Databricks Runtime 10.5 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 10.5 for Machine Learning provides a ready-to-go environment for machine learning and data science based on Databricks Runtime 10.5 (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 10.5 ML is built on top of Databricks Runtime 10.5. For information on what’s new in Databricks Runtime 10.5, including Apache Spark MLlib and SparkR, see the Databricks Runtime 10.5 (EoS) release notes.
Enhancements to AutoML
The following enhancements have been made to AutoML.
Improved memory usage allows AutoML to train on larger datasets.
With AutoML forecasting, you can now export the best model’s predictions to a table using the API. If
output_database
is provided, AutoML saves predictions of the best model to a new table in the specified database. The predictions are not saved ifoutput_database
is not specified.
Enhancements to Databricks Feature Store
The following enhancements have been made to Databricks Feature Store.
You can now delete an existing feature table with the
drop_table
API. This action also drops the underlying Delta table.You can now use the Feature Engineering and Workspace Feature Store Python API to add a tag to a feature table when you create or register it, and to add, update, delete, or read tags on existing feature tables.
The Feature Store client now supports publishing to a DynamoDB online store without explicitly passing in secrets. Instead, you can use the attached instance profile from the running Databricks cluster. For instructions, see Publish features to an online store. For API details, see Feature Engineering and Workspace Feature Store Python API.
System environment
The system environment in Databricks Runtime 10.5 ML differs from Databricks Runtime 10.5 as follows:
DBUtils: Databricks Runtime ML does not include Library utility (dbutils.library) (legacy). Use
%pip
commands instead. See Notebook-scoped Python libraries.For GPU clusters, Databricks Runtime ML includes the following NVIDIA GPU libraries:
CUDA 11.0
cuDNN 8.0.5.39
NCCL 2.10.3
TensorRT 7.2.2
Libraries
The following sections list the libraries included in Databricks Runtime 10.5 ML that differ from those included in Databricks Runtime 10.5.
In this section:
Top-tier libraries
Databricks Runtime 10.5 ML includes the following top-tier libraries:
Python libraries
Databricks Runtime 10.5 ML uses Virtualenv for Python package management and includes many popular ML packages.
In addition to the packages specified in the in the following sections, Databricks Runtime 10.5 ML also includes the following packages:
hyperopt 0.2.7.db1
sparkdl 2.2.0-db6
feature_store 0.4.1
automl 1.8.0
