Databricks Runtime 12.1 para Machine Learning (sin soporte técnico)
Databricks Runtime 12.1 para Machine Learning proporciona un entorno listo para usar de aprendizaje automático y ciencia de datos basado en Databricks Runtime 12.1 (sin soporte técnico). Databricks Runtime ML contiene muchas bibliotecas populares de aprendizaje automático, incluidas TensorFlow, PyTorch y XGBoost. Databricks Runtime ML incluye AutoML, una herramienta para entrenar automáticamente canalizaciones de aprendizaje automático. Databricks Runtime ML también admite el entrenamiento de aprendizaje profundo distribuido mediante Horovod.
Para más información, incluidas las instrucciones para crear un clúster de Databricks Runtime ML, consulte IA y Machine Learning en Databricks.
Nuevas características y mejoras
Databricks Runtime 12.1 ML se basa en Databricks Runtime 12.1. Para más información sobre las novedades de Databricks Runtime 12.1, incluyendo Apache Spark MLlib y SparkR, consulte las notas de la versión de Databricks Runtime 12.1 (sin soporte técnico).
Databricks AutoML
A partir de Databricks Runtime 12.1 ML, la API de Python en AutoML permite especificar un nombre personalizado para el experimento generado por AutoML. Utilice el parámetro experiment_name.
Para más información sobre Databricks AutoML, consulte ¿Qué es AutoML?.
Entorno del sistema
El entorno del sistema de Databricks Runtime 12.1 ML se diferencia del de Databricks Runtime 12.1 en los siguientes aspectos:
- DBUtils: Databricks Runtime ML no incluye la utilidad de biblioteca de (dbutils.library) (heredada).
Use comandos
%pipen su lugar. Consulte Bibliotecas de Python cuyo ámbito es Notebook. - En los clústeres de GPU, Databricks Runtime ML incluye las siguientes bibliotecas de GPU de NVIDIA:
- CUDA 11.3
- cuDNN 8.0.5.39
- NCCL 2.9.9
- TensorRT 7.2.2
Databricks Runtime 12.1 ML incluye XGBoost 1.7.2, que no admite clústeres de GPU con capacidad de proceso 5.2 ni versiones anteriores.
Bibliotecas
En las siguientes secciones, se enumeran las bibliotecas que se incluyen en Databricks Runtime 12.1 ML, que difieren de las que se incluyen en Databricks Runtime 12.1.
En esta sección:
- Bibliotecas de nivel superior
- Bibliotecas de Python
- Bibliotecas de R
- Bibliotecas de Java y Scala (clúster de Scala 2.12)
Bibliotecas de nivel superior
Databricks Runtime 12.1 ML incluye las siguientes bibliotecas de nivel superior:
- GraphFrames
- Horovod y HorovodRunner
- MLflow
- PyTorch
- spark-tensorflow-connector
- TensorFlow
- TensorBoard
- Scikit-learn
Bibliotecas de Python
En Databricks Runtime 12.1 ML se usa Virtualenv para administrar los paquetes de Python. Además, incluye muchos paquetes populares de ML.
Además de los paquetes especificados en las siguientes secciones, Databricks Runtime 12.1 ML también incluye estos paquetes:
- hyperopt 0.2.7.db1
- sparkdl 2.3.0-db3
- automl 1.15.0
Para reproducir el entorno de Python de Databricks Runtime ML en el entorno virtual local de Python, descargue el archivo requirements-12.1.txt y ejecute pip install -r requirements-12.1.txt. Este comando instala todas las bibliotecas de código abierto que usa Databricks Runtime ML, pero no instala bibliotecas que desarrolla Databricks, como databricks-automl, databricks-feature-store o la bifurcación de Databricks de hyperopt.
