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Databricks Runtime 17.2 para Machine Learning proporciona un entorno listo para usar en el aprendizaje automático y la ciencia de datos basado en Databricks Runtime 17.2. Databricks Runtime ML contiene muchas bibliotecas de aprendizaje automático populares, como 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 TorchDistributor, DeepSpeed y Ray.
Nuevas características y mejoras
Databricks Runtime 17.2 ML se basa en Databricks Runtime 17.2. Para obtener información sobre las novedades de Databricks Runtime 17.2, incluidas Apache Spark MLlib y SparkR, consulte las notas de la versión de Databricks Runtime 17.2 .
Entorno del sistema
El entorno del sistema en Databricks Runtime 17.2 ML difiere de Databricks Runtime 17.2 de la manera siguiente.
- En el caso de los clústeres de GPU, Databricks Runtime ML incluye las siguientes bibliotecas de GPU de NVIDIA:
- CUDA 12.6
- cublas 12.6.4.1-1
- cusolver 11.7.1.2-1
- cupti 12.6.80-1
- cusparse 12.5.4.2-1
- cuDNN 9.5.1.17-1
- NCCL 2.26.2
- TensorRT 10.2.0.19-1
Libraries
En las secciones siguientes se enumeran las bibliotecas incluidas en Databricks Runtime 17.2 ML que difieren de las incluidas en Databricks Runtime 17.2.
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 17.2 ML incluye las siguientes bibliotecas de nivel superior:
- Conjuntos de datos
- GraphFrames
- MLflow
- PyTorch
- spark-tensorflow-connector (conector para Spark y TensorFlow)
- Scikit-learn
- streaming
- TensorFlow
- TensorBoard
- transformers
Bibliotecas de Python
Databricks Runtime 17.2 ML usa virtualenv para la administración de paquetes de Python e incluye muchos paquetes populares de ML.
Para reproducir el entorno de Python de Ml en tiempo de ejecución de Databricks en el entorno virtual local de Python, descargue requirements-cpu-17.2.txt para clústeres de CPU o requirements-gpu-17.2.txt para clústeres de GPU. A continuación, ejecute pip install -r requirements-<cpu|gpu>-17.2.txt. Este comando instala todas las bibliotecas de código abierto que usa Databricks Runtime ML, pero no instala bibliotecas desarrolladas por Databricks, como databricks-automl.
Bibliotecas de Python en clústeres de CPU
| Biblioteca | Versión | Biblioteca | Versión | Biblioteca | Versión |
|---|---|---|---|---|---|
| absl-py | 1.0.0 | acelerar | 1.5.2 | aiohappyeyeballs | 2.4.4 |
| aiohttp | 3.11.10 | aiohttp-cors | 0.8.1 | aiosignal | 1.2.0 |
| alambique | 1.16.2 | tipos anotados | 0.7.0 | anyio | 4.6.2 |
| argcomplete | 3.6.2 | argon2-cffi | 21.3.0 | argon2-cffi-bindings | 21.2.0 |
| flecha | 1.3.0 | astor | 0.8.1 | "asttokens" | 2.0.5 |
| astunparse | 1.6.3 | async-lru | 2.0.4 | atributos | 24.3.0 |
| Audioread | 3.0.1 | comando automático | 2.2.2 | azure-common | 1.1.28 |
| azure-core | 1.35.0 | azure-cosmos | 4.3.1 | azure-identity | 1.20.0 |
| azure-mgmt-core | 1.6.0 | azure-mgmt-web | 8.0.0 | azure-storage-blob | 12.23.0 |
| Servicio de Azure Storage File Data Lake | 12.17.0 | babel | 2.16.0 | backoff | 2.2.1 |
