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Las notas de la versión siguientes proporcionan información sobre Databricks Runtime 19 ML.
Azure Databricks publicó esta versión en junio de 2026.
Important
Databricks Runtime 19 está en beta. El contenido de los entornos admitidos puede cambiar durante la versión Beta. Los cambios pueden incluir la lista de paquetes o versiones de paquetes instalados.
Databricks Runtime 19 ML se basa en Databricks Runtime 19. Para obtener información sobre las novedades de Databricks Runtime 19, incluido Apache Spark MLlib y SparkR, consulte las notas de la versión de Databricks Runtime 19 (beta).
Cambios de comportamiento
-
Paquetes de Python eliminados: En comparación con Databricks Runtime 18 ML, se han eliminado aproximadamente 40 paquetes del runtime de ML en Databricks Runtime 19 ML, además de los paquetes eliminados en Databricks Runtime 19. Se elimina la pila TensorFlow/Keras (
tensorflow,keras,tf_keras). Las cargas de trabajo que dependen de estos paquetes deben instalarlas explícitamente mediante una biblioteca de clústeres o un script de inicialización. Para obtener la lista completa de paquetes incluidos en Databricks Runtime 19 ML, consulte Python bibliotecas.
Nuevas características y mejoras
Las actualizaciones de biblioteca incluyen:
- Actualización de CUDA a la versión 13.0
- flash_attn 2.8.3
- langchain 1.3.1
- mlflow-skinny 3.12.0
- openai 2.37.0
- torch 2.12.0
- torchvision 0.27.0
- transformadores 4.57.6
- triton 3.7.0
- xgboost 3.2.0
Entorno del sistema
El entorno del sistema en Databricks Runtime 19 ML difiere de Databricks Runtime 19 como se indica a continuación.
- En el caso de los clústeres de GPU, Databricks Runtime ML incluye las siguientes bibliotecas de GPU de NVIDIA:
- CUDA 13.0
- cublas 13.1.1.3-1
- cusolver 12.0.4.66
- cupti 13.0.85
- cusparse 12.6.3.3
- cuDNN 9.23.0.39
- NCCL 2.28.3
Libraries
En las secciones siguientes se enumeran las bibliotecas incluidas en Databricks Runtime 19 ML que difieren de las incluidas en Databricks Runtime 19.
Bibliotecas de nivel superior
Databricks Runtime 19 ML incluye las siguientes bibliotecas de nivel superior:
Bibliotecas de Python
Databricks Runtime 19 ML usa virtualenv para Python administración de paquetes e incluye muchos paquetes populares de ML.
Para reproducir el entorno de Python de Databricks Runtime ML en el entorno virtual local de Python, descargue requirements-cpu-19.txt para clústeres de CPU o requirements-gpu-19.txt para clústeres de GPU. A continuación, ejecute pip install -r requirements-<cpu|gpu>-19.txt. Este comando instala todas las bibliotecas de código abierto que usa Databricks Runtime ML, pero no instala bibliotecas desarrolladas por Databricks.
