Databricks Runtime 12.0 for Machine Learning (EoS)
Note
Support for this Databricks Runtime version has ended. For the end-of-support date, see End-of-support history. For all supported Databricks Runtime versions, see Databricks Runtime release notes versions and compatibility.
Databricks Runtime 12.0 for Machine Learning provides a ready-to-go environment for machine learning and data science based on Databricks Runtime 12.0 (EoS). Databricks Runtime ML contains many popular machine learning libraries, including TensorFlow, PyTorch, and XGBoost. Databricks Runtime ML includes AutoML, a tool to automatically train machine learning pipelines. Databricks Runtime ML also supports distributed deep learning training using Horovod.
For more information, including instructions for creating a Databricks Runtime ML cluster, see AI and machine learning on Databricks.
New features and improvements
Databricks Runtime 12.0 ML is built on top of Databricks Runtime 12.0. For information on what’s new in Databricks Runtime 12.0, including Apache Spark MLlib and SparkR, see the Databricks Runtime 12.0 (EoS) release notes.
Enhancements to AutoML
- Forecasting models can now optionally include country holidays.
- Forecasting now supports monthly, quarterly, and annual frequencies.
- AutoML can now use larger datasets for training. AutoML automatically allocates more CPU cores for large datasets.
For more information about AutoML, see What is AutoML?.
MLflow 2.0
Databricks Runtime 12.0 ML includes MLflow 2.0. MLflow 2.0 builds upon MLflow’s strong platform foundation and incorporates extensive user feedback to simplify data science workflows and deliver innovative, first-class tools for MLOps. Features and improvements include extensions to MLflow Recipes (formerly MLflow Pipelines) such as AutoML, hyperparameter tuning, and classification support, as well modernized integrations with the ML ecosystem, a streamlined MLflow Tracking UI, a refresh of core APIs across MLflow’s platform components, and more. For more information, see the MLflow 2.0 documentation or check out the blog post.
scikit-learn 1.0
Databricks Runtime ML 12.0 includes scikit-learn version 1.0. Visit the scikit-learn documentation to learn about changes with this scikit-learn release.
System environment
The system environment in Databricks Runtime 12.0 ML differs from Databricks Runtime 12.0 as follows:
- DBUtils: Databricks Runtime ML does not include Library utility (dbutils.library) (legacy).
Use
%pipcommands instead. See Notebook-scoped Python libraries. - For GPU clusters, Databricks Runtime ML includes the following NVIDIA GPU libraries:
- CUDA 11.3
- cuDNN 8.0.5.39
- NCCL 2.9.9
- TensorRT 7.2.2
Databricks Runtime 12.0 ML includes XGBoost 1.6.2, which does not support GPU clusters with compute capability 5.2 and below.
Libraries
The following sections list the libraries included in Databricks Runtime 12.0 ML that differ from those included in Databricks Runtime 12.0.
In this section:
Top-tier libraries
Databricks Runtime 12.0 ML includes the following top-tier libraries:
- GraphFrames
- Horovod and HorovodRunner
- MLflow
- PyTorch
- spark-tensorflow-connector
- TensorFlow
- TensorBoard
- Scikit-learn
Python libraries
Databricks Runtime 12.0 ML uses Virtualenv for Python package management and includes many popular ML packages.
In addition to the packages specified in the following sections, Databricks Runtime 12.0 ML also includes the following packages:
- hyperopt 0.2.7.db1
- sparkdl 2.3.0-db3
- automl 1.14.1
To reproduce the Databricks Runtime ML Python environment in your local Python virtual environment, download the requirements-12.0.txt file and run pip install -r requirements-12.0.txt. This command installs all of the open source libraries that Databricks Runtime ML uses, but does not install libraries developed by Databricks, such as databricks-automl, databricks-feature-store, or the Databricks fork of hyperopt.