Bibliotecas de Python en clústeres de CPU
| Biblioteca | Versión | Biblioteca | Versión | Biblioteca | Versión |
|---|---|---|---|---|---|
| absl-py | 1.0.0 | argon2-cffi | 21.3.0 | argon2-cffi-bindings | 21.2.0 |
| astor | 0.8.1 | asttokens | 2.0.5 | astunparse | 1.6.3 |
| attrs | 21.4.0 | azure-core | 1.26.1 | azure-cosmos | 4.2.0 |
| backcall | 0.2.0 | backports.entry-points-selectable | 1.2.0 | bcrypt | 3.2.0 |
| beautifulsoup4 | 4.11.1 | black | 22.3.0 | bleach | 4.1.0 |
| blis | 0.7.9 | boto3 | 1.21.32 | botocore | 1.24.32 |
| cachetools | 4.2.2 | catalogue | 2.0.8 | category-encoders | 2.5.1.post0 |
| certifi | 2021.10.8 | cffi | 1.15.0 | chardet | 4.0.0 |
| charset-normalizer | 2.0.4 | click | 8.0.4 | cloudpickle | 2.0.0 |
| cmdstanpy | 1.0.8 | confection | 0.0.3 | configparser | 5.2.0 |
| convertdate | 2.4.0 | criptografía | 3.4.8 | cycler | 0.11.0 |
| cymem | 2.0.7 | Cython | 0.29.28 | databricks-automl-runtime | 0.2.14 |
| databricks-cli | 0.17.4 | databricks-feature-store | 0.9.0 | dbl-tempo | 0.1.12 |
| dbus-python | 1.2.16 | debugpy | 1.5.1 | decorator | 5.1.1 |
| defusedxml | 0.7.1 | dill | 0.3.4 | diskcache | 5.4.0 |
| distlib | 0.3.6 | docstring-to-markdown | 0,11 | entrypoints | 0,4 |
| ephem | 4.1.4 | executing | 0.8.3 | facets-overview | 1.0.0 |
| fastjsonschema | 2.16.2 | fasttext | 0.9.2 | filelock | 3.6.0 |
| Flask | 1.1.2 | flatbuffers | 22.12.6 | fonttools | 4.25.0 |
| fsspec | 2022.2.0 | future | 0.18.2 | gast | 0.4.0 |
| gitdb | 4.0.10 | GitPython | 3.1.27 | google-auth | 1.33.0 |
| google-auth-oauthlib | 0.4.6 | google-pasta | 0.2.0 | grpcio | 1.42.0 |
| gunicorn | 20.1.0 | gviz-api | 1.10.0 | h5py | 3.6.0 |
| hijri-converter | 2.2.4 | holidays | 0.17.2 | horovod | 0.26.1 |
| htmlmin | 0.1.12 | huggingface-hub | 0.11.1 | idna | 3.3 |
| ImageHash | 4.3.1 | imbalanced-learn | 0.8.1 | importlib-metadata | 4.11.3 |
| ipykernel | 6.15.3 | ipython | 8.5.0 | ipython-genutils | 0.2.0 |
| ipywidgets | 7.7.2 | isodate | 0.6.1 | itsdangerous | 2.0.1 |
| jedi | 0.18.1 | Jinja2 | 2.11.3 | jmespath | 0.10.0 |
| joblib | 1.1.0 | joblibspark | 0.5.0 | jsonschema | 4.4.0 |
| jupyter-client | 6.1.12 | jupyter_core | 4.11.2 | jupyterlab-pygments | 0.1.2 |
| jupyterlab-widgets | 1.0.0 | keras | 2.10.0 | keras-preprocessing | 1.1.2 |
| kiwisolver | 1.3.2 | korean-lunar-calendar | 0.3.1 | langcodes | 3.3.0 |
| libclang | 14.0.6 | lightgbm | 3.3.3 | llvmlite | 0.38.0 |
| LunarCalendar | 0.0.9 | Mako | 1.2.0 | Markdown | 3.3.4 |
| MarkupSafe | 2.0.1 | matplotlib | 3.5.1 | matplotlib-inline | 0.1.2 |