Bibliotecas de Python en clústeres de CPU
| Library | Versión | Library | Versión | Library | Versión |
|---|---|---|---|---|---|
| absl-py | 2.3.1 | acelerar | 1.13.0 | aiohappyeyeballs | 2.6.1 |
| aiohttp | 3.13.2 | aiohttp-cors | 0.8.1 | aiosignal | 1.4.0 |
| alambique | 1.18.4 | documento anotado | 0.0.4 | tipos con anotaciones | 0.7.0 |
| anyio | 4.10.0 | arro3-core | 0.8.0 | "asttokens" | 3.0.0 |
| astunparse | 1.6.3 | attrs | 25.4.0 | Audioread | 3.1.0 |
| autocommand | 2.2.2 | azure-core | 1.41.0 | azure-cosmos | 4.3.1 |
| azure-identity | 1.25.3 | azure-mgmt-core | 1.6.0 | azure-mgmt-web | 10.1.0 |
| azure-storage-blob | 12.29.0 | azure-storage-file-datalake (servicio para el almacenamiento de archivos en un lago de datos) | 12.24.0 | backports.tarfile | 1.2.0 |
| black | 25.9.0 | intermitente | 1.7.0 | felicidad | 1.3.3 |
| boto3 | 1.40.46 | botocore | 1.40.46 | cachetools | 5.5.1 |
| catálogo | 2.0.10 | certifi | 2025.11.12 | cffi | 2.0.0 |
| normalizador de conjuntos de caracteres | 3.4.4 | click | 8.2.1 | cloudpathlib | 0.24.0 |
| cloudpickle | 3.1.1 | cmdstanpy | 1.3.0 | colorido | 0.5.8 |
| colorlog | 6.10.1 | comm | 0.2.3 | confitería | 1.3.3 |
| contourpy | 1.3.3 | cryptography | 46.0.3 | cycler | 0.11.0 |
| cymem | 2.0.13 | databricks-agents | 1.10.2 | databricks-feature-engineering | 0.13.0.1 |
| databricks-sdk (kit de desarrollo de software de Databricks) | 0.108.0 | dataclasses-json | 0.6.7 | datasets | 4.8.5 |
| dbl-tempo | 0.1.26 | dbus-python | 1.3.2 | debugpy | 1.8.16 |
| decorator | 5.2.1 | velocidad profunda | 0.19.0 | deltalake | 1.5.1 |
| Deprecated | 1.3.1 | dill | 0.4.0 | distlib | 0.4.0 |
| dm-tree | 0.1.10 | einops | 0.8.2 | evaluate | 0.4.6 |
| executing | 2.2.1 | Farama-Notifications | 0.0.6 | fastapi | 0.136.1 |
| filelock | 3.20.0 | Flask | 2.2.5 | fonttools | 4.60.1 |
| frozenlist | 1.8.0 | fsspec | 2023.5.0 | gitdb | 4.0.11 |
| GitPython | 3.1.45 | google-api-core | 2.30.3 | google-auth | 2.53.0 |
| google-cloud-core | 2.6.0 | google-cloud-storage | 3.10.1 | google-crc32c | 1.8.0 |
| google-resumable-media | 2.9.0 | googleapis-common-protos | 1.71.0 | graphql-core | 3.2.4 |
| greenlet | 3.2.4 | grpcio | 1.76.0 | grpcio-status | 1.76.0 |
| gimnasio | 0.28.1 | h11 | 0.16.0 | hf-xet | 1.5.0 |
| hjson | 3.1.0 | vacaciones | 0.54 | httpcore | 1.0.9 |
| httplib2 | 0.20.4 | httpx | 0.28.1 | huggingface_hub | 0.36.2 |
| idna | 3,11 | ImageIO | 2.37.2 | imbalanced-learn | 0.14.0 |