Python libraries on CPU clusters
Library |
Version |
Library |
Version |
Library |
Version |
---|---|---|---|---|---|
absl-py |
0.11.0 |
Antergos Linux |
2015.10 (ISO-Rolling) |
appdirs |
1.4.4 |
argon2-cffi |
20.1.0 |
astor |
0.8.1 |
astunparse |
1.6.3 |
async-generator |
1.10 |
attrs |
20.3.0 |
backcall |
0.2.0 |
bcrypt |
3.2.0 |
bidict |
0.21.4 |
bleach |
3.3.0 |
blis |
0.7.7 |
boto3 |
1.16.7 |
botocore |
1.19.7 |
cachetools |
4.2.4 |
catalogue |
2.0.7 |
certifi |
2020.12.5 |
cffi |
1.14.5 |
chardet |
4.0.0 |
click |
7.1.2 |
cloudpickle |
1.6.0 |
cmdstanpy |
0.9.68 |
configparser |
5.0.1 |
convertdate |
2.4.0 |
cryptography |
3.4.7 |
cycler |
0.10.0 |
cymem |
2.0.6 |
Cython |
0.29.23 |
databricks-automl-runtime |
0.2.7 |
databricks-cli |
0.16.4 |
dbl-tempo |
0.1.2 |
dbus-python |
1.2.16 |
decorator |
5.0.6 |
defusedxml |
0.7.1 |
dill |
0.3.2 |
diskcache |
5.4.0 |
distlib |
0.3.4 |
distro-info |
0.23ubuntu1 |
entrypoints |
0.3 |
ephem |
4.1.3 |
facets-overview |
1.0.0 |
fasttext |
0.9.2 |
filelock |
3.0.12 |
Flask |
1.1.2 |
flatbuffers |
2.0 |
fsspec |
0.9.0 |
future |
0.18.2 |
gast |
0.4.0 |
gitdb |
4.0.9 |
GitPython |
3.1.12 |
google-auth |
1.22.1 |
google-auth-oauthlib |
0.4.2 |
google-pasta |
0.2.0 |
grpcio |
1.39.0 |
gunicorn |
20.0.4 |
gviz-api |
1.10.0 |
h5py |
3.1.0 |
hijri-converter |
2.2.3 |
holidays |
0.13 |
horovod |
0.23.0 |
htmlmin |
0.1.12 |
huggingface-hub |
0.5.1 |
idna |
2.10 |
ImageHash |
4.2.1 |
imbalanced-learn |
0.8.1 |
importlib-metadata |
3.10.0 |
ipykernel |
5.3.4 |
ipython |
7.22.0 |
ipython-genutils |
0.2.0 |
ipywidgets |
7.6.3 |
isodate |
0.6.0 |
itsdangerous |
1.1.0 |
jedi |
0.17.2 |
Jinja2 |
2.11.3 |
jmespath |
0.10.0 |
joblib |
1.0.1 |
joblibspark |
0.3.0 |
jsonschema |
3.2.0 |
jupyter-client |
6.1.12 |
jupyter-core |
4.7.1 |
jupyterlab-pygments |
0.1.2 |
jupyterlab-widgets |
1.0.0 |
keras |
2.8.0 |
Keras-Preprocessing |
1.1.2 |
kiwisolver |
1.3.1 |
koalas |
1.8.2 |
korean-lunar-calendar |
0.2.1 |
langcodes |
3.3.0 |
libclang |
13.0.0 |
lightgbm |
3.3.2 |
llvmlite |
0.38.0 |
LunarCalendar |
0.0.9 |
Mako |
1.1.3 |
Markdown |
3.3.3 |
MarkupSafe |
2.0.1 |
matplotlib |
3.4.2 |
missingno |
0.5.1 |
mistune |
0.8.4 |
mleap |
0.18.1 |
mlflow-skinny |
1.24.0 |
multimethod |
1.8 |
murmurhash |
1.0.6 |
nbclient |
0.5.3 |
nbconvert |
6.0.7 |
nbformat |
5.1.3 |
nest-asyncio |
1.5.1 |
networkx |
2.5 |
nltk |
3.6.1 |
notebook |
6.3.0 |
numba |
0.55.1 |
numpy |
1.20.1 |
oauthlib |
3.1.0 |
opt-einsum |
3.3.0 |
packaging |
21.3 |
pandas |
1.2.4 |
pandas-profiling |
3.1.0 |
pandocfilters |
1.4.3 |
paramiko |
2.7.2 |
parso |
0.7.0 |
pathy |
0.6.1 |
patsy |
0.5.1 |
petastorm |
0.11.4 |
pexpect |
4.8.0 |
phik |
0.12.2 |
