Databricks Runtime 13.0 per Machine Learning (EoS)
Nota
Il supporto per questa versione di Databricks Runtime è terminato. Per la data di fine del supporto, vedere Cronologia di fine del supporto. Per tutte le versioni supportate di Databricks Runtime, vedere Versioni e compatibilità delle note sulla versione di Databricks Runtime.
Databricks Runtime 13.0 per Machine Learning è un ambiente pronto all’uso ottimizzato per l'esecuzione di processi di apprendimento automatico e data science basato su Databricks Runtime 13.0 (EoS). Databricks Runtime ML contiene molte di queste popolari librerie per l’apprendimento automatico, tra cui TensorFlow, PyTorch e XGBoost. Databricks Runtime ML include AutoML, uno strumento per eseguire automaticamente il training delle pipeline di Machine Learning. Azure Databricks supporta il training di Deep Learning distribuito tramite HorovodRunner e il pacchetto .
Per altre informazioni, incluse le istruzioni per la creazione di un cluster di Machine Learning di Databricks Runtime, vedere Intelligenza artificiale e Machine Learning in Databricks.
Miglioramenti e nuove funzionalità
Databricks Runtime 13.0 ML è basato su Databricks Runtime 13.0. Per informazioni sulle novità di Databricks Runtime 13.0, tra cui Apache Spark MLlib e SparkR, vedere le note sulla versione di Databricks Runtime 13.0 (EoS).
Modifiche a AutoML
In Databricks Runtime 13.0 ML e versioni successive AutoML non è supportato per le aree di lavoro con conformità FedRAMP .
Per altre informazioni su AutoML, vedere Che cos'è AutoML?.
Miglioramenti a Databricks Feature Store
Nelle aree di lavoro abilitate per Unity Catalog in un cluster che esegue Databricks Runtime 13.0 ML o versione successiva, è possibile pubblicare tabelle delle funzionalità sia dell'area di lavoro che di Unity Catalog negli archivi online di Cosmos DB.
Per altre informazioni sull'archivio funzionalità di Databricks, vedere Progettazione e servizio delle funzionalità.
Ambiente di sistema
L'ambiente di sistema in Databricks Runtime 13.0 ML differisce da Databricks Runtime 13.0 come indicato di seguito:
- DBUtils: Databricks Runtime ML non include l'utilità libreria (dbutils.library) (legacy).
Usare
%pipinvece i comandi. Vedere Librerie Python con ambito notebook. - Per i cluster GPU, Databricks Runtime ML include le librerie GPU NVIDIA seguenti:
- CUDA 11.7
- cuDNN 8.5.0.96-1
- NCCL 2.15.1
- TensorRT 7.2.2
Databricks Runtime 13.0 ML include XGBoost 1.7.2, che non supporta cluster GPU con capacità di calcolo 5.2 e versioni precedenti.
Il pacchetto miniconda è stato rimosso da Databricks Runtime 13.0 ML.
Librerie
Le sezioni seguenti elencano le librerie incluse in Databricks Runtime 13.0 ML che differiscono da quelle incluse in Databricks Runtime 13.0.
Contenuto della sezione:
Librerie di livello superiore
Databricks Runtime 13.0 ML include le librerie di livello superiore seguenti:
- GraphFrames
- Horovod e HorovodRunner
- MLflow
- PyTorch
- spark-tensorflow-connector
- TensorFlow
- TensorBoard
- Scikit-learn
Librerie Python
Databricks Runtime 13.0 ML usa Virtualenv per la gestione dei pacchetti Python e include molti dei pacchetti ML più diffusi.
Sono state introdotte le librerie Python seguenti con Databricks Runtime 13.0 ML:
- accelerate
- datasets
- evaluate
- ydata-profiling
Oltre ai pacchetti specificati nelle sezioni seguenti, Databricks Runtime 13.0 ML include anche i pacchetti seguenti:
- hyperopt 0.2.7+db3
- sparkdl 3.0.0_db1
- automl 1.17.0
Per riprodurre l'ambiente Python di Databricks Runtime ML nell'ambiente virtuale Python locale, scaricare il file requirements-13.0.txt ed eseguire pip install -r requirements-13.0.txt. Questo comando installa tutte le librerie open source usate da Databricks Runtime ML, ma non installa librerie sviluppate da Databricks, ad esempio databricks-automl, databricks-feature-store o la creazione di copia tramite fork di Databricks di hyperopt.