| mccabe | 0.7.0 | mistune | 0.8.4 | mleap | 0.20.0 |
| mlflow-skinny | 2.1.1 | multimethod | 1.9.1 | murmurhash | 1.0.9 |
| mypy-extensions | 0.4.3 | nbclient | 0.5.13 | nbconvert | 6.4.4 |
| nbformat | 5.3.0 | nest-asyncio | 1.5.5 | networkx | 2.7.1 |
| nltk | 3.7 | nodeenv | 1.7.0 | notebook | 6.4.8 |
| numba | 0.55.1 | numpy | 1.21.5 | oauthlib | 3.2.0 |
| opt-einsum | 3.3.0 | empaquetado | 21,3 | pandas | 1.4.2 |
| pandas-profiling | 3.5.0 | pandocfilters | 1.5.0 | paramiko | 2.9.2 |
| parso | 0.8.3 | pathspec | 0.9.0 | pathy | 0.6.1 |
| patsy | 0.5.2 | petastorm | 0.12.0 | pexpect | 4.8.0 |
| phik | 0.12.3 | pickleshare | 0.7.5 | Pillow | 9.0.1 |
| pip | 21.2.4 | platformdirs | 2.6.0 | plotly | 5.6.0 |
| pluggy | 1.0.0 | pmdarima | 2.0.2 | preshed | 3.0.8 |
| prometheus-client | 0.13.1 | prompt-toolkit | 3.0.20 | prophet | 1.1.1 |
| protobuf | 3.19.4 | psutil | 5.8.0 | psycopg2 | 2.9.3 |
| ptyprocess | 0.7.0 | pure-eval | 0.2.2 | pyarrow | 7.0.0 |
| pyasn1 | 0.4.8 | pyasn1-modules | 0.2.8 | pybind11 | 2.10.1 |
| pycparser | 2.21 | pydantic | 1.10.2 | pyflakes | 2.5.0 |
| Pygments | 2.11.2 | PyGObject | 3.36.0 | PyJWT | 2.6.0 |
| PyMeeus | 0.5.12 | PyNaCl | 1.5.0 | pyodbc | 4.0.32 |
| pyparsing | 3.0.4 | pyright | 1.1.283 | pyrsistent | 0.18.0 |
| Python-dateutil | 2.8.2 | python-editor | 1.0.4 | python-lsp-jsonrpc | 1.0.0 |
| python-lsp-server | 1.6.0 | pytz | 2021.3 | PyWavelets | 1.3.0 |
| PyYAML | 6.0 | pyzmq | 22.3.0 | regex | 2022.3.15 |
| Solicitudes | 2.27.1 | requests-oauthlib | 1.3.1 | requests-unixsocket | 0.2.0 |
| rope | 0.22.0 | rsa | 4.7.2 | s3transfer | 0.5.0 |
| scikit-learn | 1.0.2 | scipy | 1.7.3 | seaborn | 0.11.2 |
| Send2Trash | 1.8.0 | setuptools | 61.2.0 | setuptools-git | 1.2 |
| shap | 0.41.0 | simplejson | 3.17.6 | six (seis) | 1.16.0 |
| segmentación | 0.0.7 | smart-open | 5.1.0 | smmap | 5.0.0 |
| soupsieve | 2.3.1 | spacy | 3.4.3 | spacy-legacy | 3.0.10 |
| spacy-loggers | 1.0.4 | spark-tensorflow-distributor | 1.0.0 | sqlparse | 0.4.2 |
| srsly | 2.4.5 | ssh-import-id | 5.10 | stack-data | 0.2.0 |
| statsmodels | 0.13.2 | tabulate | 0.8.9 | tangled-up-in-unicode | 0.2.0 |
| tenacity | 8.0.1 | tensorboard | 2.10.0 | tensorboard-data-server | 0.6.1 |
| tensorboard-plugin-profile | 2.8.0 | tensorboard-plugin-wit | 1.8.1 | tensorflow-cpu | 2.10.0 |
| tensorflow-estimator | 2.10.0 | tensorflow-io-gcs-filesystem | 0.29.0 | termcolor | 2.1.1 |
| terminado | 0.13.1 | testpath | 0.5.0 | thinc | 8.1.6 |