pickleshare |
0.7.5 |
Pillow |
8.2.0 |
pip |
21.0.1 |
plotly |
5.6.0 |
pmdarima |
1.8.5 |
preshed |
3.0.6 |
prometheus-client |
0.10.1 |
prompt-toolkit |
3.0.17 |
prophet |
1.0.1 |
protobuf |
3.17.2 |
psutil |
5.8.0 |
psycopg2 |
2.8.5 |
ptyprocess |
0.7.0 |
pyarrow |
4.0.0 |
pyasn1 |
0.4.8 |
pyasn1-modules |
0.2.8 |
pybind11 |
2.9.2 |
pycparser |
2.20 |
pydantic |
1.8.2 |
Pygments |
2.8.1 |
PyGObject |
3.36.0 |
PyMeeus |
0.5.11 |
PyNaCl |
1.5.0 |
pyodbc |
4.0.30 |
pyparsing |
2.4.7 |
pyrsistent |
0.17.3 |
pystan |
2.19.1.1 |
python-apt |
2.0.0+ubuntu0.20.4.7 |
python-dateutil |
2.8.1 |
python-editor |
1.0.4 |
python-engineio |
4.3.0 |
python-socketio |
5.4.1 |
pytz |
2020.5 |
PyWavelets |
1.1.1 |
PyYAML |
5.4.1 |
pyzmq |
20.0.0 |
regex |
2021.4.4 |
requests |
2.25.1 |
requests-oauthlib |
1.3.0 |
requests-unixsocket |
0.2.0 |
rsa |
4.8 |
s3transfer |
0.3.7 |
sacremoses |
0.0.49 |
scikit-learn |
0.24.1 |
scipy |
1.6.2 |
seaborn |
0.11.1 |
Send2Trash |
1.5.0 |
setuptools |
52.0.0 |
setuptools-git |
1.2 |
shap |
0.40.0 |
simplejson |
3.17.2 |
six |
1.15.0 |
slicer |
0.0.7 |
smart-open |
5.2.1 |
smmap |
3.0.5 |
spacy |
3.2.3 |
spacy-legacy |
3.0.9 |
spacy-loggers |
1.0.2 |
spark-tensorflow-distributor |
1.0.0 |
sqlparse |
0.4.1 |
srsly |
2.4.3 |
ssh-import-id |
5.10 |
statsmodels |
0.12.2 |
tabulate |
0.8.7 |
tangled-up-in-unicode |
0.1.0 |
tenacity |
6.2.0 |
tensorboard |
2.8.0 |
tensorboard-data-server |
0.6.1 |
tensorboard-plugin-profile |
2.5.0 |
tensorboard-plugin-wit |
1.8.1 |
tensorflow-cpu |
2.8.0 |
tensorflow-estimator |
2.8.0 |
tensorflow-io-gcs-filesystem |
0.24.0 |
termcolor |
1.1.0 |
terminado |
0.9.4 |
testpath |
0.4.4 |
tf-estimator-nightly |
2.8.0.dev2021122109 |
thinc |
8.0.15 |
threadpoolctl |
2.1.0 |
tokenizers |
0.12.1 |
torch |
1.10.2+cpu |
torchvision |
0.11.3+cpu |
tornado |
6.1 |
tqdm |
4.59.0 |
traitlets |
5.0.5 |
transformers |
4.17.0 |
typer |
0.4.1 |
typing-extensions |
3.7.4.3 |
ujson |
4.0.2 |
unattended-upgrades |
0.1 |
urllib3 |
1.25.11 |
virtualenv |
20.4.1 |
visions |
0.7.4 |
wasabi |
0.9.1 |
wcwidth |
0.2.5 |
webencodings |
0.5.1 |
websocket-client |
0.57.0 |
Werkzeug |
1.0.1 |
wheel |
0.36.2 |
widgetsnbextension |
3.5.1 |
wrapt |
1.12.1 |
xgboost |
1.5.2 |
zipp |
3.4.1 |
Python libraries on GPU clusters
Library |
Version |
Library |
Version |
Library |
Version |
---|---|---|---|---|---|
absl-py |
0.11.0 |
Antergos Linux |
2015.10 (ISO-Rolling) |
appdirs |
1.4.4 |
argon2-cffi |
20.1.0 |
astor |
0.8.1 |
astunparse |
1.6.3 |
async-generator |
1.10 |
attrs |
20.3.0 |
backcall |
0.2.0 |
bcrypt |
3.2.0 |
bidict |
0.21.4 |
bleach |
3.3.0 |
blis |
0.7.7 |
boto3 |
1.16.7 |
botocore |
1.19.7 |
cachetools |
