46=py37_0
- openssl=1.1.1k=h27cfd23_0 # (updated from 1.1.1g in June 15, 2021 maintenance update)
- packaging=20.1=py_0
- pandas=1.0.1=py37h0573a6f_0
- paramiko=2.7.1=py_0
- parso=0.5.2=py_0
- patsy=0.5.1=py37_0
- pexpect=4.8.0=py37_1
- pickleshare=0.7.5=py37_1001
- pillow=7.0.0=py37hb39fc2d_0
- pip=20.0.2=py37_3
- plotly=4.9.0=py_0
- prompt_toolkit=3.0.3=py_0
- protobuf=3.11.4=py37he6710b0_0
- psutil=5.6.7=py37h7b6447c_0
- psycopg2=2.8.6=py37h3c74f83_1 # (updated from 2.8.4 in June 15, 2021 maintenance update)
- ptyprocess=0.6.0=py37_0
- pyasn1=0.4.8=py_0
- pyasn1-modules=0.2.7=py_0
- pycparser=2.19=py37_0
- pygments=2.5.2=py_0
- pyjwt=1.7.1=py37_0
- pynacl=1.3.0=py37h7b6447c_0
- pyodbc=4.0.30=py37he6710b0_0
- pyopenssl=19.1.0=py_1
- pyparsing=2.4.6=py_0
- pysocks=1.7.1=py37_1
- python=3.7.10=hdb3f193_0 # (updated from 3.7.6 in June 15, 2021 maintenance update)
- python-dateutil=2.8.1=py_0
- python-editor=1.0.4=py_0
- pytorch=1.6.0=py3.7_cpu_0
- pytz=2019.3=py_0
- pyzmq=18.1.1=py37he6710b0_0
- readline=8.1=h27cfd23_0 # (updated from 7.0 in June 15, 2021 maintenance update)
- requests=2.22.0=py37_1
- requests-oauthlib=1.3.0=py_0
- retrying=1.3.3=py37_2
- rsa=4.0=py_0
- s3transfer=0.3.3=py37_1
- scikit-learn=0.22.1=py37hd81dba3_0
- scipy=1.4.1=py37h0b6359f_0
- setuptools=45.2.0=py37_0
- simplejson=3.17.0=py37h7b6447c_0
- six=1.14.0=py37_0
- smmap=3.0.4=py_0
- sqlite=3.35.4=hdfb4753_0 # (updated from 3.31.1 in June 15, 2021 maintenance update)
- sqlparse=0.3.0=py_0
- statsmodels=0.11.0=py37h7b6447c_0
- tabulate=0.8.3=py37_0
- tk=8.6.10=hbc83047_0 # (updated from 8.6.8 in June 15, 2021 maintenance update)
- torchvision=0.7.0=py37_cpu
- tornado=6.0.3=py37h7b6447c_3
- tqdm=4.42.1=py_0
- traitlets=4.3.3=py37_0
- unixodbc=2.3.7=h14c3975_0
- urllib3=1.25.8=py37_0
- wcwidth=0.1.8=py_0
- websocket-client=0.56.0=py37_0
- werkzeug=1.0.0=py_0
- wheel=0.34.2=py37_0
- wrapt=1.11.2=py37h7b6447c_0
- xz=5.2.5=h7b6447c_0 # (updated from 5.2.4 in June 15, 2021 maintenance update)
- zeromq=4.3.1=he6710b0_3
- zlib=1.2.11=h7b6447c_3
- zstd=1.3.7=h0b5b093_0
- pip:
- astunparse==1.6.3
- azure-core==1.8.0
- azure-storage-blob==12.4.0
- databricks-cli==0.11.0
- diskcache==5.0.2
- docker==4.3.1
- gorilla==0.3.0
- horovod==0.19.5
- joblibspark==0.2.0
- keras-preprocessing==1.1.2
- koalas==1.2.0
- mleap==0.16.1
- mlflow==1.11.0
- msrest==0.6.18
- opt-einsum==3.3.0
- petastorm==0.9.5
- pyarrow==1.0.1
- pyyaml==5.3.1
- querystring-parser==1.2.4
- seaborn==0.10.0
- spark-tensorflow-distributor==0.1.0
- tensorboard==2.3.0
- tensorboard-plugin-wit==1.7.0
- tensorflow-cpu==2.3.0
- tensorflow-estimator==2.3.0
- termcolor==1.1.0
- xgboost==1.1.1
prefix: /databricks/conda/envs/databricks-ml