Librerie Python nei cluster CPU
| Library | Versione | Library | Versione | Library | Versione |
|---|---|---|---|---|---|
| absl-py | 1.0.0 | accelerate | 0.16.0 | aiohttp | 3.8.4 |
| aiosignal | 1.3.1 | appdirs | 1.4.4 | argon2-cffi | 21.3.0 |
| argon2-cffi-bindings | 21.2.0 | astor | 0.8.1 | asttoken | 2.2.1 |
| astunparse | 1.6.3 | async-timeout | 4.0.2 | attrs | 21.4.0 |
| azure-core | 1.26.3 | azure-cosmos | 4.3.1b1 | backcall | 0.2.0 |
| bcrypt | 3.2.0 | beautifulsoup4 | 4.11.1 | black | 22.6.0 |
| bleach | 4.1.0 | blinker | 1.4 | blis | 0.7.9 |
| boto3 | 1.24.28 | botocore | 1.27.28 | cachetools | 4.2.4 |
| catalogue | 2.0.8 | category-encoders | 2.6.0 | certifi | 2022.9.14 |
| cffi | 1.15.1 | chardet | 4.0.0 | charset-normalizer | 2.0.4 |
| click | 8.0.4 | cloudpickle | 2.0.0 | cmdstanpy | 1.1.0 |
| confection | 0.0.4 | configparser | 5.2.0 | convertdate | 2.4.0 |
| cryptography | 37.0.1 | cycler | 0.11.0 | cymem | 2.0.7 |
| Cython | 0.29.32 | databricks-automl-runtime | 0.2.16 | databricks-cli | 0.17.4 |
| databricks-feature-store | 0.11.0 | datasets | 2.10.0 | dbl-tempo | 0.1.12 |
| dbus-python | 1.2.18 | 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 | evaluate | 0.4.0 | executing | 1.2.0 |
| facet-overview | 1.0.2 | fastjsonschema | 2.16.3 | fasttext | 0.9.2 |
| filelock | 3.6.0 | Flask | 1.1.2 | flatbuffers | 23.3.3 |
| fonttools | 4.25.0 | frozenlist | 1.3.3 | fsspec | 2022.7.1 |
| 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 | googleapis-common-protos | 1.56.4 | grpcio | 1.48.1 |
| grpcio-status | 1.48.1 | gunicorn | 20.1.0 | gviz-api | 1.10.0 |
| h5py | 3.7.0 | hijri-converter | 2.2.4 | holidays | 0.19 |
| horovod | 0.27.0 | htmlmin | 0.1.12 | httplib2 | 0.20.2 |
| huggingface-hub | 0.13.2 | idna | 3.3 | ImageHash | 4.3.1 |
| imbalanced-learn | 0.8.1 | importlib-metadata | 4.11.3 | ipykernel | 6.17.1 |
| ipython | 8.10.0 | ipython-genutils | 0.2.0 | ipywidgets | 7.7.2 |
| isodate | 0.6.1 | itsdangerous | 2.0.1 | jedi | 0.18.1 |
| jeepney | 0.7.1 | Jinja2 | 2.11.3 | jmespath | 0.10.0 |
| joblib | 1.2.0 | joblibspark | 0.5.1 | jsonschema | 4.16.0 |
| jupyter-client | 7.3.4 | jupyter_core | 4.11.2 | jupyterlab-pygments | 0.1.2 |
| jupyterlab-widgets | 1.0.0 | keras | 2.11.0 | keyring | 23.5.0 |
| kiwisolver | 1.4.2 | korean-lunar-calendar | 0.3.1 | langcodes | 3.3.0 |
| launchpadlib | 1.10.16 | lazr.restfulclient | 0.14.4 | lazr.uri | 1.0.6 |
| libclang | 15.0.6.1 | lightgbm | 3.3.5 | llvmlite | 0.38.0 |
| LunarCalendar | 0.0.9 | Mako | 1.2.0 | Markdown | 3.3.4 |