4.2.4 |
catalogue |
2.0.7 |
certifi |
2020.12.5 |
cffi |
1.14.5 |
chardet |
4.0.0 |
click |
7.1.2 |
cloudpickle |
1.6.0 |
cmdstanpy |
0.9.68 |
configparser |
5.0.1 |
convertdate |
2.4.0 |
cryptography |
3.4.7 |
cycler |
0.10.0 |
cymem |
2.0.6 |
Cython |
0.29.23 |
databricks-automl-runtime |
0.2.7 |
databricks-cli |
0.16.4 |
dbl-tempo |
0.1.2 |
dbus-python |
1.2.16 |
decorator |
5.0.6 |
defusedxml |
0.7.1 |
dill |
0.3.2 |
diskcache |
5.4.0 |
distlib |
0.3.4 |
distro-info |
0.23ubuntu1 |
entrypoints |
0.3 |
ephem |
4.1.3 |
facets-overview |
1.0.0 |
fasttext |
0.9.2 |
filelock |
3.0.12 |
Flask |
1.1.2 |
flatbuffers |
2.0 |
fsspec |
0.9.0 |
future |
0.18.2 |
gast |
0.4.0 |
gitdb |
4.0.9 |
GitPython |
3.1.12 |
google-auth |
1.22.1 |
google-auth-oauthlib |
0.4.2 |
google-pasta |
0.2.0 |
grpcio |
1.39.0 |
gunicorn |
20.0.4 |
gviz-api |
1.10.0 |
h5py |
3.1.0 |
hijri-converter |
2.2.3 |
holidays |
0.13 |
horovod |
0.23.0 |
htmlmin |
0.1.12 |
huggingface-hub |
0.5.1 |
idna |
2.10 |
ImageHash |
4.2.1 |
imbalanced-learn |
0.8.1 |
importlib-metadata |
3.10.0 |
ipykernel |
5.3.4 |
ipython |
7.22.0 |
ipython-genutils |
0.2.0 |
ipywidgets |
7.6.3 |
isodate |
0.6.0 |
itsdangerous |
1.1.0 |
jedi |
0.17.2 |
Jinja2 |
2.11.3 |
jmespath |
0.10.0 |
joblib |
1.0.1 |
joblibspark |
0.3.0 |
jsonschema |
3.2.0 |
jupyter-client |
6.1.12 |
jupyter-core |
4.7.1 |
jupyterlab-pygments |
0.1.2 |
jupyterlab-widgets |
1.0.0 |
keras |
2.8.0 |
Keras-Preprocessing |
1.1.2 |
kiwisolver |
1.3.1 |
koalas |
1.8.2 |
korean-lunar-calendar |
0.2.1 |
langcodes |
3.3.0 |
libclang |
13.0.0 |
lightgbm |
3.3.2 |
llvmlite |
0.38.0 |
LunarCalendar |
0.0.9 |
Mako |
1.1.3 |
Markdown |
3.3.3 |
MarkupSafe |
2.0.1 |
matplotlib |
3.4.2 |
missingno |
0.5.1 |
mistune |
0.8.4 |
mleap |
0.18.1 |
mlflow-skinny |
1.24.0 |
multimethod |
1.8 |
murmurhash |
1.0.6 |
nbclient |
0.5.3 |
nbconvert |
6.0.7 |
nbformat |
5.1.3 |
nest-asyncio |
1.5.1 |
networkx |
2.5 |
nltk |
3.6.1 |
notebook |
6.3.0 |
numba |
0.55.1 |
numpy |
1.20.1 |
oauthlib |
3.1.0 |
opt-einsum |
3.3.0 |
packaging |
21.3 |
pandas |
1.2.4 |
pandas-profiling |
3.1.0 |
pandocfilters |
1.4.3 |
paramiko |
2.7.2 |
parso |
0.7.0 |
pathy |
0.6.1 |
patsy |
0.5.1 |
petastorm |
0.11.4 |
pexpect |
4.8.0 |
phik |
0.12.2 |
pickleshare |
0.7.5 |
Pillow |
8.2.0 |
pip |
21.0.1 |
plotly |
5.6.0 |
pmdarima |
1.8.5 |
preshed |
3.0.6 |
prompt-toolkit |
3.0.17 |
prophet |
1.0.1 |
protobuf |
3.17.2 |
psutil |
5.8.0 |
psycopg2 |
2.8.5 |
ptyprocess |
0.7.0 |
pyarrow |
4.0.0 |
pyasn1 |
0.4.8 |
pyasn1-modules |
0.2.8 |
pybind11 |
2.9.2 |
pycparser |
2.20 |
pydantic |
1.8.2 |
Pygments |
2.8.1 |
PyGObject |
3.36.0 |
PyMeeus |
0.5.11 |
PyNaCl |
1.5.0 |
pyodbc |
4.0.30 |