Python biblioteca sobre clustering de GPU

YAML
name: databricks-ml-gpu
channels:
- pytorch
- defaults
dependencies:
- _libgcc_mutex=0.1=main
- absl-py=0.9.0=py37_0
- asn1crypto=1.3.0=py37_1
- astor=0.8.0=py37_0
- backcall=0.1.0=py37_0
- backports=1.0=py_2
- bcrypt=3.2.0=py37h7b6447c_0
- blas=1.0=mkl
- blinker=1.4=py37_0
- boto3=1.12.0=py_0
- botocore=1.15.0=py_0
- c-ares=1.15.0=h7b6447c_1001
- ca-certificates=2020.7.22=0
- cachetools=4.1.1=py_0
- certifi=2020.6.20=pyhd3eb1b0_3 # (updated from py37_0 in June 15, 2021 maintenance update)
- cffi=1.14.0=py37he30daa8_1 # (updated from py37h2e261b9_0 in June 15, 2021 maintenance update)
- chardet=3.0.4=py37_1003
- click=7.0=py37_0
- cloudpickle=1.3.0=py_0
- configparser=3.7.4=py37_0
- cryptography=2.8=py37h1ba5d50_0
- cudatoolkit=10.1.243=h6bb024c_0
- cycler=0.10.0=py37_0
- cython=0.29.15=py37he6710b0_0
- decorator=4.4.1=py_0
- dill=0.3.1.1=py37_1
- docutils=0.15.2=py37_0
- entrypoints=0.3=py37_0
- flask=1.1.1=py_1
- freetype=2.9.1=h8a8886c_1
- future=0.18.2=py37_1
- gast=0.3.3=py_0
- gitdb=4.0.5=py_0
- gitpython=3.1.0=py_0
- google-auth=1.11.2=py_0
- google-auth-oauthlib=0.4.1=py_2
- google-pasta=0.2.0=py_0
- grpcio=1.27.2=py37hf8bcb03_0
- gunicorn=20.0.4=py37_0
- h5py=2.10.0=py37h7918eee_0
- hdf5=1.10.4=hb1b8bf9_0
- icu=58.2=he6710b0_3
- idna=2.8=py37_0
- intel-openmp=2020.0=166
- ipykernel=5.1.4=py37h39e3cac_0
- ipython=7.12.0=py37h5ca1d4c_0
- ipython_genutils=0.2.0=py37_0
- isodate=0.6.0=py_1
- itsdangerous=1.1.0=py37_0
- jedi=0.14.1=py37_0
- jinja2=2.11.1=py_0
- jmespath=0.10.0=py_0
- joblib=0.14.1=py_0
- jpeg=9b=h024ee3a_2
- jupyter_client=5.3.4=py37_0
- jupyter_core=4.6.1=py37_0
- kiwisolver=1.1.0=py37he6710b0_0
- krb5=1.16.4=h173b8e3_0 # (updated from 1.16.4 in June 15, 2021 maintenance update)
- ld_impl_linux-64=2.33.1=h53a641e_7
- libedit=3.1.20181209=hc058e9b_0
- libffi=3.3=he6710b0_2 # (updated from 3.2.1 in June 15, 2021 maintenance update)
- libgcc-ng=9.1.0=hdf63c60_0
- libgfortran-ng=7.3.0=hdf63c60_0
- libpng=1.6.37=hbc83047_0
- libpq=12.2=h20c2e04_0 # (updated from 11.2 in June 15, 2021 maintenance update)
- libprotobuf=3.11.4=hd408876_0
- libsodium=1.0.16=h1bed415_0
- libstdcxx-ng=9.1.0=hdf63c60_0
- libtiff=4.1.0=h2733197_0
- lightgbm=2.3.0=py37he6710b0_0
- lz4-c=1.8.1.2=h14c3975_0
- mako=1.1.2=py_0
- markdown=3.1.1=py37_0
- markupsafe=1.1.1=py37h14c3975_1
- matplotlib-base=3.1.3=py37hef1b27d_0
- mkl=2020.0=166
- mkl-service=2.3.0=py37he904b0f_0
- mkl_fft=1.0.15=py37ha843d7b_0
- mkl_random=1.1.0=py37hd6b4f25_0
- ncurses=6.2=he6710b0_1
- networkx=2.4=py_1
- ninja=1.10.0=py37hfd86e86_0
- nltk=3.4.5=py37_0
- numpy=1.18.1=py37h4f9e942_0
- numpy-base=1.18.1=py37hde5b4d6_1
- oauthlib=3.1.0=py_0
- olefile=0.46=py37_0
- openssl=1.1.1k=h27cfd23_0 # (updated from 1.1.1g in June 15, 2021 maintenance update)
- packaging=20.1=py_0
- pandas=1.0.1=py37h0573a6f_0
- paramiko=2.7.1=py_0
- parso=0.5.2=py_0
- patsy=0.5.1=py37_0
- pexpect=4.8.0=py37_1
- pickleshare=0.7.5=py37_1001
- pillow=7.0.0=py37hb39fc2d_0
- pip=20.0.2=py37_3
- plotly=4.9.0=py_0
- prompt_toolkit=3.0.3=py_0
- protobuf=3.11.4=py37he6710b0_0