| importlib_metadata | 8.7.0 | importlib_resources | 7.1.0 | inflect | 7.3.1 |
| iniconfig | 2.1.0 | ipyflow-core | 0.0.227 | ipykernel | 6.31.0 |
| ipython | 9.7.0 | ipython_pygments_lexers | 1.1.1 | ipywidgets | 8.1.7 |
| isodate | 0.7.2 | Es peligroso | 2.2.0 | jaraco.collections | 5.1.0 |
| 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 | 3.1.6 |
| jiter | 0.15.0 | jmespath | 1.0.1 | joblib | 1.5.2 |
| joblibspark | 0.6.0 | jsonpatch | 1.33 | jsonpointer | 3.1.1 |
| jsonschema | 4.25.0 | jsonschema-specifications | 2025.9.1 | jupyter_client | 8.6.3 |
| jupyter_core | 5.8.1 | jupyterlab_widgets | 3.0.15 | kiwisolver | 1.4.8 |
| langchain | 1.3.1 | langchain-core | 1.4.0 | langchain-protocol | 0.0.15 |
| langgraph | 1.2.1 | langgraph-checkpoint | 4.1.1 | langgraph-prebuilt | 1.1.0 |
| langgraph-sdk | 0.3.15 | langsmith | 0.4.41 | launchpadlib | 1.11.0 |
| lazr.restfulclient | 0.14.6 | lazr.uri | 1.0.6 | lazy_loader | 0.4 |
| librosa | 0.11.0 | lightgbm | 4.6.0 | linkify-it-py | 2.0.3 |
| llvmlite | 0.45.1 | lz4 | 4.4.5 | Mako | 1.3.12 |
| marisa-trie | 1.2.0 | Markdown | 3.8 | markdown-it-py | 2.2.0 |
| MarkupSafe | 3.0.2 | malvavisco | 3.26.2 | matplotlib | 3.10.6 |
| matplotlib-inline | 0.2.1 | Mccabe | 0.7.0 | mdit-py-plugins | 0.5.0 |
| mdurl | 0.1.2 | memray | 1.19.3 | mlflow-skinny | 3.12.0 |
| mmh3 | 5.2.1 | more-itertools | 10.3.0 | mpmath | 1.3.0 |
| msal | 1.36.0 | msal-extensions | 1.3.1 | msgpack | 1.1.2 |
| msrest | 0.7.1 | Multidic | 6.7.0 | multiproceso | 0.70.18 |
| murmurhash | 1.0.15 | mypy-extensions | 1.0.0 | nest-asyncio | 1.6.0 |
| networkx | 3,5 | ninja | 1.13.0 | NLTK | 3.9.2 |
| nodeenv | 1.10.0 | numba | 0.62.1 | numpy | 2.3.4 |
| nvidia-nccl-cu12 | 2.30.4 | oauthlib | 3.2.0 | openai | 2.37.0 |
| opencensus | 0.11.4 | opencensus-context==0.1.2 | 0.1.3 | opentelemetry-api | 1.42.1 |
| opentelemetry-proto | 1.42.1 | opentelemetry-sdk | 1.42.1 | opentelemetry-semantic-conventions | 0.63b1 |
| optuna | 3.6.1 | optuna-integration | 3.6.0 | orjson | 3.11.9 |
| ormsgpack | 1.12.2 | packaging | 25.0 | pandas | 2.3.3 |
| parso | 0.8.5 | especificación de ruta (pathspec) | 0.12.1 | patsy | 1.0.1 |
| pexpect | 4.9.0 | pillow | 12.0.0 | pip | 25,3 |
| platformdirs | 4.5.0 | pluggy | 1.5.0 | chucho | 1.9.0 |
| preshed | 3.0.13 | prometheus_client | 0.21.1 | prompt_toolkit | 3.0.52 |
| propcache | 0.3.1 | profeta | 1.2.1 | proto-plus | 1.28.0 |
| protobuf | 6.33.5 | psutil | 7.0.0 | ptyprocess | 0.7.0 |
| pure_eval | 0.2.3 | py-cpuinfo | 9.0.0 | py-spy | 0.4.2 |