pyparsing |
2.4.7 |
pyrsistent |
0.17.3 |
pystan |
2.19.1.1 |
python-apt |
2.0.0+ubuntu0.20.4.7 |
python-dateutil |
2.8.1 |
python-editor |
1.0.4 |
python-engineio |
4.3.0 |
python-socketio |
5.4.1 |
pytz |
2020.5 |
PyWavelets |
1.1.1 |
PyYAML |
5.4.1 |
pyzmq |
20.0.0 |
regex |
2021.4.4 |
requests |
2.25.1 |
requests-oauthlib |
1.3.0 |
requests-unixsocket |
0.2.0 |
rsa |
4.8 |
s3transfer |
0.3.7 |
sacremoses |
0.0.49 |
scikit-learn |
0.24.1 |
scipy |
1.6.2 |
seaborn |
0.11.1 |
Send2Trash |
1.5.0 |
setuptools |
52.0.0 |
setuptools-git |
1.2 |
shap |
0.40.0 |
simplejson |
3.17.2 |
six |
1.15.0 |
slicer |
0.0.7 |
smart-open |
5.2.1 |
smmap |
3.0.5 |
spacy |
3.2.3 |
spacy-legacy |
3.0.9 |
spacy-loggers |
1.0.2 |
spark-tensorflow-distributor |
1.0.0 |
sqlparse |
0.4.1 |
srsly |
2.4.3 |
ssh-import-id |
5.10 |
statsmodels |
0.12.2 |
tabulate |
0.8.7 |
tangled-up-in-unicode |
0.1.0 |
tenacity |
6.2.0 |
tensorboard |
2.8.0 |
tensorboard-data-server |
0.6.1 |
tensorboard-plugin-profile |
2.5.0 |
tensorboard-plugin-wit |
1.8.1 |
tensorflow |
2.8.0 |
tensorflow-estimator |
2.8.0 |
tensorflow-io-gcs-filesystem |
0.24.0 |
termcolor |
1.1.0 |
terminado |
0.9.4 |
testpath |
0.4.4 |
tf-estimator-nightly |
2.8.0.dev2021122109 |
thinc |
8.0.15 |
threadpoolctl |
2.1.0 |
tokenizers |
0.12.1 |
torch |
1.10.2+cu113 |
torchvision |
0.11.3+cu113 |
tornado |
6.1 |
tqdm |
4.59.0 |
traitlets |
5.0.5 |
transformers |
4.17.0 |
typer |
0.4.1 |
typing-extensions |
3.7.4.3 |
ujson |
4.0.2 |
unattended-upgrades |
0.1 |
urllib3 |
1.25.11 |
virtualenv |
20.4.1 |
visions |
0.7.4 |
wasabi |
0.9.1 |
wcwidth |
0.2.5 |
webencodings |
0.5.1 |
websocket-client |
0.57.0 |
Werkzeug |
1.0.1 |
wheel |
0.36.2 |
widgetsnbextension |
3.5.1 |
wrapt |
1.12.1 |
xgboost |
1.5.2 |
zipp |
3.4.1 |
R libraries
The R libraries are identical to the R Libraries in Databricks Runtime 10.5.
Java and Scala libraries (Scala 2.12 cluster)
In addition to Java and Scala libraries in Databricks Runtime 10.5, Databricks Runtime 10.5 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 |
0.18.1-23eb1ef |
ml.dmlc |
xgboost4j-spark_2.12 |
1.5.2 |
ml.dmlc |
xgboost4j_2.12 |
1.5.2 |
org.graphframes |
graphframes_2.12 |
0.8.2-db1-spark3.2 |
org.mlflow |
mlflow-client |
1.24.0 |
org.mlflow |
mlflow-spark |
1.24.0 |
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 |
0.18.1-23eb1ef |
ml.dmlc |
xgboost4j-spark_2.12 |
1.5.2 |
ml.dmlc |
xgboost4j_2.12 |
1.5.2 |
org.graphframes |
graphframes_2.12 |
0.8.2-db1-spark3.2 |
org.mlflow |
mlflow-client |
1.24.0 |
org.mlflow |
mlflow-spark |
1.24.0 |
org.scala-lang.modules |
scala-java8-compat_2.12 |
0.8.0 |
org.tensorflow |
spark-tensorflow-connector_2.12 |
1.15.0 |