- psutil=5.6.7=py37h7b6447c_0
- psycopg2=2.8.6=py37h3c74f83_1 # (updated from 2.8.4 in June 15, 2021 maintenance update)
- ptyprocess=0.6.0=py37_0
- pyasn1=0.4.8=py_0
- pyasn1-modules=0.2.7=py_0
- pycparser=2.19=py37_0
- pygments=2.5.2=py_0
- pyjwt=1.7.1=py37_0
- pynacl=1.3.0=py37h7b6447c_0
- pyodbc=4.0.30=py37he6710b0_0
- pyopenssl=19.1.0=py_1
- pyparsing=2.4.6=py_0
- pysocks=1.7.1=py37_1
- python=3.7.10=hdb3f193_0 # (updated from 3.7.6 in June 15, 2021 maintenance update)
- python-dateutil=2.8.1=py_0
- python-editor=1.0.4=py_0
- pytorch=1.6.0=py3.7_cuda10.1.243_cudnn7.6.3_0
- pytz=2019.3=py_0
- pyzmq=18.1.1=py37he6710b0_0
- readline=8.1=h27cfd23_0 # (updated from 7.0 in June 15, 2021 maintenance update)
- requests=2.22.0=py37_1
- requests-oauthlib=1.3.0=py_0
- retrying=1.3.3=py37_2
- rsa=4.0=py_0
- s3transfer=0.3.3=py37_1
- scikit-learn=0.22.1=py37hd81dba3_0
- scipy=1.4.1=py37h0b6359f_0
- setuptools=45.2.0=py37_0
- simplejson=3.17.0=py37h7b6447c_0
- six=1.14.0=py37_0
- smmap=3.0.4=py_0
- sqlite=3.35.4=hdfb4753_0 # (updated from 3.31.1 in June 15, 2021 maintenance update)
- sqlparse=0.3.0=py_0
- statsmodels=0.11.0=py37h7b6447c_0
- tabulate=0.8.3=py37_0
- tk=8.6.10=hbc83047_0 # (updated from 8.6.8 in June 15, 2021 maintenance update)
- torchvision=0.7.0=py37_cu101
- tornado=6.0.3=py37h7b6447c_3
- tqdm=4.42.1=py_0
- traitlets=4.3.3=py37_0
- unixodbc=2.3.7=h14c3975_0
- urllib3=1.25.8=py37_0
- wcwidth=0.1.8=py_0
- websocket-client=0.56.0=py37_0
- werkzeug=1.0.0=py_0
- wheel=0.34.2=py37_0
- wrapt=1.11.2=py37h7b6447c_0
- xz=5.2.5=h7b6447c_0 # (updated from 5.2.4 in June 15, 2021 maintenance update)
- zeromq=4.3.1=he6710b0_3
- zlib=1.2.11=h7b6447c_3
- zstd=1.3.7=h0b5b093_0
- pip:
- astunparse==1.6.3
- azure-core==1.8.0
- azure-storage-blob==12.4.0
- databricks-cli==0.11.0
- diskcache==5.0.2
- docker==4.3.1
- gorilla==0.3.0
- horovod==0.19.5
- joblibspark==0.2.0
- keras-preprocessing==1.1.2
- koalas==1.2.0
- mleap==0.16.1
- mlflow==1.11.0
- msrest==0.6.18
- opt-einsum==3.3.0
- petastorm==0.9.5
- pyarrow==1.0.1
- pyyaml==5.3.1
- querystring-parser==1.2.4
- seaborn==0.10.0
- spark-tensorflow-distributor==0.1.0
- tensorboard==2.3.0
- tensorboard-plugin-wit==1.7.0
- tensorflow==2.3.0
- tensorflow-estimator==2.3.0
- termcolor==1.1.0
- xgboost==1.1.1
prefix: /databricks/conda/envs/databricks-ml-gpu

Spark pacote contendo os módulos Python

Spark pacote

Módulo Python

Versão

graphframes

graphframes

0.8.0-db2-spark3.0

R biblioteca

A biblioteca R é idêntica à biblioteca R em Databricks Runtime 7.3 LTS.

Java e biblioteca ( 2.12 clustering) Scala Scala

Além de Java e Scala biblioteca em Databricks Runtime 7.3 LTS, Databricks Runtime 7.3 LTS para Machine Learning contém os seguintes JARs:

ID do grupo

ID do artefato

Versão

com.typesafe.akka

também conhecido como actor_2.12

2.5.23

ml.combust.mleap

mleap-databricks-runtime_2.12

0,17.3-4882dc3

ml.dmlc

xgboost4j-spark_2.12

1.0.0

ml.dmlc

xgboost4j_2,12

1.0.0

org.mlflow

cliente mlflow

1.11.0

org.Scala-lang.modules

Scala-java8-compat_2.12

0,8.0

org.tensorflow

spark-tensorflow-connector_2.12

1,15.0