| MarkupSafe | 2.0.1 | matplotlib | 3.5.2 | matplotlib-inline | 0.1.6 |
| mccabe | 0.7.0 | mistune | 0.8.4 | mleap | 0.20.0 |
| mlflow-skinny | 2.2.1 | more-itertools | 8.10.0 | multidict | 6.0.4 |
| multimethod | 1.9.1 | multiprocess | 0.70.12.2 | murmurhash | 1.0.9 |
| mypy-extensions | 0.4.3 | nbclient | 0.5.13 | nbconvert | 6.4.4 |
| nbformat | 5.5.0 | nest-asyncio | 1.5.5 | networkx | 2.8.4 |
| nltk | 3.7 | nodeenv | 1.7.0 | notebook | 6.4.12 |
| numba | 0.55.1 | numpy | 1.21.5 | oauthlib | 3.2.0 |
| opt-einsum | 3.3.0 | packaging | 21.3 | pandas | 1.4.4 |
| pandas-profiling | 3.6.6 | pandocfilters | 1.5.0 | paramiko | 2.9.2 |
| parso | 0.8.3 | pathspec | 0.9.0 | pathy | 0.10.1 |
| patsy | 0.5.2 | petastorm | 0.12.1 | pexpect | 4.8.0 |
| phik | 0.12.3 | pickleshare | 0.7.5 | Pillow | 9.2.0 |
| pip | 22.2.2 | platformdirs | 2.5.2 | plotly | 5.9.0 |
| pluggy | 1.0.0 | pmdarima | 2.0.2 | preshed | 3.0.8 |
| prometheus-client | 0.14.1 | prompt-toolkit | 3.0.36 | prophet | 1.1.2 |
| protobuf | 3.19.4 | psutil | 5.9.0 | 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 | 2.10.3 |
| pycparser | 2.21 | pydantic | 1.10.6 | pyflakes | 3.0.1 |
| Pygments | 2.11.2 | PyGObject | 3.42.1 | PyJWT | 2.3.0 |
| PyMeeus | 0.5.12 | PyNaCl | 1.5.0 | pyodbc | 4.0.32 |
| pyparsing | 3.0.9 | pyright | 1.1.294 | pyrsistent | 0.18.0 |
| python-dateutil | 2.8.2 | python-editor | 1.0.4 | python-lsp-jsonrpc | 1.0.0 |
| python-lsp-server | 1.7.1 | pytoolconfig | 1.2.2 | pytz | 2022.1 |
| PyWavelets | 1.3.0 | PyYAML | 6.0 | pyzmq | 23.2.0 |
| regex | 2022.7.9 | requests | 2.28.1 | requests-oauthlib | 1.3.1 |
| responses | 0.18.0 | rope | 1.7.0 | rsa | 4.9 |
| s3transfer | 0.6.0 | scikit-learn | 1.1.1 | scipy | 1.9.1 |
| seaborn | 0.11.2 | SecretStorage | 3.3.1 | Send2Trash | 1.8.0 |
| setuptools | 63.4.1 | shap | 0.41.0 | simplejson | 3.17.6 |
| six | 1.16.0 | slicer | 0.0.7 | smart-open | 5.2.1 |
| smmap | 5.0.0 | soupsieve | 2.3.1 | spacy | 3.5.0 |
| spacy-legacy | 3.0.12 | spacy-logger | 1.0.4 | spark-tensorflow-distributor | 1.0.0 |
| sqlparse | 0.4.2 | srsly | 2.4.6 | ssh-import-id | 5.11 |
| stack-data | 0.6.2 | statsmodels | 0.13.2 | tabulate | 0.8.10 |
| tangled-up-in-unicode | 0.2.0 | tenacity | 8.0.1 | tensorboard | 2.11.0 |
| tensorboard-data-server | 0.6.1 | tensorboard-plugin-profile | 2.11.1 | tensorboard-plugin-wit | 1.8.1 |
| tensorflow-cpu | 2.11.0 | tensorflow-estimator | 2.11.0 | tensorflow-io-gcs-filesystem | 0.31.0 |
| termcolor | 2.2.0 | terminado | 0.13.1 | testpath | 0.6.0 |
| thinc | 8.1.9 | threadpoolctl | 2.2.0 | tokenize-rt | 4.2.1 |