| backports.tarfile | 1.2.0 | bcrypt | 3.2.0 | beautifulsoup4 | 4.12.3 |
| negro | 24.10.0 | blanquear | 6.2.0 | intermitente | 1.7.0 |
| felicidad | 0.7.11 | boto3 | 1.36.2 | botocore | 1.36.3 |
| Brotli | 1.1.0 | cachetools | 5.5.1 | catálogo | 2.0.10 |
| codificadores de categorías | 2.6.3 | certifi | 2025.1.31 | cffi | 1.17.1 |
| chardet | 4.0.0 | charset-normalizer | 3.3.2 | circuitbreaker | 2.1.3 |
| Haz clic | 8.1.7 | cloudpathlib | 0.21.1 | cloudpickle | 3.0.0 |
| cmdstanpy | 1.2.5 | colorido | 0.5.7 | colorlog | 6.9.0 |
| Comunicación | 0.2.1 | confitería | 0.1.5 | configparser | 5.2.0 |
| contourpy | 1.3.1 | coolname | 2.2.0 | cramjam | 2.10.0 |
| criptografía | 43.0.3 | ciclista | 0.11.0 | cymem | 2.0.11 |
| Cython | 3.0.12 | dacita | 1.9.2 | databricks-automl-runtime | 0.2.21 |
| databricks-feature-engineering | 0.12.1 | SDK de Databricks | 0.49.0 | Conjuntos de datos | 3.5.0 |
| dbl-tempo | 0.1.26 | dbus-python | 1.3.2 | debugpy | 1.8.11 |
| decorator | 5.1.1 | velocidad profunda | 0.16.5 | defusedxml | 0.7.1 |
| dill | 0.3.8 | distlib | 0.3.9 | dm-tree | 0.1.9 |
| Conversión de docstring a markdown | 0.11 | einops | 0.8.1 | puntos de entrada | 0.4 |
| evaluar | 0.4.3 | executing | 0.8.3 | visión general de las facetas | 1.1.1 |
| Farama-Notifications | 0.0.4 | fastapi | 0.116.1 | fastjsonschema | 2.21.1 |
| fasttext-wheel | 0.9.2 | bloqueo de archivos | 3.13.1 | Flask | 2.2.5 |
| flatbuffers | 25.2.10 | fonttools | 4.55.3 | Fqdn | 1.5.1 |
| frozenlist | 1.5.0 | fsspec | 2023.5.0 | futuro | 0.18.3 |
| gast | 0.4.0 | gitdb | 4.0.11 | GitPython | 3.1.43 |
| google-api-core | 2.20.0 | google-auth | 2.40.3 | google-cloud-core | 2.4.3 |
| Google Cloud Storage (almacenamiento en la nube de Google) | 2.10.0 | google-crc32c | 1.7.1 | google-pasta | 0.2.0 |
| google-resumable-media (medios reanudables de Google) | 2.7.2 | googleapis-common-protos | 1.65.0 | gql | 3.5.3 |
| graphql-core | 3.2.4 | greenlet | 3.1.1 | grpcio | 1.67.0 |
| grpcio-status | 1.67.0 | gunicorn | 20.1.0 | gimnasio | 0.28.1 |
| h11 | 0.14.0 | h5py | 3.12.1 | hjson | 3.1.0 |
| vacaciones | 0.54 | htmlmin | 0.1.12 | httpcore | 1.0.2 |
| httplib2 | 0.20.4 | httpx | 0.27.0 | huggingface-hub | 0.30.2 |
| idna | 3.7 | Hash de imagen | 4.3.1 | imageio | 2.37.0 |
| imbalanced-learn | 0.13.0 | importlib-metadata | 6.6.0 | importlib_resources | 6.5.2 |
| inflect | 7.3.1 | iniconfig | 1.1.1 | ipyflow-core | 0.0.209 |
| ipykernel | 6.29.5 | ipython | 8.30.0 | ipython-genutils | 0.2.0 |
| ipywidgets | 7.8.1 | isodate | 0.6.1 | isoduration | 20.11.0 |
| Es peligroso | 2.2.0 | jaraco.context | 5.3.0 | jaraco.functools | 4.0.1 |
| jaraco.text | 3.12.1 | jax-jumpy | 1.0.0 | Jedi | 0.19.2 |
| Jinja2 | 3.1.5 | jiter | 0.10.0 | jmespath | 1.0.1 |
| joblib | 1.4.2 | joblibspark | 0.6.0 | json5 | 0.9.25 |
| jsonpatch | 1.33 | jsonpointer | 3.0.0 | jsonschema | 4.23.0 |
| jsonschema-specifications | 2023.7.1 | jupyter_events | 0.10.0 | jupyter-lsp | 2.2.0 |
| jupyter_client | 8.6.3 | jupyter_core | 5.7.2 | jupyter_server | 2.14.1 |
