Databricks Runtime 10.0 para ML (sem suporte)
O Databricks Runtime 10.0 para Machine Learning fornece um ambiente de aprendizado de máquina e ciência de dados pronto para uso baseado no Databricks Runtime 10.0 (sem suporte). O Databricks Runtime ML contém muitas bibliotecas de aprendizado de máquina populares, inclusive TensorFlow, PyTorch e XGBoost. Ele também dá suporte ao treinamento de aprendizado profundo distribuído com o uso do Horovod.
Para obter mais informações, como instruções para a criação de um cluster do Databricks Runtime ML, confira IA e Machine Learning no Databricks.
Novos recursos e aprimoramentos
O Databricks Runtime 10.0 ML foi desenvolvido com base no Databricks Runtime 10.0. Para mais informações sobre as novidades do Databricks Runtime 10.0, inclusive o Apache Spark MLlib e o SparkR, veja as notas sobre a versão do Databricks Runtime 10.0 (sem suporte).
Previsão de série temporal com AutoML
Agora o AutoML dá suporte à previsão de série temporal. Para obter mais informações, confira Documentação do AutoML.
Principais alterações no ambiente do Python para o Databricks Runtime ML
Pacotes do Python adicionados
- databricks-automl-runtime 0.1.0
- imbalanced-learn 0.8.0
- transformers 4.9.2
Ambiente do sistema
Atualizamos a versão incluída do RStudio Server Open Source para v1.4.
O ambiente do sistema no Databricks Runtime 10.0 ML é diferente do Databricks Runtime 10.0 nestes aspectos:
- DBUtils: O Databricks Runtime ML não inclui Utilitário de biblioteca (dbutils.library) (herdado).
Use os comandos
%pip. Confira as bibliotecas Python no escopo do notebook. - Para clusters de GPU, o Databricks Runtime ML inclui as seguintes bibliotecas de GPU NVIDIA:
- CUDA 11.0
- cuDNN 8.0.5.39
- NCCL 2.10.3
- TensorRT 7.2.2
Bibliotecas
As seções a seguir listam as bibliotecas incluídas no Databricks Runtime 10.0 ML que são diferentes daquelas incluídas no Databricks Runtime 10.0.
Nesta seção:
- Bibliotecas de camada superior
- Bibliotecas do Python
- Bibliotecas do R
- Bibliotecas do Java e do Scala (cluster do Scala 2.12)
Bibliotecas de camada superior
O Databricks Runtime 10.0 ML inclui as seguintes bibliotecas de camada superior:
- GraphFrames
- Horovod e HorovodRunner
- MLflow
- PyTorch
- spark-tensorflow-connector
- TensorFlow
- TensorBoard
Bibliotecas do Python
O Databricks Runtime 10.0 ML usa o Virtualenv para gerenciamento de pacotes do Python e inclui muitos pacotes de ML bastante populares.
Além dos pacotes especificados nas seções a seguir, o Databricks Runtime 10.0 ML também inclui os seguintes pacotes:
- hyperopt 0.2.5.db2
- sparkdl 2.2.0_db3
- feature_store 0.3.4
- automl 1.3.1
Bibliotecas do Python em clusters de CPU
| Biblioteca | Versão | Biblioteca | Versão | Biblioteca | Versão |
|---|---|---|---|---|---|
| absl-py | 0.11.0 | Antergos Linux | 2015.10 (atualização cumulativa de ISO) | 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 | bleach | 3.3.0 | blis | 0.7.4 |
| boto3 | 1.16.7 | botocore | 1.19.7 | Gargalo | 1.3.2 |
| cachetools | 4.2.2 | catalogue | 2.0.6 | certifi | 2020.12.5 |
| cffi | 1.14.5 | chardet | 4.0.0 | clang | 5.0 |
| clique | 7.1.2 | cloudpickle | 1.6.0 | cmdstanpy | 0.9.68 |
| configparser | 5.0.1 | convertdate | 2.3.2 | criptografia | 3.4.7 |
| cycler | 0.10.0 | cymem | 2.0.5 | Cython | 0.29.23 |
| databricks-automl-runtime | 0.1.0 | databricks-cli | 0.14.3 | dbus-python | 1.2.16 |
| decorator | 5.0.6 | defusedxml | 0.7.1 | dill | 0.3.2 |
| diskcache | 5.2.1 | distlib | 0.3.2 | distro-info | 0.23ubuntu1 |
| entrypoints | 0.3 | ephem | 4.0.0.2 | facets-overview | 1.0.0 |