| tokenizers | 0.13.2 | tomli | 2.0.1 | torch | 1.13.1+cpu |
| torchvision | 0.14.1+cpu | tornado | 6.1 | tqdm | 4.64.1 |
| traitlets | 5.1.1 | transformers | 4.26.1 | typeguard | 2.13.3 |
| typer | 0.7.0 | typing_extensions | 4.3.0 | ujson | 5.4.0 |
| unattended-upgrades | 0.1 | urllib3 | 1.26.11 | virtualenv | 20.16.3 |
| visions | 0.7.5 | wadllib | 1.3.6 | wasabi | 1.1.1 |
| wcwidth | 0.2.5 | webencodings | 0.5.1 | websocket-client | 0.58.0 |
| Werkzeug | 2.0.3 | whatthepatch | 1.0.2 | wheel | 0.37.1 |
| widgetsnbextension | 3.6.1 | wrapt | 1.14.1 | xgboost | 1.7.4 |
| xxhash | 3.2.0 | yapf | 0.31.0 | yarl | 1.8.2 |
| ydata-profiling | 4.1.0 | zipp | 3.8.0 |
Librerie Python nei cluster GPU
| Library | Versione | Library | Versione | Library | Versione |
|---|---|---|---|---|---|
| absl-py | 1.0.0 | accelerate | 0.16.0 | aiohttp | 3.8.4 |
| aiosignal | 1.3.1 | appdirs | 1.4.4 | argon2-cffi | 21.3.0 |
| argon2-cffi-bindings | 21.2.0 | astor | 0.8.1 | asttoken | 2.2.1 |
| astunparse | 1.6.3 | async-timeout | 4.0.2 | attrs | 21.4.0 |
| azure-core | 1.26.3 | azure-cosmos | 4.3.1b1 | backcall | 0.2.0 |
| bcrypt | 3.2.0 | beautifulsoup4 | 4.11.1 | black | 22.6.0 |
| bleach | 4.1.0 | blinker | 1.4 | blis | 0.7.9 |
| boto3 | 1.24.28 | botocore | 1.27.28 | cachetools | 4.2.4 |
| catalogue | 2.0.8 | category-encoders | 2.6.0 | certifi | 2022.9.14 |
| cffi | 1.15.1 | chardet | 4.0.0 | charset-normalizer | 2.0.4 |
| click | 8.0.4 | cloudpickle | 2.0.0 | cmdstanpy | 1.1.0 |
| confection | 0.0.4 | configparser | 5.2.0 | convertdate | 2.4.0 |
| cryptography | 37.0.1 | cycler | 0.11.0 | cymem | 2.0.7 |
| Cython | 0.29.32 | databricks-automl-runtime | 0.2.16 | databricks-cli | 0.17.4 |
| databricks-feature-store | 0.11.0 | datasets | 2.10.0 | dbl-tempo | 0.1.12 |
| dbus-python | 1.2.18 | 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 | evaluate | 0.4.0 | executing | 1.2.0 |
| facet-overview | 1.0.2 | fastjsonschema | 2.16.3 | fasttext | 0.9.2 |
| filelock | 3.6.0 | Flask | 1.1.2 | flatbuffers | 23.3.3 |
| fonttools | 4.25.0 | frozenlist | 1.3.3 | fsspec | 2022.7.1 |
| 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 | googleapis-common-protos | 1.56.4 | grpcio | 1.48.1 |
| grpcio-status | 1.48.1 | gunicorn | 20.1.0 | gviz-api | 1.10.0 |
| h5py | 3.7.0 | hijri-converter | 2.2.4 | holidays | 0.19 |
| horovod | 0.27.0 | htmlmin | 0.1.12 | httplib2 | 0.20.2 |
| huggingface-hub | 0.13.1 | idna | 3.3 | ImageHash | 4.3.1 |
| imbalanced-learn | 0.8.1 | importlib-metadata | 4.11.3 | ipykernel | 6.17.1 |