| jupyter_server_terminals | 0.4.4 | jupyterlab | 4.3.4 | jupyterlab-pygments | 0.1.2 |
| jupyterlab-widgets | 1.0.0 | jupyterlab_server (servidor de JupyterLab) | 2.27.3 | keras | 3.5.0 |
| kiwisolver | 1.4.8 | langchain | 0.3.21 | langchain-core | 0.3.63 |
| langchain-text-splitters | 0.3.8 | códigos de idioma | 3.5.0 | langsmith | 0.1.133 |
| datos_de_idioma | 1.3.0 | launchpadlib | 1.11.0 | lazr.restfulclient | 0.14.6 |
| lazr.uri | 1.0.6 | lazy_loader | 0.4 | libclang | 15.0.6.1 |
| librosa | 0.11.0 | lightgbm | 4.6.0 | lightning-utilities | 0.14.3 |
| linkify-it-py | 2.0.0 | llvmlite | 0.44.0 | lz4 | 4.3.2 |
| Mako | 1.2.0 | marisa-trie | 1.2.0 | Markdown | 3.4.1 |
| markdown-it-py | 2.2.0 | MarkupSafe | 3.0.2 | matplotlib | 3.10.0 |
| matplotlib-inline | 0.1.7 | Mccabe | 0.7.0 | mdit-py-plugins | 0.3.0 |
| mdurl | 0.1.0 | memray | 1.17.2 | mistune | 2.0.4 |
| ml_dtypes | 0.5.1 | mlflow-skinny | 3.0.1 | mmh3 | 5.1.0 |
| more-itertools | 10.3.0 | mosaicml-cli | 0.6.41 | mosaicml-streaming | 0.12.0 |
| mpmath | 1.3.0 | msal | 1.32.3 | msal-extensions | 1.3.1 |
| msgpack | 1.1.1 | Multidic | 6.1.0 | multimétodo | 1.12 |
| multiprocess | 0.70.16 | murmurhash | 1.0.13 | mypy-extensions | 1.0.0 |
| namex | 0.1.0 | nbclient | 0.8.0 | nbconvert | 7.16.4 |
| nbformat | 5.10.4 | nest-asyncio | 1.6.0 | networkx | 3.4.2 |
| ninja | 1.11.1.4 | NLTK | 3.9.1 | nodeenv | 1.9.1 |
| notebook | 7.3.2 | notebook_shim | 0.2.3 | numba | 0.61.0 |
| numpy | 2.1.3 | nvidia-nccl-cu12 | 2.27.5 | oauthlib | 3.2.0 |
| oci | 2.155.2 | openai | 1.69.0 | opencensus | 0.11.4 |
| opencensus-context==0.1.2 | 0.1.3 | opentelemetry-api | 1.35.0 | opentelemetry-sdk | 1.35.0 |
| convenciones-semánticas-de-opentelemetry | 0,56b0 | opt_einsum | 3.4.0 | optree | 0.16.0 |
| optuna | 3.6.1 | optuna-integration | 3.6.0 | orjson | 3.11.0 |
| overrides | 7.4.0 | embalaje | 24,2 | Pandas | 2.2.3 |
| pandocfilters | 1.5.0 | paramiko | 3.4.0 | parso | 0.8.4 |
| pathspec | 0.10.3 | chivo expiatorio | 1.0.1 | pexpect | 4.8.0 |
| phik | 0.12.5 | almohada | 11.1.0 | pip | 25.0.1 |
| platformdirs | 3.10.0 | plotly | 5.24.1 | pluggy | 1.5.0 |
| pmdarima | 2.0.4 | chucho | 1.8.2 | preshed | 3.0.10 |
| prometheus_client | 0.21.0 | prompt-toolkit | 3.0.43 | propcache | 0.2.0 |
| profeta | 1.1.6 | proto-plus | 1.26.1 | protobuf | 5.29.4 |
| psutil | 5.9.0 | psycopg2 | 2.9.3 | ptyprocess | 0.7.0 |
| pure-eval | 0.2.2 | puremagic | 1.30 | py-cpuinfo | 9.0.0 |
| py-spy | 0.4.0 | pyarrow | 19.0.1 | pyasn1 | 0.4.8 |
| pyasn1-modules | 0.2.8 | pybind11 | 3.0.0 | pyccolo | 0.0.71 |
| pycparser | 2.21 | pydantic | 2.10.6 | pydantic_core | 2.27.2 |
| pyflakes | 3.2.0 | Pygments | 2.15.1 | PyGObject | 3.48.2 |
| pyiceberg | 0.9.0 | PyJWT | 2.10.1 | PyNaCl | 1.5.0 |
| pyodbc | 5.2.0 | pyOpenSSL | 24.2.1 | pyparsing | 3.2.0 |
| pyright | 1.1.394 | pytesseract | 0.3.10 | pytest | 8.3.5 |
| Python-dateutil | 2.9.0.post0 | editor de Python | 1.0.4 | python-json-logger | 3.2.1 |
| python-lsp-jsonrpc | 1.1.2 | python-lsp-servidor | 1.12.0 | python-snappy | 0.7.3 |