| filelock | 3.0.12 | Flask | 1.1.2 | flatbuffers | 1.12 |
| 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 | h5py | 3.1.0 | hijri-converter | 2.2.1 |
| feriados | 0.11.2 | horovod | 0.22.1 | htmlmin | 0.1.12 |
| huggingface-hub | 0.0.12 | idna | 2.10 | ImageHash | 4.2.1 |
| imbalanced-learn | 0.8.0 | 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 | 2.6.0 | Keras-Preprocessing | 1.1.2 | kiwisolver | 1.3.1 |
| koalas | 1.8.1 | korean-lunar-calendar | 0.2.1 | lightgbm | 3.1.1 |
| llvmlite | 0.37.0 | LunarCalendar | 0.0.9 | Mako | 1.1.3 |
| Markdown | 3.3.3 | MarkupSafe | 1.1.1 | matplotlib | 3.4.2 |
| missingno | 0.5.0 | mistune | 0.8.4 | mleap | 0.17.0 |
| mlflow-skinny | 1.20.2 | multimethod | 1.4 | 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 | 0.54.0 | numpy | 1.19.2 |
| oauthlib | 3.1.0 | opt-einsum | 3.3.0 | empacotando | 20.9 |
| pandas | 1.2.4 | pandas-profiling | 3.0.0 | pandocfilters | 1.4.3 |
| paramiko | 2.7.2 | parso | 0.7.0 | pathy | 0.6.0 |
| patsy | 0.5.1 | petastorm | 0.11.2 | pexpect | 4.8.0 |
| phik | 0.12.0 | pickleshare | 0.7.5 | Pillow | 8.2.0 |
| pip | 21.0.1 | plotly | 5.1.0 | 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 | pycparser | 2,20 | pydantic | 1.8.2 |
| Pygments | 2.8.1 | PyGObject | 3.36.0 | PyMeeus | 0.5.11 |
| PyNaCl | 1.3.0 | 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 | pytz | 2020.5 |
| PyWavelets | 1.1.1 | PyYAML | 5.4.1 | pyzmq | 20.0.0 |
| regex | 2021.4.4 | solicitações | 2.25.1 | requests-oauthlib | 1.3.0 |
| requests-unixsocket | 0.2.0 | rsa | 4.7.2 | s3transfer | 0.3.7 |
| sacremoses | 0.0.45 | 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 | 0.39.0 | simplejson | 3.17.2 |
| six | 1.15.0 | slicer | 0.0.7 | smart-open | 5.2.0 |
| smmap | 3.0.5 | spacy | 3.1.2 | spacy-legacy | 3.0.8 |
| 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 | 2.6.0 |
| tensorboard-data-server | 0.6.1 | tensorboard-plugin-wit | 1.8.0 | tensorflow-cpu | 2.6.0 |
| tensorflow-estimator | 2.6.0 | termcolor | 1.1.0 | terminado | 0.9.4 |
| testpath | 0.4.4 | thinc | 8.0.8 | threadpoolctl | 2.1.0 |
| tokenizers | 0.10.3 | torch | 1.9.0+cpu | torchvision | 0.10.0+cpu |
| tornado | 6.1 | tqdm | 4.59.0 | traitlets | 5.0.5 |
| transformers | 4.9.2 | 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 | 0.7.1 | 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 | 1.4.2 | zipp | 3.4.1 |
Bibliotecas do Python em clusters de GPU
| Biblioteca | Versão | Biblioteca | Versão | Biblioteca | Versão |
|---|---|---|---|---|---|
| absl-py | 0.11.0 | Antergos Linux | 2015.10 (atualização cumulativa de ISO) | 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 | bleach | 3.3.0 | blis | 0.7.4 |
| boto3 | 1.16.7 | botocore | 1.19.7 | Gargalo | 1.3.2 |
| cachetools | 4.2.2 | catalogue | 2.0.6 | certifi | 2020.12.5 |
| cffi | 1.14.5 | chardet | 4.0.0 | clang | 5.0 |
| clique | 7.1.2 | cloudpickle | 1.6.0 | cmdstanpy | 0.9.68 |
| configparser | 5.0.1 | convertdate | 2.3.2 | criptografia | 3.4.7 |
| cycler | 0.10.0 | cymem | 2.0.5 | Cython | 0.29.23 |
| databricks-automl-runtime | 0.1.0 | databricks-cli | 0.14.3 | dbus-python | 1.2.16 |
| decorator | 5.0.6 | defusedxml | 0.7.1 | dill | 0.3.2 |
| diskcache | 5.2.1 | distlib | 0.3.2 | distro-info | 0.23ubuntu1 |
| entrypoints | 0.3 | ephem | 4.0.0.2 | facets-overview | 1.0.0 |
| filelock | 3.0.12 | Flask | 1.1.2 | flatbuffers | 1.12 |
| 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 | h5py | 3.1.0 | hijri-converter | 2.2.1 |
| feriados | 0.11.2 | horovod | 0.22.1 | htmlmin | 0.1.12 |
| huggingface-hub | 0.0.12 | idna | 2.10 | ImageHash | 4.2.1 |