| threadpoolctl | 2.2.0 | tokenize-rt | 4.2.1 | tokenizers | 0.13.2 |
| tomli | 1.2.2 | torch | 1.13.0+cpu | torchvision | 0.14.0+cpu |
| tornado | 6.1 | tqdm | 4.64.0 | traitlets | 5.1.1 |
| transformers | 4.25.1 | typeguard | 2.13.3 | typer | 0.7.0 |
| typing_extensions | 4.1.1 | ujson | 5.1.0 | unattended-upgrades | 0,1 |
| urllib3 | 1.26.9 | virtualenv | 20.8.0 | visions | 0.7.5 |
| wasabi | 0.10.1 | wcwidth | 0.2.5 | webencodings | 0.5.1 |
| websocket-client | 0.58.0 | Werkzeug | 2.0.3 | whatthepatch | 1.0.3 |
| wheel | 0.37.1 | widgetsnbextension | 3.6.1 | wrapt | 1.12.1 |
| xgboost | 1.7.2 | yapf | 0.31.0 | zipp | 3.7.0 |
Bibliotecas de Python en clústeres de GPU
| Biblioteca | Versión | Biblioteca | Versión | Biblioteca | Versión |
|---|---|---|---|---|---|
| absl-py | 1.0.0 | argon2-cffi | 21.3.0 | argon2-cffi-bindings | 21.2.0 |
| astor | 0.8.1 | asttokens | 2.0.5 | astunparse | 1.6.3 |
| attrs | 21.4.0 | azure-core | 1.26.1 | azure-cosmos | 4.2.0 |
| backcall | 0.2.0 | backports.entry-points-selectable | 1.2.0 | bcrypt | 3.2.0 |
| beautifulsoup4 | 4.11.1 | black | 22.3.0 | bleach | 4.1.0 |
| blis | 0.7.9 | boto3 | 1.21.32 | botocore | 1.24.32 |
| cachetools | 4.2.2 | catalogue | 2.0.8 | category-encoders | 2.5.1.post0 |
| certifi | 2021.10.8 | cffi | 1.15.0 | chardet | 4.0.0 |
| charset-normalizer | 2.0.4 | click | 8.0.4 | cloudpickle | 2.0.0 |
| cmdstanpy | 1.0.8 | confection | 0.0.3 | configparser | 5.2.0 |
| convertdate | 2.4.0 | criptografía | 3.4.8 | cycler | 0.11.0 |
| cymem | 2.0.7 | Cython | 0.29.28 | databricks-automl-runtime | 0.2.14 |
| databricks-cli | 0.17.4 | databricks-feature-store | 0.9.0 | dbl-tempo | 0.1.12 |
| dbus-python | 1.2.16 | debugpy | 1.5.1 | decorator | 5.1.1 |
| defusedxml | 0.7.1 | dill | 0.3.4 | diskcache | 5.4.0 |
| distlib | 0.3.6 | docstring-to-markdown | 0,11 | entrypoints | 0,4 |
| ephem | 4.1.4 | executing | 0.8.3 | facets-overview | 1.0.0 |
| fastjsonschema | 2.16.2 | fasttext | 0.9.2 | filelock | 3.6.0 |
| Flask | 1.1.2 | flatbuffers | 22.12.6 | fonttools | 4.25.0 |
| fsspec | 2022.2.0 | future | 0.18.2 | gast | 0.4.0 |
| gitdb | 4.0.10 | GitPython | 3.1.27 | google-auth | 1.33.0 |
| google-auth-oauthlib | 0.4.6 | google-pasta | 0.2.0 | grpcio | 1.42.0 |
| gunicorn | 20.1.0 | gviz-api | 1.10.0 | h5py | 3.6.0 |
| hijri-converter | 2.2.4 | holidays | 0.17.2 | horovod | 0.26.1 |
| htmlmin | 0.1.12 | huggingface-hub | 0.11.1 | idna | 3.3 |
| ImageHash | 4.3.1 | imbalanced-learn | 0.8.1 | importlib-metadata | 4.11.3 |
| ipykernel | 6.15.3 | ipython | 8.5.0 | ipython-genutils | 0.2.0 |