| configuración de herramienta Python | 1.2.6 | pytorch-ranger | 0.1.1 | pytz | 2024.1 |
| PyWavelets | 1.8.0 | PyYAML | 6.0.2 | pyzmq | 26.2.0 |
| cuestionario | 2.1.0 | ray | 2.37.0 | referencing | 0.30.2 |
| regex | 2024.11.6 | solicitudes | 2.32.3 | requests-oauthlib | 1.3.1 |
| requests-toolbelt | 1.0.0 | rfc3339-validator | 0.1.4 | rfc3986-validator | 0.1.1 |
| rico | 13.9.4 | cuerda | 1.12.0 | rpds-py | 0.22.3 |
| rsa | 4.9.1 | ruamel.yaml | 0.18.14 | ruamel.yaml.clib | 0.2.12 |
| s3transfer | 0.11.3 | safetensors | 0.5.3 | scikit-image | 0.25.0 |
| scikit-learn | 1.6.1 | scipy | 1.15.1 | biblioteca de visualización de datos de Python llamada seaborn | 0.13.2 |
| Send2Trash | 1.8.2 | transformadores de frases | 4.0.1 | frase | 0.2.0 |
| setuptools | 74.0.0 | shap | 0.47.1 | Shellingham | 1.5.4 |
| simplejson | 3.17.6 | six | 1.16.0 | sklearn-compat | 0.1.3 |
| rebanador | 0.0.8 | smart_open | 7.3.0.post1 | smmap | 5.0.0 |
| sniffio | 1.3.0 | sortedcontainers | 2.4.0 | archivo de sonido | 0.13.1 |
| soupsieve | 2,5 | soxr | 0.5.0.post1 | spacy | 3.7.5 |
| spacy-legacy | 3.0.12 | espacy-loggers | 1.0.5 | SQLAlchemy | 2.0.37 |
| sqlparse | 0.4.2 | srsly | 2.5.1 | ssh-import-id | 5.11 |
| stack-data | 0.2.0 | estaño | 0.5.1 | Starlette | 0.47.2 |
| statsmodels (paquete de Python para análisis estadístico) | 0.14.4 | strictyaml | 1.7.3 | Sintonía | 1.13.3 |
| tabulate | 0.9.0 | tenacidad | 9.0.0 | tensorboard | 2.19.0 |
| servidor-de-datos-de-tensorboard | 0.7.2 | tensorboardX | 2.6.4 | TensorFlow | 2.19.0 |
| Estimador de TensorFlow | 2.15.0 | termcolor | 3.1.0 | terminado | 0.17.1 |
| textual | 4.0.0 | tf_keras | 2.19.0 | thinc | 8.2.4 |
| threadpoolctl | 3.5.0 | tifffile | 2024.12.12 | tiktoken | 0.9.0 |
| tinycss2 | 1.4.0 | tokenize_rt | 6.1.0 | tokenizers | 0.21.0 |
| tomli | 2.0.1 | antorcha | 2.7.0+cpu | torch-optimizer | 0.3.0 |
| torcheval | 0.0.7 | torchmetrics | 1.6.0 | antorcha | 0.22.0+cpu |
| tornado | 6.4.2 | tqdm | 4.67.1 | traitlets | 5.14.3 |
| Transformadores | 4.51.3 | typeguard | 4.4.2 | typer | 0.16.0 |
| types-python-dateutil | 2.9.0.20250708 | typing_extensions | 4.12.2 | tzdata | 2024.1 |
| uc-micro-py | 1.0.1 | ujson | 5.10.0 | unattended-upgrades | 0,1 |
| uri-template | 1.3.0 | urllib3 | 2.3.0 | uvicorn | 0.35.0 |
| validadores | 0.35.0 | virtualenv | 20.29.3 | Visiones | 0.8.1 |
| wadllib | 1.3.6 | wasabi | 1.1.3 | wcwidth | 0.2.5 |
| weasel | 0.4.1 | webcolores | 24.11.1 | codificaciones web | 0.5.1 |
| cliente de websocket | 1.8.0 | websockets | 11.0.3 | Werkzeug | 3.1.3 |
| ¿Qué es el parche? | 1.0.2 | rueda | 0.45.1 | widgetsnbextension | 3.6.6 |
| nube de palabras | 1.9.4 | envuelto | 1.17.0 | xgboost | 3.0.0 |
| xgboost-ray | 0.1.19 | xxhash | 3.5.0 | yapf | 0.40.2 |
| yarl | 1.18.0 | ydata-profiling | 4.16.1 | zipp | 3.21.0 |
| zstd | 1.5.5.1 |
Bibliotecas de Python en clústeres de GPU
Nota:
PyTorch usa las dependencias de PYPI de CUDA para proporcionar compatibilidad con CUDA en lugar de las versiones de biblioteca de CUDA integradas en Databricks Runtime 17.2 ML.