| imbalanced-learn | 0.8.0 | 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 | 2.6.0 | Keras-Preprocessing | 1.1.2 | kiwisolver | 1.3.1 |
| koalas | 1.8.1 | korean-lunar-calendar | 0.2.1 | lightgbm | 3.1.1 |
| llvmlite | 0.37.0 | LunarCalendar | 0.0.9 | Mako | 1.1.3 |
| Markdown | 3.3.3 | MarkupSafe | 1.1.1 | matplotlib | 3.4.2 |
| missingno | 0.5.0 | mistune | 0.8.4 | mleap | 0.17.0 |
| mlflow-skinny | 1.20.2 | multimethod | 1.4 | 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 | 0.54.0 | numpy | 1.19.2 |
| oauthlib | 3.1.0 | opt-einsum | 3.3.0 | empacotando | 20.9 |
| pandas | 1.2.4 | pandas-profiling | 3.0.0 | pandocfilters | 1.4.3 |
| paramiko | 2.7.2 | parso | 0.7.0 | pathy | 0.6.0 |
| patsy | 0.5.1 | petastorm | 0.11.2 | pexpect | 4.8.0 |
| phik | 0.12.0 | pickleshare | 0.7.5 | Pillow | 8.2.0 |
| pip | 21.0.1 | plotly | 5.1.0 | 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 |
| pycparser | 2,20 | pydantic | 1.8.2 | Pygments | 2.8.1 |
| PyGObject | 3.36.0 | PyMeeus | 0.5.11 | PyNaCl | 1.3.0 |
| 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 | pytz | 2020.5 | PyWavelets | 1.1.1 |
| PyYAML | 5.4.1 | pyzmq | 20.0.0 | regex | 2021.4.4 |
| solicitações | 2.25.1 | requests-oauthlib | 1.3.0 | requests-unixsocket | 0.2.0 |
| rsa | 4.7.2 | s3transfer | 0.3.7 | sacremoses | 0.0.45 |
| 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 | 0.39.0 | simplejson | 3.17.2 | six | 1.15.0 |
| slicer | 0.0.7 | smart-open | 5.2.0 | smmap | 3.0.5 |
| spacy | 3.1.2 | spacy-legacy | 3.0.8 | 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 | 2.6.0 | tensorboard-data-server | 0.6.1 |
| tensorboard-plugin-wit | 1.8.0 | tensorflow | 2.6.0 | tensorflow-estimator | 2.6.0 |
| termcolor | 1.1.0 | terminado | 0.9.4 | testpath | 0.4.4 |
| thinc | 8.0.8 | threadpoolctl | 2.1.0 | tokenizers | 0.10.3 |
| torch | 1.9.0+cu111 | torchvision | 0.10.0+cu111 | tornado | 6.1 |
| tqdm | 4.59.0 | traitlets | 5.0.5 | transformers | 4.9.2 |
| 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 | 0.7.1 | 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 | 1.4.2 | zipp | 3.4.1 |
Pacotes do Spark que contêm módulos do Python
| Pacote do Spark | Módulo do Python | Versão |
|---|---|---|
| graphframes | graphframes | 0.8.1-db6-spark3.2 |
Bibliotecas do R
As bibliotecas do R são idênticas às bibliotecas do R do Databricks Runtime 10.0.
Bibliotecas do Java e do Scala (cluster do Scala 2.12)
Além das bibliotecas do Java e do Scala no Databricks Runtime 10.0, o Databricks Runtime 10.0 ML contém os seguintes JARs:
Clusters de CPU
| ID do Grupo | Artifact ID | Versão |
|---|---|---|
| com.typesafe.akka | akka-actor_2.12 | 2.5.23 |
| ml.combust.mleap | mleap-databricks-runtime_2.12 | 0.17.0-4882dc3 |
| ml.dmlc | xgboost4j-spark_2.12 | 1.4.1 |
| ml.dmlc | xgboost4j_2.12 | 1.4.1 |
| org.graphframes | graphframes_2.12 | 0.8.1-db6-spark3.2 |
| org.mlflow | mlflow-client | 1.20.2 |
| org.mlflow | mlflow-spark | 1.20.2 |
| org.scala-lang.modules | scala-java8-compat_2.12 | 0.8.0 |
| org.tensorflow | spark-tensorflow-connector_2.12 | 1.15.0 |
Clusters de GPU
| ID do Grupo | Artifact ID | Versão |
|---|---|---|
| com.typesafe.akka | akka-actor_2.12 | 2.5.23 |
| ml.combust.mleap | mleap-databricks-runtime_2.12 | 0.17.0-4882dc3 |
| ml.dmlc | xgboost4j-gpu_2.12 | 1.4.1 |
| ml.dmlc | xgboost4j-spark-gpu_2.12 | 1.4.1 |
| org.graphframes | graphframes_2.12 | 0.8.1-db6-spark3.2 |
| org.mlflow | mlflow-client | 1.20.2 |
| org.mlflow | mlflow-spark | 1.20.2 |
| org.scala-lang.modules | scala-java8-compat_2.12 | 0.8.0 |
| org.tensorflow | spark-tensorflow-connector_2.12 | 1.15.0 |