| pyarrow | 21.0.0 | pyasn1 | 0.6.1 | pyasn1_modules | 0.4.2 |
| pyccolo | 0.0.83 | pycparser | 2.23 | pydantic (una biblioteca de validación de datos en Python) | 2.13.3 |
| pydantic_core | 2.46.3 | pyflakes | 3.2.0 | Pygments | 2.19.2 |
| PyGObject | 3.48.2 | pyiceberg | 0.11.1 | PyJWT | 2.10.1 |
| pyparsing | 3.2.5 | pyright | 1.1.409 | piroaring | 1.1.0 |
| pytesseract | 0.3.13 | pytest | 8.4.2 | Python-dateutil | 2.9.0.post0 |
| python-dotenv | 1.2.2 | editor de Python | 1.0.4 | pytokens | 0.2.0 |
| pytz | 2025.2 | PyYAML | 6.0.3 | pyzmq | 27.1.0 |
| Ray | 2.37.0 | Referencia | 0.37.0 | regex | 2025.9.1 |
| requests | 2.32.5 | requests-oauthlib | 2.0.0 | requests-toolbelt | 1.0.0 |
| rich | 14.2.0 | rpds-py | 0.28.0 | s3transfer | 0.14.0 |
| safetensors | 0.7.0 | scikit-image | 0.25.2 | scikit-learn | 1.7.2 |
| scipy | 1.16.3 | transformadores de frases | 5.5.1 | frase | 0.2.1 |
| setuptools | 80.9.0 | shap | 0.51.0 | Shellingham | 1.5.4 |
| seis | 1.17.0 | rebanador | 0.0.8 | smart_open | 7.6.1 |
| smmap | 5.0.0 | sniffio | 1.3.0 | archivo de sonido | 0.13.1 |
| soxr | 1.1.0 | spacy | 3.8.14 | spacy-legacy | 3.0.12 |
| spacy-loggers | 1.0.5 | SQLAlchemy | 2.0.43 | sqlparse | 0.5.5 |
| srsly | 2.5.3 | ssh-import-id | 5.11 | stack-data | 0.6.3 |
| estaño | 0.5.1 | starlette | 0.52.1 | statsmodels | 0.14.5 |
| strictyaml | 1.7.3 | Sintonía | 1.14.0 | tenacity | 9.1.2 |
| tensorboard | 2.20.0 | servidor-de-datos-de-tensorboard | 0.7.2 | tensorboardX | 2.6.5 |
| textual | 8.2.7 | thinc | 8.3.13 | threadpoolctl | 3.5.0 |
| Archivo TIFF | 2025.10.4 | tiktoken | 0.13.0 | tokenize_rt | 6.2.0 |
| tokenizadores | 0.22.1 | tomli | 2.0.1 | antorcha | 2.12.0+cpu |
| torcheval | 0.0.7 | torchvision | 0.27.0+cpu | tornado | 6.5.1 |
| tqdm | 4.67.1 | traitlets | 5.14.3 | transformadores | 4.57.6 |
| typeguard | 4.3.0 | typer | 0.25.1 | inspección de escritura | 0.9.0 |
| inspección de tipeo | 0.4.2 | typing_extensions | 4.15.0 | tzdata | 2026.2 |
| uc-micro-py | 1.0.3 | unattended-upgrades | 0,1 | urllib3 | 2.5.0 |
| uuid_utils | 0.16.0 | uvicorn | 0.47.0 | virtualenv | 20.35.4 |
| wadllib | 1.3.6 | wasabi | 1.1.3 | wcwidth | 0.2.13 |
| weasel | 1.0.0 | Werkzeug | 3.1.3 | wheel | 0.45.1 |
| cuando quiera | 0.7.3 | widgetsnbextension | 4.0.14 | wrapt | 1.17.0 |
| xgboost | 3.2.0 | xgboost-ray | 0.1.19 | xxhash | 3.5.0 |
| yarl | 1.22.0 | zipp | 3.23.0 | zstandard | 0.25.0 |
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 19 ML.