| Biblioteca | Versión | Biblioteca | Versión | Biblioteca | Versión |
|---|---|---|---|---|---|
| absl-py | 1.0.0 | acelerar | 1.5.2 | aiohappyeyeballs | 2.4.4 |
| aiohttp | 3.11.10 | aiohttp-cors | 0.8.1 | aiosignal | 1.2.0 |
| tipos anotados | 0.7.0 | anyio | 4.6.2 | argcomplete | 3.6.2 |
| argon2-cffi | 21.3.0 | argon2-cffi-bindings | 21.2.0 | flecha | 1.3.0 |
| astor | 0.8.1 | "asttokens" | 2.0.5 | astunparse | 1.6.3 |
| async-lru | 2.0.4 | atributos | 24.3.0 | Audioread | 3.0.1 |
| comando automático | 2.2.2 | azure-common | 1.1.28 | azure-core | 1.35.0 |
| azure-cosmos | 4.3.1 | azure-identity | 1.20.0 | azure-mgmt-core | 1.6.0 |
| azure-mgmt-web | 8.0.0 | azure-storage-blob | 12.23.0 | Servicio de Azure Storage File Data Lake | 12.17.0 |
| babel | 2.16.0 | backoff | 2.2.1 | backports.tarfile | 1.2.0 |
| bcrypt | 3.2.0 | beautifulsoup4 | 4.12.3 | negro | 24.10.0 |
| blanquear | 6.2.0 | intermitente | 1.7.0 | felicidad | 0.7.11 |
| boto3 | 1.36.2 | botocore | 1.36.3 | Brotli | 1.1.0 |
| cachetools | 5.5.1 | catálogo | 2.0.10 | codificadores de categorías | 2.6.3 |
| certifi | 2025.1.31 | cffi | 1.17.1 | chardet | 4.0.0 |
| charset-normalizer | 3.3.2 | circuitbreaker | 2.1.3 | Haz clic | 8.1.7 |
| cloudpathlib | 0.21.1 | cloudpickle | 3.0.0 | cmdstanpy | 1.2.5 |
| colorido | 0.5.7 | colorlog | 6.9.0 | Comunicación | 0.2.1 |
| confitería | 0.1.5 | configparser | 5.2.0 | contourpy | 1.3.1 |
| coolname | 2.2.0 | cramjam | 2.10.0 | criptografía | 43.0.3 |
| ciclista | 0.11.0 | cymem | 2.0.11 | Cython | 3.0.12 |
| dacita | 1.9.2 | databricks-automl-runtime | 0.2.21 | databricks-feature-engineering | 0.12.1 |
| SDK de Databricks | 0.49.0 | Conjuntos de datos | 3.5.0 | dbl-tempo | 0.1.26 |
| dbus-python | 1.3.2 | debugpy | 1.8.11 | decorator | 5.1.1 |
| velocidad profunda | 0.16.5 | defusedxml | 0.7.1 | dill | 0.3.8 |
| distlib | 0.3.9 | dm-tree | 0.1.9 | Conversión de docstring a markdown | 0.11 |
| einops | 0.8.1 | puntos de entrada | 0.4 | evaluar | 0.4.3 |
| executing | 0.8.3 | visión general de las facetas | 1.1.1 | Farama-Notifications | 0.0.4 |
| fastapi | 0.116.1 | fastjsonschema | 2.21.1 | fasttext-wheel | 0.9.2 |
| bloqueo de archivos | 3.13.1 | flash_attn | 2.7.4.post1 | Flask | 2.2.5 |
| flatbuffers | 25.2.10 | fonttools | 4.55.3 | Fqdn | 1.5.1 |
| frozenlist | 1.5.0 | fsspec | 2023.5.0 | futuro | 0.18.3 |
| gast | 0.4.0 | gitdb | 4.0.11 | GitPython | 3.1.43 |
| google-api-core | 2.20.0 | google-auth | 2.40.3 | google-cloud-core | 2.4.3 |
| Google Cloud Storage (almacenamiento en la nube de Google) | 2.10.0 | google-crc32c | 1.7.1 | google-pasta | 0.2.0 |
| google-resumable-media (medios reanudables de Google) | 2.7.2 | googleapis-common-protos | 1.65.0 | gql | 3.5.3 |
| graphql-core | 3.2.4 | greenlet | 3.1.1 | grpcio | 1.67.0 |
| grpcio-status | 1.67.0 | gunicorn | 20.1.0 | gimnasio | 0.28.1 |
| h11 | 0.14.0 | h5py | 3.12.1 | hjson | 3.1.0 |