Python libraries on CPU clusters
| Library | Version | Library | Version | Library | Version |
|---|---|---|---|---|---|
| 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 | cryptography | 3.4.8 | cycler | 0.11.0 |
| cymem | 2.0.7 | Cython | 0.29.28 | databricks-automl-runtime | 0.2.13 |
| databricks-cli | 0.17.3 | databricks-feature-store | 0.8.0 | 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 | entrypoints | 0.4 | ephem | 4.1.3 |
| 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 | 22.10.26 | fonttools | 4.25.0 | fsspec | 2022.2.0 |
| future | 0.18.2 | gast | 0.4.0 | gitdb | 4.0.9 |
| 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 | 0.16 | horovod | 0.25.0 | htmlmin | 0.1.12 |
| huggingface-hub | 0.11.0 | 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 | missingno | 0.5.1 |
| mistune | 0.8.4 | mleap | 0.20.0 | mlflow-skinny | 2.0.1 |
| multimethod | 1.8 | 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 |
| notebook | 6.4.8 | numba | 0.55.1 | numpy | 1.21.5 |
| oauthlib | 3.2.0 | opt-einsum | 3.3.0 | packaging | 21.3 |
| pandas | 1.4.2 | pandas-profiling | 3.3.0 | 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 | 0.11.4 |
| pexpect | 4.8.0 | phik | 0.12.2 | pickleshare | 0.7.5 |
| Pillow | 9.0.1 | pip | 21.2.4 | platformdirs | 2.5.4 |
| plotly | 5.6.0 | pmdarima | 2.0.1 | 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 | 1.9.2 | Pygments | 2.11.2 |
| PyGObject | 3.36.0 | PyJWT | 2.6.0 | PyMeeus | 0.5.11 |
| PyNaCl | 1.5.0 | pyodbc | 4.0.32 | pyparsing | 3.0.4 |
| pyrsistent | 0.18.0 | python-dateutil | 2.8.2 | python-editor | 1.0.4 |
| pytz | 2021.3 | PyWavelets | 1.3.0 | PyYAML | 6.0 |
| pyzmq | 22.3.0 | regex | 2022.3.15 | requests | 2.27.1 |
| requests-oauthlib | 1.3.1 | requests-unixsocket | 0.2.0 | 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 | 1.16.0 | slicer | 0.0.7 | smart-open | 5.1.0 |
| smmap | 5.0.0 | soupsieve | 2.3.1 | spacy | 3.4.1 |
| spacy-legacy | 3.0.10 | spacy-loggers | 1.0.3 | 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 | 0.28.0 |
| termcolor | 2.1.1 | terminado | 0.13.1 | testpath | 0.5.0 |
| thinc | 8.1.5 | threadpoolctl | 2.2.0 | tokenize-rt | 4.2.1 |
| tokenizers | 0.13.2 | tomli | 1.2.2 | torch | 1.12.1+cpu |
| torchvision | 0.13.1+cpu | tornado | 6.1 | tqdm | 4.64.0 |
| traitlets | 5.1.1 | transformers | 4.23.1 | typer | 0.4.2 |
| typing_extensions | 4.1.1 | 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 | wheel | 0.37.1 | widgetsnbextension | 3.6.1 |
| wrapt | 1.12.1 | zipp | 3.7.0 |
Python libraries on GPU clusters
| Library | Version | Library | Version | Library | Version |
|---|---|---|---|---|---|
| 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 | cryptography | 3.4.8 | cycler | 0.11.0 |
| cymem | 2.0.7 | Cython | 0.29.28 | databricks-automl-runtime | 0.2.13 |
| databricks-cli | 0.17.3 | databricks-feature-store | 0.8.0 | 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 | entrypoints | 0.4 | ephem | 4.1.3 |
| 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 | 22.10.26 | fonttools | 4.25.0 | fsspec | 2022.2.0 |
| future | 0.18.2 | gast | 0.4.0 | gitdb | 4.0.9 |
| 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 | 0.16 | horovod | 0.25.0 | htmlmin | 0.1.12 |
| huggingface-hub | 0.11.0 | 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 | missingno | 0.5.1 |
| mistune | 0.8.4 | mleap | 0.20.0 | mlflow-skinny | 2.0.1 |
| multimethod | 1.8 | 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 |
| notebook | 6.4.8 | numba | 0.55.1 | numpy | 1.21.5 |
| oauthlib | 3.2.0 | opt-einsum | 3.3.0 | packaging | 21.3 |
| pandas | 1.4.2 | pandas-profiling | 3.3.0 | 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 | 0.11.4 |
| pexpect | 4.8.0 | phik | 0.12.2 | pickleshare | 0.7.5 |
| Pillow | 9.0.1 | pip | 21.2.4 | platformdirs | 2.5.4 |
| plotly | 5.6.0 | pmdarima | 2.0.1 | 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 | 1.9.2 | Pygments | 2.11.2 | PyGObject | 3.36.0 |
| PyJWT | 2.6.0 | PyMeeus | 0.5.11 | PyNaCl | 1.5.0 |
| pyodbc | 4.0.32 | pyparsing | 3.0.4 | pyrsistent | 0.18.0 |
| python-dateutil | 2.8.2 | python-editor | 1.0.4 | pytz | 2021.3 |
| PyWavelets | 1.3.0 | PyYAML | 6.0 | pyzmq | 22.3.0 |
| regex | 2022.3.15 | requests | 2.27.1 | requests-oauthlib | 1.3.1 |
| requests-unixsocket | 0.2.0 | 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 | 1.16.0 |
| slicer | 0.0.7 | smart-open | 5.1.0 | smmap | 5.0.0 |
| soupsieve | 2.3.1 | spacy | 3.4.1 | spacy-legacy | 3.0.10 |
| spacy-loggers | 1.0.3 | 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 | 0.28.0 | termcolor | 2.1.1 |
| terminado | 0.13.1 | testpath | 0.5.0 | thinc | 8.1.5 |
| threadpoolctl | 2.2.0 | tokenize-rt | 4.2.1 | tokenizers | 0.13.2 |
| tomli | 1.2.2 | torch | 1.12.1+cu113 | torchvision | 0.13.1+cu113 |
| tornado | 6.1 | tqdm | 4.64.0 | traitlets | 5.1.1 |
| transformers | 4.23.1 | typer | 0.4.2 | typing_extensions | 4.1.1 |
| 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 |
| wheel | 0.37.1 | widgetsnbextension | 3.6.1 | wrapt | 1.12.1 |
| zipp | 3.7.0 |
R libraries
The R libraries are identical to the R Libraries in Databricks Runtime 12.0.
Java and Scala libraries (Scala 2.12 cluster)
In addition to Java and Scala libraries in Databricks Runtime 12.0, Databricks Runtime 12.0 ML contains the following JARs:
CPU clusters
| Group ID | Artifact ID | Version |
|---|---|---|
| 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 |
GPU clusters
| Group ID | Artifact ID | Version |
|---|---|---|
| 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 |