Amazon
Web Services
Microsoft Azure
Google Cloud PlatformDatabricks Runtime 13.0 for Machine Learning (unsupported)
Databricks Runtime 13.0 for Machine Learning provides a ready-to-go environment for machine learning and data science based on Databricks Runtime 13.0 (unsupported). 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 13.0 ML is built on top of Databricks Runtime 13.0. For information on what’s new in Databricks Runtime 13.0, including Apache Spark MLlib and SparkR, see the Databricks Runtime 13.0 (unsupported) release notes.
Changes to Databricks AutoML
In Databricks Runtime 13.0 ML and above, Databricks AutoML requires the E2 version of the Databricks platform.
For more information about Databricks AutoML, see What is AutoML?.
Enhancements to Databricks Feature Store
In Unity Catalog-enabled workspaces on a cluster running Databricks Runtime 13.0 ML or above, you can publish both workspace and Unity Catalog feature tables to Cosmos DB online stores.
For more information about Databricks Feature Store, see What is a feature store?.
System environment
The system environment in Databricks Runtime 13.0 ML differs from Databricks Runtime 13.0 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 11.7
cuDNN 8.5.0.96-1
NCCL 2.15.1
TensorRT 7.2.2
Databricks Runtime 13.0 ML includes XGBoost 1.7.2, which does not support GPU clusters with compute capability 5.2 and below.
The miniconda package has been removed from Databricks Runtime 13.0 ML.
Libraries
The following sections list the libraries included in Databricks Runtime 13.0 ML that differ from those included in Databricks Runtime 13.0.
In this section:
Top-tier libraries
Databricks Runtime 13.0 ML includes the following top-tier libraries:
Python libraries
Databricks Runtime 13.0 ML uses Virtualenv for Python package management and includes many popular ML packages.
The following Python libraries have been introduced with Databricks Runtime 13.0 ML:
accelerate
datasets
evaluate
ydata-profiling
In addition to the packages specified in the following sections, Databricks Runtime 13.0 ML also includes the following packages:
hyperopt 0.2.7+db3
sparkdl 3.0.0_db1
automl 1.17.0
To reproduce the Databricks Runtime ML Python environment in your local Python virtual environment, download the requirements-13.0.txt file and run pip install -r requirements-13.0.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 |
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 |
asttokens |
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 |
facets-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-loggers |
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 |
Python libraries on GPU clusters
Library |
Version |
Library |
Version |
Library |
Version |
|---|---|---|---|---|---|
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 |
asttokens |
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 |
facets-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-loggers |
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 |
R libraries
The R libraries are identical to the R Libraries in Databricks Runtime 13.0.
Java and Scala libraries (Scala 2.12 cluster)
In addition to Java and Scala libraries in Databricks Runtime 13.0, Databricks Runtime 13.0 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-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 |
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-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 |