| vacaciones | 0.54 | htmlmin | 0.1.12 | httpcore | 1.0.2 |
| httplib2 | 0.20.4 | httpx | 0.27.0 | huggingface-hub | 0.30.2 |
| idna | 3.7 | Hash de imagen | 4.3.1 | imageio | 2.37.0 |
| imbalanced-learn | 0.13.0 | importlib-metadata | 6.6.0 | importlib_resources | 6.5.2 |
| inflect | 7.3.1 | iniconfig | 1.1.1 | ipyflow-core | 0.0.209 |
| ipykernel | 6.29.5 | ipython | 8.30.0 | ipython-genutils | 0.2.0 |
| ipywidgets | 7.8.1 | isodate | 0.6.1 | isoduration | 20.11.0 |
| Es peligroso | 2.2.0 | jaraco.context | 5.3.0 | jaraco.functools | 4.0.1 |
| jaraco.text | 3.12.1 | jax-jumpy | 1.0.0 | Jedi | 0.19.2 |
| Jinja2 | 3.1.5 | jiter | 0.10.0 | jmespath | 1.0.1 |
| joblib | 1.4.2 | joblibspark | 0.6.0 | json5 | 0.9.25 |
| jsonpatch | 1.33 | jsonpointer | 3.0.0 | jsonschema | 4.23.0 |
| jsonschema-specifications | 2023.7.1 | jupyter_events | 0.10.0 | jupyter-lsp | 2.2.0 |
| jupyter_client | 8.6.3 | jupyter_core | 5.7.2 | jupyter_server | 2.14.1 |
| jupyter_server_terminals | 0.4.4 | jupyterlab | 4.3.4 | jupyterlab-pygments | 0.1.2 |
| jupyterlab-widgets | 1.0.0 | jupyterlab_server (servidor de JupyterLab) | 2.27.3 | keras | 3.5.0 |
| kiwisolver | 1.4.8 | langchain | 0.3.21 | langchain-core | 0.3.63 |
| langchain-text-splitters | 0.3.8 | códigos de idioma | 3.5.0 | langsmith | 0.1.133 |
| datos_de_idioma | 1.3.0 | launchpadlib | 1.11.0 | lazr.restfulclient | 0.14.6 |
| lazr.uri | 1.0.6 | lazy_loader | 0.4 | libclang | 15.0.6.1 |
| librosa | 0.11.0 | lightgbm | 4.6.0 | lightning-utilities | 0.14.3 |
| linkify-it-py | 2.0.0 | llvmlite | 0.44.0 | lz4 | 4.3.2 |
| Mako | 1.2.0 | marisa-trie | 1.2.0 | Markdown | 3.4.1 |
| markdown-it-py | 2.2.0 | MarkupSafe | 3.0.2 | matplotlib | 3.10.0 |
| matplotlib-inline | 0.1.7 | Mccabe | 0.7.0 | mdit-py-plugins | 0.3.0 |
| mdurl | 0.1.0 | memray | 1.17.2 | mistune | 2.0.4 |
| ml_dtypes | 0.5.1 | mlflow-skinny | 3.0.1 | mmh3 | 5.1.0 |
| more-itertools | 10.3.0 | mosaicml-cli | 0.6.41 | mosaicml-streaming | 0.12.0 |
| mpmath | 1.3.0 | msal | 1.32.3 | msal-extensions | 1.3.1 |
| msgpack | 1.1.1 | Multidic | 6.1.0 | multimétodo | 1.12 |
| multiprocess | 0.70.16 | murmurhash | 1.0.13 | mypy-extensions | 1.0.0 |
| namex | 0.1.0 | nbclient | 0.8.0 | nbconvert | 7.16.4 |
| nbformat | 5.10.4 | nest-asyncio | 1.6.0 | networkx | 3.4.2 |
| ninja | 1.11.1.4 | NLTK | 3.9.1 | nodeenv | 1.9.1 |
| notebook | 7.3.2 | notebook_shim | 0.2.3 | numba | 0.61.0 |
| numpy | 2.1.3 | nvidia-cublas-cu12 | 12.6.4.1 | nvidia-cuda-cupti-cu12 | 12.6.80 |
| nvidia-cuda-nvrtc-cu12 | 12.6.77 | nvidia-cuda-runtime-cu12 | 12.6.77 | nvidia-cudnn-cu12 | 9.5.1.17 |
| nvidia-cufft-cu12 | 11.3.0.4 | nvidia-cufile-cu12 | 1.11.1.6 | nvidia-curand-cu12 | 10.3.7.77 |
| nvidia-cusolver-cu12 | 11.7.1.2 | nvidia-cusparse-cu12 | 12.5.4.2 | nvidia-cusparselt-cu12 | 0.6.3 |
| nvidia-nccl-cu12 | 2.26.2 | nvidia-nvjitlink-cu12 | 12.6.85 | nvidia-nvtx-cu12 | 12.6.77 |