| ipython | 8.10.0 | ipython-genutils | 0.2.0 | ipywidgets | 7.7.2 |
| isodate | 0.6.1 | itsdangerous | 2.0.1 | jedi | 0.18.1 |
| jeepney | 0.7.1 | Jinja2 | 2.11.3 | jmespath | 0.10.0 |
| joblib | 1.2.0 | joblibspark | 0.5.1 | jsonschema | 4.16.0 |
| jupyter-client | 7.3.4 | jupyter_core | 4.11.2 | jupyterlab-pygments | 0.1.2 |
| jupyterlab-widgets | 1.0.0 | keras | 2.11.0 | keyring | 23.5.0 |
| kiwisolver | 1.4.2 | korean-lunar-calendar | 0.3.1 | langcodes | 3.3.0 |
| launchpadlib | 1.10.16 | lazr.restfulclient | 0.14.4 | lazr.uri | 1.0.6 |
| libclang | 15.0.6.1 | lightgbm | 3.3.5 | llvmlite | 0.38.0 |
| LunarCalendar | 0.0.9 | Mako | 1.2.0 | Markdown | 3.3.4 |
| MarkupSafe | 2.0.1 | matplotlib | 3.5.2 | matplotlib-inline | 0.1.6 |
| mccabe | 0.7.0 | mistune | 0.8.4 | mleap | 0.20.0 |
| mlflow-skinny | 2.2.1 | more-itertools | 8.10.0 | multidict | 6.0.4 |
| multimethod | 1.9.1 | multiprocess | 0.70.12.2 | murmurhash | 1.0.9 |
| mypy-extensions | 0.4.3 | nbclient | 0.5.13 | nbconvert | 6.4.4 |
| nbformat | 5.5.0 | nest-asyncio | 1.5.5 | networkx | 2.8.4 |
| nltk | 3.7 | nodeenv | 1.7.0 | notebook | 6.4.12 |
| numba | 0.55.1 | numpy | 1.21.5 | oauthlib | 3.2.0 |
| opt-einsum | 3.3.0 | packaging | 21.3 | pandas | 1.4.4 |
| pandas-profiling | 3.6.6 | pandocfilters | 1.5.0 | paramiko | 2.9.2 |
| parso | 0.8.3 | pathspec | 0.9.0 | pathy | 0.10.1 |
| patsy | 0.5.2 | petastorm | 0.12.1 | pexpect | 4.8.0 |
| phik | 0.12.3 | pickleshare | 0.7.5 | Pillow | 9.2.0 |
| pip | 22.2.2 | platformdirs | 2.5.2 | plotly | 5.9.0 |
| pluggy | 1.0.0 | pmdarima | 2.0.2 | preshed | 3.0.8 |
| prompt-toolkit | 3.0.36 | prophet | 1.1.2 | protobuf | 3.19.4 |
| psutil | 5.9.0 | 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 | 2.10.3 | pycparser | 2.21 |
| pydantic | 1.10.6 | pyflakes | 3.0.1 | Pygments | 2.11.2 |
| PyGObject | 3.42.1 | PyJWT | 2.3.0 | PyMeeus | 0.5.12 |
| PyNaCl | 1.5.0 | pyodbc | 4.0.32 | pyparsing | 3.0.9 |
| pyright | 1.1.294 | pyrsistent | 0.18.0 | python-dateutil | 2.8.2 |
| python-editor | 1.0.4 | python-lsp-jsonrpc | 1.0.0 | python-lsp-server | 1.7.1 |
| pytoolconfig | 1.2.2 | pytz | 2022.1 | PyWavelets | 1.3.0 |
| PyYAML | 6.0 | pyzmq | 23.2.0 | regex | 2022.7.9 |
| requests | 2.28.1 | requests-oauthlib | 1.3.1 | responses | 0.18.0 |
| rope | 1.7.0 | rsa | 4.9 | s3transfer | 0.6.0 |
| scikit-learn | 1.1.1 | scipy | 1.9.1 | seaborn | 0.11.2 |
| SecretStorage | 3.3.1 | Send2Trash | 1.8.0 | setuptools | 63.4.1 |
| shap | 0.41.0 | simplejson | 3.17.6 | six | 1.16.0 |
| slicer | 0.0.7 | smart-open | 5.2.1 | smmap | 5.0.0 |