| Library | Versión | Library | Versión | Library | Versión |
|---|---|---|---|---|---|
| absl-py | 2.3.1 | acelerar | 1.13.0 | aiohappyeyeballs | 2.6.1 |
| aiohttp | 3.13.2 | aiohttp-cors | 0.8.1 | aiosignal | 1.4.0 |
| documento anotado | 0.0.4 | tipos con anotaciones | 0.7.0 | anyio | 4.10.0 |
| arro3-core | 0.8.0 | "asttokens" | 3.0.0 | astunparse | 1.6.3 |
| attrs | 25.4.0 | Audioread | 3.1.0 | autocommand | 2.2.2 |
| azure-core | 1.41.0 | azure-cosmos | 4.3.1 | azure-identity | 1.25.3 |
| azure-mgmt-core | 1.6.0 | azure-mgmt-web | 10.1.0 | azure-storage-blob | 12.29.0 |
| azure-storage-file-datalake (servicio para el almacenamiento de archivos en un lago de datos) | 12.24.0 | backports.tarfile | 1.2.0 | black | 25.9.0 |
| intermitente | 1.7.0 | felicidad | 1.3.3 | boto3 | 1.40.46 |
| botocore | 1.40.46 | cachetools | 5.5.1 | catálogo | 2.0.10 |
| certifi | 2025.11.12 | cffi | 2.0.0 | normalizador de conjuntos de caracteres | 3.4.4 |
| click | 8.2.1 | cloudpathlib | 0.24.0 | cloudpickle | 3.1.1 |
| cmdstanpy | 1.3.0 | colorido | 0.5.8 | colorlog | 6.10.1 |
| comm | 0.2.3 | confitería | 1.3.3 | contourpy | 1.3.3 |
| cryptography | 46.0.3 | vínculos de CUDA | 13.2.0 | cuda-pathfinder | 1.5.4 |
| cuda-toolkit | 13.0.2 | cycler | 0.11.0 | cymem | 2.0.13 |
| databricks-agents | 1.10.2 | databricks-feature-engineering | 0.13.0.1 | databricks-sdk (kit de desarrollo de software de Databricks) | 0.108.0 |
| dataclasses-json | 0.6.7 | datasets | 4.8.5 | dbl-tempo | 0.1.26 |
| dbus-python | 1.3.2 | debugpy | 1.8.16 | decorator | 5.2.1 |
| velocidad profunda | 0.19.0 | deltalake | 1.5.1 | Deprecated | 1.3.1 |
| dill | 0.4.0 | distlib | 0.4.0 | dm-tree | 0.1.10 |
| einops | 0.8.2 | evaluate | 0.4.6 | executing | 2.2.1 |
| Farama-Notifications | 0.0.6 | fastapi | 0.136.3 | filelock | 3.20.0 |
| flash_attn | 2.8.3 | Flask | 2.2.5 | fonttools | 4.60.1 |
| frozenlist | 1.8.0 | fsspec | 2023.5.0 | gitdb | 4.0.11 |
| GitPython | 3.1.45 | google-api-core | 2.30.3 | google-auth | 2.53.0 |
| google-cloud-core | 2.6.0 | google-cloud-storage | 3.10.1 | google-crc32c | 1.8.0 |
| google-resumable-media | 2.9.0 | googleapis-common-protos | 1.71.0 | graphql-core | 3.2.4 |
| greenlet | 3.2.4 | grpcio | 1.76.0 | grpcio-status | 1.76.0 |
| gimnasio | 0.28.1 | h11 | 0.16.0 | hf-xet | 1.5.0 |
| hjson | 3.1.0 | vacaciones | 0.54 | httpcore | 1.0.9 |
| httplib2 | 0.20.4 | httpx | 0.28.1 | huggingface_hub | 0.36.2 |
| idna | 3,11 | ImageIO | 2.37.2 | imbalanced-learn | 0.14.0 |
| importlib_metadata | 8.7.0 | importlib_resources | 7.1.0 | inflect | 7.3.1 |
| iniconfig | 2.1.0 | ipyflow-core | 0.0.227 | ipykernel | 6.31.0 |
| ipython | 9.7.0 | ipython_pygments_lexers | 1.1.1 | ipywidgets | 8.1.7 |
| isodate | 0.7.2 | Es peligroso | 2.2.0 | jaraco.collections | 5.1.0 |