| oauthlib | 3.2.0 | oci | 2.155.2 | openai | 1.69.0 |
| opencensus | 0.11.4 | opencensus-context==0.1.2 | 0.1.3 | opentelemetry-api | 1.35.0 |
| opentelemetry-sdk | 1.35.0 | convenciones-semánticas-de-opentelemetry | 0,56b0 | opt_einsum | 3.4.0 |
| optree | 0.16.0 | optuna | 3.6.1 | optuna-integration | 3.6.0 |
| orjson | 3.11.0 | overrides | 7.4.0 | embalaje | 24,2 |
| Pandas | 2.2.3 | pandocfilters | 1.5.0 | paramiko | 3.4.0 |
| parso | 0.8.4 | pathspec | 0.10.3 | chivo expiatorio | 1.0.1 |
| pexpect | 4.8.0 | phik | 0.12.5 | almohada | 11.1.0 |
| pip | 25.0.1 | platformdirs | 3.10.0 | plotly | 5.24.1 |
| pluggy | 1.5.0 | pmdarima | 2.0.4 | chucho | 1.8.2 |
| preshed | 3.0.10 | prometheus_client | 0.21.0 | prompt-toolkit | 3.0.43 |
| propcache | 0.2.0 | profeta | 1.1.6 | proto-plus | 1.26.1 |
| protobuf | 5.29.4 | psutil | 5.9.0 | psycopg2 | 2.9.3 |
| ptyprocess | 0.7.0 | pure-eval | 0.2.2 | puremagic | 1.30 |
| py-cpuinfo | 9.0.0 | py-spy | 0.4.0 | pyarrow | 19.0.1 |
| pyasn1 | 0.4.8 | pyasn1-modules | 0.2.8 | pybind11 | 3.0.0 |
| pyccolo | 0.0.71 | pycparser | 2.21 | pydantic | 2.10.6 |
| pydantic_core | 2.27.2 | pyflakes | 3.2.0 | Pygments | 2.15.1 |
| PyGObject | 3.48.2 | pyiceberg | 0.9.0 | PyJWT | 2.10.1 |
| PyNaCl | 1.5.0 | pyodbc | 5.2.0 | pyOpenSSL | 24.2.1 |
| pyparsing | 3.2.0 | pyright | 1.1.394 | pytesseract | 0.3.10 |
| pytest | 8.3.5 | Python-dateutil | 2.9.0.post0 | editor de Python | 1.0.4 |
| python-json-logger | 3.2.1 | python-lsp-jsonrpc | 1.1.2 | python-lsp-servidor | 1.12.0 |
| python-snappy | 0.7.3 | configuración de herramienta Python | 1.2.6 | pytorch-ranger | 0.1.1 |
| pytz | 2024.1 | PyWavelets | 1.8.0 | PyYAML | 6.0.2 |
| pyzmq | 26.2.0 | cuestionario | 2.1.0 | ray | 2.37.0 |
| referencing | 0.30.2 | regex | 2024.11.6 | solicitudes | 2.32.3 |
| requests-oauthlib | 1.3.1 | requests-toolbelt | 1.0.0 | rfc3339-validator | 0.1.4 |
| rfc3986-validator | 0.1.1 | rico | 13.9.4 | cuerda | 1.12.0 |
| rpds-py | 0.22.3 | rsa | 4.9.1 | ruamel.yaml | 0.18.14 |
| ruamel.yaml.clib | 0.2.12 | s3transfer | 0.11.3 | safetensors | 0.5.3 |
| scikit-image | 0.25.0 | scikit-learn | 1.6.1 | scipy | 1.15.1 |
| biblioteca de visualización de datos de Python llamada seaborn | 0.13.2 | Send2Trash | 1.8.2 | transformadores de frases | 4.0.1 |
| frase | 0.2.0 | setuptools | 74.0.0 | shap | 0.47.1 |
| Shellingham | 1.5.4 | simplejson | 3.17.6 | six | 1.16.0 |
| sklearn-compat | 0.1.3 | rebanador | 0.0.8 | smart_open | 7.3.0.post1 |
| smmap | 5.0.0 | sniffio | 1.3.0 | sortedcontainers | 2.4.0 |
| archivo de sonido | 0.13.1 | soupsieve | 2,5 | soxr | 0.5.0.post1 |
| spacy | 3.7.5 | spacy-legacy | 3.0.12 | espacy-loggers | 1.0.5 |
| SQLAlchemy | 2.0.37 | sqlparse | 0.4.2 | srsly | 2.5.1 |
| ssh-import-id | 5.11 | stack-data | 0.2.0 | estaño | 0.5.1 |
| Starlette | 0.47.2 | statsmodels (paquete de Python para análisis estadístico) | 0.14.4 | strictyaml | 1.7.3 |