| soupsieve | 2.3.1 | spacy | 3.5.0 | spacy-legacy | 3.0.12 |
| spacy-logger | 1.0.4 | spark-tensorflow-distributor | 1.0.0 | sqlparse | 0.4.2 |
| srsly | 2.4.6 | ssh-import-id | 5.11 | stack-data | 0.6.2 |
| statsmodels | 0.13.2 | tabulate | 0.8.10 | tangled-up-in-unicode | 0.2.0 |
| tenacity | 8.0.1 | tensorboard | 2.11.0 | tensorboard-data-server | 0.6.1 |
| tensorboard-plugin-profile | 2.11.1 | tensorboard-plugin-wit | 1.8.1 | tensorflow | 2.11.0 |
| tensorflow-estimator | 2.11.0 | tensorflow-io-gcs-filesystem | 0.31.0 | termcolor | 2.2.0 |
| terminado | 0.13.1 | testpath | 0.6.0 | thinc | 8.1.9 |
| threadpoolctl | 2.2.0 | tokenize-rt | 4.2.1 | tokenizers | 0.13.2 |
| tomli | 2.0.1 | torch | 1.13.1+cu117 | torchvision | 0.14.1+cu117 |
| tornado | 6.1 | tqdm | 4.64.1 | traitlets | 5.1.1 |
| transformers | 4.26.1 | typeguard | 2.13.3 | typer | 0.7.0 |
| typing_extensions | 4.3.0 | ujson | 5.4.0 | unattended-upgrades | 0.1 |
| urllib3 | 1.26.11 | virtualenv | 20.16.3 | visions | 0.7.5 |
| wadllib | 1.3.6 | wasabi | 1.1.1 | wcwidth | 0.2.5 |
| webencodings | 0.5.1 | websocket-client | 0.58.0 | Werkzeug | 2.0.3 |
| whatthepatch | 1.0.2 | wheel | 0.37.1 | widgetsnbextension | 3.6.1 |
| wrapt | 1.14.1 | xgboost | 1.7.4 | xxhash | 3.2.0 |
| yapf | 0.31.0 | yarl | 1.8.2 | ydata-profiling | 4.1.0 |
| zipp | 3.8.0 |
Librerie R
Le librerie R sono identiche alle librerie R in Databricks Runtime 13.0.
Librerie Java e Scala (cluster Scala 2.12)
Oltre alle librerie Java e Scala in Databricks Runtime 13.0, Databricks Runtime 13.0 ML contiene i file JAR seguenti:
Cluster CPU
| ID gruppo | ID artefatto | Versione |
|---|---|---|
| com.typesafe.akka | akka-actor_2.12 | 2.5.23 |
| ml.combust.mleap | mleap-databricks-runtime_2.12 | v0.20.0-db2 |
| ml.dmlc | xgboost4j-spark_2.12 | 1.7.3 |
| ml.dmlc | xgboost4j_2.12 | 1.7.3 |
| org.graphframes | graphframes_2.12 | 0.8.2-db1-spark3.2 |
| org.mlflow | mlflow-client | 2.2.1 |
| org.scala-lang.modules | scala-java8-compat_2.12 | 0.8.0 |
| org.tensorflow | spark-tensorflow-connector_2.12 | 1.15.0 |
Cluster GPU
| ID gruppo | ID artefatto | Versione |
|---|---|---|
| com.typesafe.akka | akka-actor_2.12 | 2.5.23 |
| ml.combust.mleap | mleap-databricks-runtime_2.12 | v0.20.0-db2 |
| ml.dmlc | xgboost4j-gpu_2.12 | 1.7.3 |
| ml.dmlc | xgboost4j-spark-gpu_2.12 | 1.7.3 |
| org.graphframes | graphframes_2.12 | 0.8.2-db1-spark3.2 |
| org.mlflow | mlflow-client | 2.2.1 |
| org.scala-lang.modules | scala-java8-compat_2.12 | 0.8.0 |
| org.tensorflow | spark-tensorflow-connector_2.12 | 1.15.0 |