| 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 | 3.1.6 |
| jiter | 0.15.0 | jmespath | 1.0.1 | joblib | 1.5.2 |
| joblibspark | 0.6.0 | jsonpatch | 1.33 | jsonpointer | 3.1.1 |
| jsonschema | 4.25.0 | jsonschema-specifications | 2025.9.1 | jupyter_client | 8.6.3 |
| jupyter_core | 5.8.1 | jupyterlab_widgets | 3.0.15 | kiwisolver | 1.4.8 |
| langchain | 1.3.1 | langchain-core | 1.4.0 | langchain-protocol | 0.0.15 |
| langgraph | 1.2.1 | langgraph-checkpoint | 4.1.1 | langgraph-prebuilt | 1.1.0 |
| langgraph-sdk | 0.3.15 | langsmith | 0.4.41 | launchpadlib | 1.11.0 |
| lazr.restfulclient | 0.14.6 | lazr.uri | 1.0.6 | lazy_loader | 0.4 |
| librosa | 0.11.0 | lightgbm | 4.6.0 | linkify-it-py | 2.0.3 |
| llvmlite | 0.45.1 | lz4 | 4.4.5 | Mako | 1.3.12 |
| marisa-trie | 1.2.0 | Markdown | 3.8 | markdown-it-py | 2.2.0 |
| MarkupSafe | 3.0.2 | malvavisco | 3.26.2 | matplotlib | 3.10.6 |
| matplotlib-inline | 0.2.1 | Mccabe | 0.7.0 | mdit-py-plugins | 0.5.0 |
| mdurl | 0.1.2 | memray | 1.19.3 | mlflow-skinny | 3.12.0 |
| mmh3 | 5.2.1 | more-itertools | 10.3.0 | mpmath | 1.3.0 |
| msal | 1.36.0 | msal-extensions | 1.3.1 | msgpack | 1.1.2 |
| msrest | 0.7.1 | Multidic | 6.7.0 | multiproceso | 0.70.18 |
| murmurhash | 1.0.15 | mypy-extensions | 1.0.0 | nest-asyncio | 1.6.0 |
| networkx | 3,5 | ninja | 1.13.0 | NLTK | 3.9.2 |
| nodeenv | 1.10.0 | numba | 0.62.1 | numpy | 2.3.4 |
| nvidia-cublas | 13.1.1.3 | nvidia-cuda-cupti | 13.0.85 | nvidia-cuda-nvrtc | 13.0.88 |
| nvidia-cuda-runtime | 13.0.96 | nvidia-cudnn-cu13 | 9.20.0.48 | nvidia-cufft | 12.0.0.61 |
| nvidia-cufile | 1.15.1.6 | nvidia-curand | 10.4.0.35 | nvidia-cusolver | 12.0.4.66 |
| nvidia-cusparse | 12.6.3.3 | nvidia-cusparselt-cu13 | 0.8.1 | nvidia-ml-py | 13.580.82 |
| nvidia-nccl-cu12 | 2.30.4 | nvidia-nccl-cu13 | 2.29.7 | nvidia-nvjitlink | 13.0.88 |
| nvidia-nvshmem-cu13 | 3.4.5 | nvidia-nvtx | 13.0.85 | oauthlib | 3.2.0 |
| openai | 2.37.0 | opencensus | 0.11.4 | opencensus-context==0.1.2 | 0.1.3 |
| opentelemetry-api | 1.42.1 | opentelemetry-proto | 1.42.1 | opentelemetry-sdk | 1.42.1 |
| opentelemetry-semantic-conventions | 0.63b1 | optuna | 3.6.1 | optuna-integration | 3.6.0 |
| orjson | 3.11.9 | ormsgpack | 1.12.2 | packaging | 25.0 |
| pandas | 2.3.3 | parso | 0.8.5 | especificación de ruta (pathspec) | 0.12.1 |
| patsy | 1.0.1 | pexpect | 4.9.0 | pillow | 12.0.0 |
| pip | 25,3 | platformdirs | 4.5.0 | pluggy | 1.5.0 |
| chucho | 1.9.0 | preshed | 3.0.13 | prometheus_client | 0.21.1 |
| prompt_toolkit | 3.0.52 | propcache | 0.3.1 | profeta | 1.2.1 |
| proto-plus | 1.28.0 | protobuf | 6.33.5 | psutil | 7.0.0 |
| ptyprocess | 0.7.0 | pure_eval | 0.2.3 | py-cpuinfo | 9.0.0 |
| py-spy | 0.4.2 | pyarrow | 21.0.0 | pyasn1 | 0.6.1 |