| ipywidgets | 7.7.2 | isodate | 0.6.1 | itsdangerous | 2.0.1 |
| jedi | 0.18.1 | Jinja2 | 2.11.3 | jmespath | 0.10.0 |
| joblib | 1.1.0 | joblibspark | 0.5.0 | jsonschema | 4.4.0 |
| jupyter-client | 6.1.12 | jupyter_core | 4.11.2 | jupyterlab-pygments | 0.1.2 |
| jupyterlab-widgets | 1.0.0 | keras | 2.10.0 | keras-preprocessing | 1.1.2 |
| kiwisolver | 1.3.2 | korean-lunar-calendar | 0.3.1 | langcodes | 3.3.0 |
| libclang | 14.0.6 | lightgbm | 3.3.3 | llvmlite | 0.38.0 |
| LunarCalendar | 0.0.9 | Mako | 1.2.0 | Markdown | 3.3.4 |
| MarkupSafe | 2.0.1 | matplotlib | 3.5.1 | matplotlib-inline | 0.1.2 |
| mccabe | 0.7.0 | mistune | 0.8.4 | mleap | 0.20.0 |
| mlflow-skinny | 2.1.1 | multimethod | 1.9.1 | murmurhash | 1.0.9 |
| mypy-extensions | 0.4.3 | nbclient | 0.5.13 | nbconvert | 6.4.4 |
| nbformat | 5.3.0 | nest-asyncio | 1.5.5 | networkx | 2.7.1 |
| nltk | 3.7 | nodeenv | 1.7.0 | notebook | 6.4.8 |
| numba | 0.55.1 | numpy | 1.21.5 | oauthlib | 3.2.0 |
| opt-einsum | 3.3.0 | empaquetado | 21,3 | pandas | 1.4.2 |
| pandas-profiling | 3.5.0 | pandocfilters | 1.5.0 | paramiko | 2.9.2 |
| parso | 0.8.3 | pathspec | 0.9.0 | pathy | 0.6.1 |
| patsy | 0.5.2 | petastorm | 0.12.0 | pexpect | 4.8.0 |
| phik | 0.12.3 | pickleshare | 0.7.5 | Pillow | 9.0.1 |
| pip | 21.2.4 | platformdirs | 2.6.0 | plotly | 5.6.0 |
| pluggy | 1.0.0 | pmdarima | 2.0.2 | preshed | 3.0.8 |
| prompt-toolkit | 3.0.20 | prophet | 1.1.1 | protobuf | 3.19.4 |
| psutil | 5.8.0 | psycopg2 | 2.9.3 | ptyprocess | 0.7.0 |
| pure-eval | 0.2.2 | pyarrow | 7.0.0 | pyasn1 | 0.4.8 |
| pyasn1-modules | 0.2.8 | pybind11 | 2.10.1 | pycparser | 2.21 |
| pydantic | 1.10.2 | pyflakes | 2.5.0 | Pygments | 2.11.2 |
| PyGObject | 3.36.0 | PyJWT | 2.6.0 | PyMeeus | 0.5.12 |
| PyNaCl | 1.5.0 | pyodbc | 4.0.32 | pyparsing | 3.0.4 |
| pyright | 1.1.283 | pyrsistent | 0.18.0 | Python-dateutil | 2.8.2 |
| python-editor | 1.0.4 | python-lsp-jsonrpc | 1.0.0 | python-lsp-server | 1.6.0 |
| pytz | 2021.3 | PyWavelets | 1.3.0 | PyYAML | 6.0 |
| pyzmq | 22.3.0 | regex | 2022.3.15 | Solicitudes | 2.27.1 |
| requests-oauthlib | 1.3.1 | requests-unixsocket | 0.2.0 | rope | 0.22.0 |
| rsa | 4.7.2 | s3transfer | 0.5.0 | scikit-learn | 1.0.2 |
| scipy | 1.7.3 | seaborn | 0.11.2 | Send2Trash | 1.8.0 |
| setuptools | 61.2.0 | setuptools-git | 1.2 | shap | 0.41.0 |
| simplejson | 3.17.6 | six (seis) | 1.16.0 | segmentación | 0.0.7 |
| smart-open | 5.1.0 | smmap | 5.0.0 | soupsieve | 2.3.1 |
| spacy | 3.4.3 | spacy-legacy | 3.0.10 | spacy-loggers | 1.0.4 |
