Databricks Runtime 10.3 for ML (Unsupported)

Databricks Runtime 10.3 for Machine Learning provides a ready-to-go environment for machine learning and data science based on Databricks Runtime 10.3 (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 Databricks Runtime for Machine Learning.

New features and improvements

Databricks Runtime 10.3 ML is built on top of Databricks Runtime 10.3. For information on what’s new in Databricks Runtime 10.3, including Apache Spark MLlib and SparkR, see the Databricks Runtime 10.3 (Unsupported) release notes.

Enhancements to Databricks AutoML

The following enhancements have been made to Databricks AutoML.

AutoML now supports ARIMA model for forecasting

In addition to Prophet, AutoML now creates and evaluates ARIMA models for forecasting problems.

Exclude columns from dataset

When you use the AutoML API, you can specify columns that AutoML should ignore during its calculations. This is available only for classification and regression problems. See Classification and regression parameters for details.

Exclude algorithm frameworks from an AutoML run

You can specify algorithm frameworks, such as scikit-learn, that AutoML should not consider as it develops models. See Advanced configurations and Classification and regression parameters for details.

max_trials deprecated

The max_trials parameter is deprecated and will be removed in the next major Databricks Runtime ML release. Use timeout_minutes to control the duration of an AutoML run. Also, in Databricks Runtime 10.1 ML and above, AutoML incorporates early stopping; it will stop training and tuning models if the validation metric is no longer improving.

Enhancements to Databricks Feature Store

You can now apply point-in-time lookups to time series feature tables. See Use time series feature tables with point-in-time support for details.

Databricks Autologging (GA)

Databricks Autologging is now generally available in Databricks Runtime 10.3 ML. Databricks Autologging is a no-code solution that provides automatic experiment tracking for machine learning training sessions on Databricks. With Databricks Autologging, model parameters, metrics, files, and lineage information are automatically captured when you train models from a variety of popular machine learning libraries. Training sessions are recorded as MLflow Tracking Runs. Model files are also tracked so you can easily log them to the MLflow Model Registry and deploy them for real-time scoring with MLflow Model Serving.

See Databricks Autologging for more information.

System environment

The system environment in Databricks Runtime 10.3 ML differs from Databricks Runtime 10.3 as follows:

Libraries

The following sections list the libraries included in Databricks Runtime 10.3 ML that differ from those included in Databricks Runtime 10.3.

Python libraries

Databricks Runtime 10.3 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 10.3 ML also includes the following packages:

  • hyperopt 0.2.7.db1

  • sparkdl 2.2.0-db5

  • feature_store 0.3.7

  • automl 1.6.0

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

0.7.4

boto3

1.16.7

botocore

1.19.7

cachetools

4.2.4

catalogue

2.0.6

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

2.3.2

cryptography

3.4.7

cycler

0.10.0

cymem

2.0.5

Cython

0.29.23

databricks-automl-runtime

0.2.5

databricks-cli

0.16.2

dbl-tempo

0.1.2

dbus-python

1.2.16

decorator

5.0.6

defusedxml

0.7.1

dill

0.3.2

diskcache

5.2.1

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

4.0.7

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

2.2.2

holidays

0.12

horovod

0.23.0

htmlmin

0.1.12

huggingface-hub

0.1.2

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

2.7.0

Keras-Preprocessing

1.1.2

kiwisolver

1.3.1

koalas

1.8.2

korean-lunar-calendar

0.2.1

langcodes

3.3.0

libclang

12.0.0

lightgbm

3.3.1

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

0.5.0

mistune

0.8.4

mleap

0.18.1

mlflow-skinny

1.23.0

multimethod

1.6

murmurhash

1.0.5

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

0.55.0

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

0.6.0

patsy

0.5.1

petastorm

0.11.3

pexpect

4.8.0

phik

0.12.0

pickleshare

0.7.5

Pillow

8.2.0

pip

21.0.1

plotly

5.5.0

pmdarima

1.8.4

preshed

3.0.5

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

2.9.0

pycparser

2.20

pydantic

1.8.2

Pygments

2.8.1

PyGObject

3.36.0

PyMeeus

0.5.11

PyNaCl

1.4.0

pyodbc

4.0.30

pyparsing

2.4.7

pyrsistent

0.17.3

pystan

2.19.1.1

python-apt

2.0.0+ubuntu0.20.4.6

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

4.7.2

s3transfer

0.3.7

sacremoses

0.0.46

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

5.2.0

smmap

3.0.5

spacy

3.2.1

spacy-legacy

3.0.8

spacy-loggers

1.0.1

spark-tensorflow-distributor

1.0.0

sqlparse

0.4.1

srsly

2.4.1

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

2.7.0

tensorboard-data-server

0.6.1

tensorboard-plugin-profile

2.5.0

tensorboard-plugin-wit

1.8.1

tensorflow-cpu

2.7.0

tensorflow-estimator

2.7.0

tensorflow-io-gcs-filesystem

0.23.1

termcolor

1.1.0

terminado

0.9.4

testpath

0.4.4

thinc

8.0.12

threadpoolctl

2.1.0

tokenizers

0.10.3

torch

1.10.1+cpu

torchvision

0.11.2+cpu

tornado

6.1

tqdm

4.59.0

traitlets

5.0.5

transformers

4.15.0

typer

0.3.2

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

0.8.2

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

1.5.1

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

0.7.4

boto3

1.16.7

botocore

1.19.7

cachetools

4.2.4

catalogue

2.0.6

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

2.3.2

cryptography

3.4.7

cycler

0.10.0

cymem

2.0.5

Cython

0.29.23

databricks-automl-runtime

0.2.5

databricks-cli

0.16.2

dbl-tempo

0.1.2

dbus-python

1.2.16

decorator

5.0.6

defusedxml

0.7.1

dill

0.3.2

diskcache

5.2.1

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

4.0.7

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

2.2.2

holidays

0.12

horovod

0.23.0

htmlmin

0.1.12

huggingface-hub

0.1.2

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

2.7.0

Keras-Preprocessing

1.1.2

kiwisolver

1.3.1

koalas

1.8.2

korean-lunar-calendar

0.2.1

langcodes

3.3.0

libclang

12.0.0

lightgbm

3.3.1

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

0.5.0

mistune

0.8.4

mleap

0.18.1

mlflow-skinny

1.23.0

multimethod

1.6

murmurhash

1.0.5

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

0.55.0

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

0.6.0

patsy

0.5.1

petastorm

0.11.3

pexpect

4.8.0

phik

0.12.0

pickleshare

0.7.5

Pillow

8.2.0

pip

21.0.1

plotly

5.5.0

pmdarima

1.8.4

preshed

3.0.5

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

2.9.0

pycparser

2.20

pydantic

1.8.2

Pygments

2.8.1

PyGObject

3.36.0

PyMeeus

0.5.11

PyNaCl

1.4.0

pyodbc

4.0.30

pyparsing

2.4.7

pyrsistent

0.17.3

pystan

2.19.1.1

python-apt

2.0.0+ubuntu0.20.4.6

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

4.7.2

s3transfer

0.3.7

sacremoses

0.0.46

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

5.2.0

smmap

3.0.5

spacy

3.2.1

spacy-legacy

3.0.8

spacy-loggers

1.0.1

spark-tensorflow-distributor

1.0.0

sqlparse

0.4.1

srsly

2.4.1

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

2.7.0

tensorboard-data-server

0.6.1

tensorboard-plugin-profile

2.5.0

tensorboard-plugin-wit

1.8.1

tensorflow

2.7.0

tensorflow-estimator

2.7.0

tensorflow-io-gcs-filesystem

0.23.1

termcolor

1.1.0

terminado

0.9.4

testpath

0.4.4

thinc

8.0.12

threadpoolctl

2.1.0

tokenizers

0.10.3

torch

1.10.1+cu111

torchvision

0.11.2+cu111

tornado

6.1

tqdm

4.59.0

traitlets

5.0.5

transformers

4.15.0

typer

0.3.2

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

0.8.2

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

1.5.1

zipp

3.4.1

Spark packages containing Python modules

Spark Package

Python Module

Version

graphframes

graphframes

0.8.2-db1-spark3.2

R libraries

The R libraries are identical to the R Libraries in Databricks Runtime 10.3.

Java and Scala libraries (Scala 2.12 cluster)

In addition to Java and Scala libraries in Databricks Runtime 10.3, Databricks Runtime 10.3 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

1.5.1

ml.dmlc

xgboost4j_2.12

1.5.1

org.graphframes

graphframes_2.12

0.8.2-db1-spark3.2

org.mlflow

mlflow-client

1.23.0

org.mlflow

mlflow-spark

1.23.0

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

1.5.1

ml.dmlc

xgboost4j_2.12

1.5.1

org.graphframes

graphframes_2.12

0.8.2-db1-spark3.2

org.mlflow

mlflow-client

1.23.0

org.mlflow

mlflow-spark

1.23.0

org.scala-lang.modules

scala-java8-compat_2.12

0.8.0

org.tensorflow

spark-tensorflow-connector_2.12

1.15.0