| Sintonía | 1.13.3 | tabulate | 0.9.0 | tenacidad | 9.0.0 |
| tensorboard | 2.19.0 | servidor-de-datos-de-tensorboard | 0.7.2 | tensorboardX | 2.6.4 |
| TensorFlow | 2.19.0 | Estimador de TensorFlow | 2.15.0 | termcolor | 3.1.0 |
| terminado | 0.17.1 | textual | 4.0.0 | tf_keras | 2.19.0 |
| thinc | 8.2.4 | threadpoolctl | 3.5.0 | tifffile | 2024.12.12 |
| tiktoken | 0.9.0 | tinycss2 | 1.4.0 | tokenize_rt | 6.1.0 |
| tokenizers | 0.21.0 | tomli | 2.0.1 | antorcha | 2.7.0 |
| torch-optimizer | 0.3.0 | torcheval | 0.0.7 | torchmetrics | 1.6.0 |
| antorcha | 0.22.0 | tornado | 6.4.2 | tqdm | 4.67.1 |
| traitlets | 5.14.3 | Transformadores | 4.51.3 | Tritón | 3.3.0 |
| typeguard | 4.4.2 | typer | 0.16.0 | types-python-dateutil | 2.9.0.20250708 |
| typing_extensions | 4.12.2 | tzdata | 2024.1 | uc-micro-py | 1.0.1 |
| ujson | 5.10.0 | unattended-upgrades | 0,1 | uri-template | 1.3.0 |
| urllib3 | 2.3.0 | uvicorn | 0.35.0 | validadores | 0.35.0 |
| virtualenv | 20.29.3 | Visiones | 0.8.1 | wadllib | 1.3.6 |
| wasabi | 1.1.3 | wcwidth | 0.2.5 | weasel | 0.4.1 |
| webcolores | 24.11.1 | codificaciones web | 0.5.1 | cliente de websocket | 1.8.0 |
| websockets | 11.0.3 | Werkzeug | 3.1.3 | ¿Qué es el parche? | 1.0.2 |
| rueda | 0.45.1 | widgetsnbextension | 3.6.6 | nube de palabras | 1.9.4 |
| envuelto | 1.17.0 | xgboost | 3.0.0 | xgboost-ray | 0.1.19 |
| xxhash | 3.5.0 | yapf | 0.40.2 | yarl | 1.18.0 |
| ydata-profiling | 4.16.1 | zipp | 3.21.0 | zstd | 1.5.5.1 |
Bibliotecas de R
Las bibliotecas de R son idénticas a las bibliotecas de R en Databricks Runtime 17.2.
Bibliotecas de Java y Scala (clúster de Scala 2.12)
Además de las bibliotecas de Java y Scala en Databricks Runtime 17.2, Databricks Runtime 17.2 ML contiene los siguientes JAR:
Clústeres de CPU
| Identificador de grupo | Id. de artefacto | Versión |
|---|---|---|
| ml.dmlc | xgboost4j-spark_2.13 | 2.1.3 |
| ml.dmlc | xgboost4j_2.13 | 2.1.3 |
| org.graphframes | graphframes_2.13 | 0.8.4-db1-spark3.5 |
| org.mlflow | mlflow-client | 2.15.1 |
| org.scala-lang.modules | scala-collection-compat_2.13 | 2.12.0 |
| org.tensorflow | spark-tensorflow-connector_2.13 | 1.15.0 |
Clústeres de GPU
| Identificador de grupo | Id. de artefacto | Versión |
|---|---|---|
| ml.dmlc | xgboost4j-spark_2.13 | 2.1.3 |
| ml.dmlc | xgboost4j_2.13 | 2.1.3 |
| org.graphframes | graphframes_2.13 | 0.8.4-db1-spark3.5 |
| org.mlflow | mlflow-client | 2.15.1 |
| org.scala-lang.modules | scala-collection-compat_2.13 | 2.12.0 |
| org.tensorflow | spark-tensorflow-connector_2.13 | 1.15.0 |
Versiones no compatibles
Sugerencia
Para ver las notas de las versiones de Databricks Runtime que han llegado al fin de soporte (EoS), consulte las Notas de lanzamiento de fin de soporte de Databricks Runtime. Las versiones de EoS Databricks Runtime se han retirado y es posible que no se actualicen.