| pyasn1_modules | 0.4.2 | pyccolo | 0.0.83 | pycparser | 2.23 |
| pydantic (una biblioteca de validación de datos en Python) | 2.13.3 | pydantic_core | 2.46.3 | pyflakes | 3.2.0 |
| Pygments | 2.19.2 | PyGObject | 3.48.2 | pyiceberg | 0.11.1 |
| PyJWT | 2.10.1 | pyparsing | 3.2.5 | pyright | 1.1.409 |
| piroaring | 1.1.0 | pytesseract | 0.3.13 | pytest | 8.4.2 |
| Python-dateutil | 2.9.0.post0 | python-dotenv | 1.2.2 | editor de Python | 1.0.4 |
| pytokens | 0.2.0 | pytz | 2025.2 | PyYAML | 6.0.3 |
| pyzmq | 27.1.0 | Ray | 2.37.0 | Referencia | 0.37.0 |
| regex | 2025.9.1 | requests | 2.32.5 | requests-oauthlib | 2.0.0 |
| requests-toolbelt | 1.0.0 | rich | 14.2.0 | rpds-py | 0.28.0 |
| s3transfer | 0.14.0 | safetensors | 0.7.0 | scikit-image | 0.25.2 |
| scikit-learn | 1.7.2 | scipy | 1.16.3 | transformadores de frases | 5.5.1 |
| frase | 0.2.1 | setuptools | 80.9.0 | shap | 0.51.0 |
| Shellingham | 1.5.4 | seis | 1.17.0 | rebanador | 0.0.8 |
| smart_open | 7.6.1 | smmap | 5.0.0 | sniffio | 1.3.0 |
| archivo de sonido | 0.13.1 | soxr | 1.1.0 | spacy | 3.8.14 |
| spacy-legacy | 3.0.12 | spacy-loggers | 1.0.5 | SQLAlchemy | 2.0.43 |
| sqlparse | 0.5.5 | srsly | 2.5.3 | ssh-import-id | 5.11 |
| stack-data | 0.6.3 | estaño | 0.5.1 | starlette | 0.52.1 |
| statsmodels | 0.14.5 | strictyaml | 1.7.3 | Sintonía | 1.14.0 |
| tenacity | 9.1.2 | tensorboard | 2.20.0 | servidor-de-datos-de-tensorboard | 0.7.2 |
| tensorboardX | 2.6.5 | textual | 8.2.7 | thinc | 8.3.13 |
| threadpoolctl | 3.5.0 | Archivo TIFF | 2025.10.4 | tiktoken | 0.13.0 |
| tokenize_rt | 6.2.0 | tokenizadores | 0.22.1 | tomli | 2.0.1 |
| antorcha | 2.12.0 | torcheval | 0.0.7 | torchvision | 0.27.0 |
| tornado | 6.5.1 | tqdm | 4.67.1 | traitlets | 5.14.3 |
| transformadores | 4.57.6 | Tritón | 3.7.0 | typeguard | 4.3.0 |
| typer | 0.25.1 | inspección de escritura | 0.9.0 | inspección de tipeo | 0.4.2 |
| typing_extensions | 4.15.0 | tzdata | 2026.2 | uc-micro-py | 1.0.3 |
| unattended-upgrades | 0,1 | urllib3 | 2.5.0 | uuid_utils | 0.16.0 |
| uvicorn | 0.47.0 | virtualenv | 20.35.4 | wadllib | 1.3.6 |
| wasabi | 1.1.3 | wcwidth | 0.2.13 | weasel | 1.0.0 |
| Werkzeug | 3.1.3 | wheel | 0.45.1 | cuando quiera | 0.7.3 |
| widgetsnbextension | 4.0.14 | wrapt | 1.17.0 | xgboost | 3.2.0 |
| xgboost-ray | 0.1.19 | xxhash | 3.5.0 | yarl | 1.22.0 |
| zipp | 3.23.0 | zstandard | 0.25.0 |
Bibliotecas de R
Las bibliotecas de R son idénticas a las bibliotecas de R en Databricks Runtime 19.
Bibliotecas de Java y Scala (clúster de Scala 2.13)
Además de las bibliotecas de Java y Scala en Databricks Runtime 19, Databricks Runtime 19 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-gpu_2.13 | 2.1.3 |
| ml.dmlc | xgboost4j-gpu_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.