| spark-tensorflow-distributor | 1.0.0 | sqlparse | 0.4.2 | srsly | 2.4.5 |
| ssh-import-id | 5.10 | stack-data | 0.2.0 | statsmodels | 0.13.2 |
| tabulate | 0.8.9 | tangled-up-in-unicode | 0.2.0 | tenacity | 8.0.1 |
| tensorboard | 2.10.0 | tensorboard-data-server | 0.6.1 | tensorboard-plugin-profile | 2.8.0 |
| tensorboard-plugin-wit | 1.8.1 | tensorflow | 2.10.0 | tensorflow-estimator | 2.10.0 |
| tensorflow-io-gcs-filesystem | 0.29.0 | termcolor | 2.1.1 | terminado | 0.13.1 |
| testpath | 0.5.0 | thinc | 8.1.6 | threadpoolctl | 2.2.0 |
| tokenize-rt | 4.2.1 | tokenizers | 0.13.2 | tomli | 1.2.2 |
| torch | 1.13.0+cu117 | torchvision | 0.14.0+cu117 | tornado | 6.1 |
| tqdm | 4.64.0 | traitlets | 5.1.1 | transformers | 4.25.1 |
| typeguard | 2.13.3 | typer | 0.7.0 | typing_extensions | 4.1.1 |
| ujson | 5.1.0 | unattended-upgrades | 0,1 | urllib3 | 1.26.9 |
| virtualenv | 20.8.0 | visions | 0.7.5 | wasabi | 0.10.1 |
| wcwidth | 0.2.5 | webencodings | 0.5.1 | websocket-client | 0.58.0 |
| Werkzeug | 2.0.3 | whatthepatch | 1.0.3 | wheel | 0.37.1 |
| widgetsnbextension | 3.6.1 | wrapt | 1.12.1 | xgboost | 1.7.2 |
| yapf | 0.31.0 | zipp | 3.7.0 |
Bibliotecas de R
Las bibliotecas de R son idénticas a las bibliotecas de R de Databricks Runtime 12.1.
Bibliotecas de Java y Scala (clúster de Scala 2.12)
Además de las bibliotecas de Java y Scala de Databricks Runtime 12.1, los siguientes archivos JAR también se incluyen en Databricks Runtime 12.1 ML:
Clústeres de CPU
| Identificador de grupo | Identificador de artefacto | Versión |
|---|---|---|
| com.typesafe.akka | akka-actor_2.12 | 2.5.23 |
| ml.combust.mleap | mleap-databricks-runtime_2.12 | v0.20.0-db1 |
| ml.dmlc | xgboost4j-spark_2.12 | 1.6.2 |
| ml.dmlc | xgboost4j_2.12 | 1.6.2 |
| org.graphframes | graphframes_2.12 | 0.8.2-db1-spark3.2 |
| org.mlflow | mlflow-client | 2.0.1 |
| org.scala-lang.modules | scala-java8-compat_2.12 | 0.8.0 |
| org.tensorflow | spark-tensorflow-connector_2.12 | 1.15.0 |
Clústeres de GPU
| Identificador de grupo | Identificador de artefacto | Versión |
|---|---|---|
| com.typesafe.akka | akka-actor_2.12 | 2.5.23 |
| ml.combust.mleap | mleap-databricks-runtime_2.12 | v0.20.0-db1 |
| ml.dmlc | xgboost4j-gpu_2.12 | 1.6.2 |
| ml.dmlc | xgboost4j-spark-gpu_2.12 | 1.6.2 |
| org.graphframes | graphframes_2.12 | 0.8.2-db1-spark3.2 |
| org.mlflow | mlflow-client | 2.0.1 |
| org.scala-lang.modules | scala-java8-compat_2.12 | 0.8.0 |
| org.tensorflow | spark-tensorflow-connector_2.12 | 1.15.0 |