Databricks Runtime 8.4 untuk ML (EoS)

Databricks merilis versi ini pada Juli 2021.

Databricks Runtime 8.4 untuk Pembelajaran Mesin menyediakan lingkungan siap pakai untuk pembelajaran mesin dan ilmu data berdasarkan Databricks Runtime 8.4 (EoS). Runtime Bahasa Umum Databricks ML berisi banyak pustaka pembelajaran mesin populer, termasuk TensorFlow, PyTorch, dan XGBoost. Ini juga mendukung pelatihan pembelajaran mendalam terdistribusi menggunakan Horovod.

Untuk informasi selengkapnya, termasuk instruksi untuk membuat kluster ML Runtime Databricks, lihat AI dan pembelajaran mesin di Databricks.

Fitur dan peningkatan baru

ML Databricks Runtime 8.4 dibuat di atas Databricks Runtime 8.4. Untuk informasi tentang apa yang baru di Databricks Runtime 8.4, termasuk Apache Spark MLlib dan SparkR, lihat catatan rilis Databricks Runtime 8.4 (EoS).

FeatureStoreClient v0.3.2

• Izinkan nama tabel fitur dan fitur yang bertentangan dengan kata khusus SQL.
• Validasi bahwa DataFrame yang disediakan adalah PySpark DataFrames (pyspark.sql.dataframe.DataFrame).

AutoML v1.1.0

• Versi terbaru AutoML yang dikirimkan dengan Databricks Runtime 8.4 ML mencakup beberapa perbaikan bug dan peningkatan stabilitas.
• Klasifikasi AutoML sekarang juga menjalankan percobaan dengan LGBMClassifier
• Regresi AutoML sekarang juga menjalankan percobaan dengan LGBMRegressor

Perubahan besar pada lingkungan Phyton ML Databricks Runtime

Lihat Databricks Runtime 8.4 (EoS) untuk perubahan besar pada lingkungan Databricks Runtime Python. Untuk daftar lengkap paket Python yang diinstal dan versinya, lihat Pustaka Python.

Paket Phyton ditingkatkan

• koalas 1.8.0 -> 1.8.1
• horovod 0.21.3 -> 0.22.1
• mleap 0.16.1 -> 0.17.0
• mlflow 1.16.0 -> 1.18.0
• pandas-profiling 2.11.0 -> 3.0.0
• petastorm 0.10.0 -> 0.11.1
• pytorch 1.8.1 -> 1.9.0
• tensorboard 2.4.1 -> 2.5.0
• tensorflow 2.4.1 -> 2.5.0
• torchvision 0.9.1 -> 0.10.0
• xgboost 1.4.1 -> 1.4.2

Penghentian

Perubahan berikut tidak digunakan lagi dan akan dihapus di Databricks Runtime 9.0:

• Di HorovodRunner, pengaturan np=0, di mana np jumlah proses paralel yang digunakan untuk pekerjaan Horovod.
• Intel Math Kernel Library (Intel MKL), bersama dengan preferensi downstream paket yang bergantung padanya.
• azure-corePustaka python untuk pengecualian dan modul inti Azure
• azure-storage-blob Klien pustaka python untuk berinteraksi dengan layanan Blob Azure Storage
• msrest Pustaka python untuk generasi swagger AutoRest
• docker Pustaka python untuk API Docker Engine
• querystring-parser Pustaka python untuk mengurai kueri di Python/Django
• intel-openmp Pustaka python untuk membuat perangkat lunak multithreaded

Lingkungan sistem

Lingkungan sistem di ML Databricks Runtime 8.4 berbeda dari Databricks Runtime 8.4 sebagai berikut:

• DBUtils: Databricks Runtime ML tidak menyertakan utilitas Pustaka (dbutils.library) (warisan). Gunakan perintah %pip dan %conda sebagai gantinya. Lihat Pustaka Python cakupan buku catatan.
• Untuk kluster GPU, Databricks Runtime ML menyertakan pustaka GPU NVIDIA berikut:
  • CUDA 11.0
  • cuDNN 8.0.4.30
  • NCCL 2.7.8
  • TensorRT 7.1.3

Pustaka

Bagian berikut mencantumkan pustaka yang disertakan dalam ML Databricks Runtime 8.4 yang berbeda dari yang disertakan dalam Databricks Runtime 8.4.

Di bagian ini:

• Pustaka tingkat atas
• Pustaka Python
• Pustaka R
• Pustaka Java dan Scala (Kluster Scala 2.12)

Pustaka tingkat atas

ML Databricks Runtime 8.4 mencakup pustaka tingkat atas berikut:

• GraphFrames
• Horovod dan HorovodRunner
• MLflow
• PyTorch
• spark-tensorflow-connector
• TensorFlow 2.5.0
• TensorBoard

Pustaka Python

ML Databricks Runtime 8.4 menggunakan Conda untuk manajemen paket Phyton dan mencakup banyak paket ML populer.

Selain paket yang ditentukan di lingkungan Conda di bagian berikut, ML Databricks Runtime 8.4 juga mencakup paket berikut:

• hyperopt 0.2.5.db2
• sparkdl 2.1.0.db4
• feature_store 0.3.2
• automl 1.1.0

Pustaka Phyton di kluster CPU

name: databricks-ml
channels:
  - pytorch
  - defaults
dependencies:
  - _libgcc_mutex=0.1=main
  - absl-py=0.11.0=pyhd3eb1b0_1
  - aiohttp=3.7.4=py38h27cfd23_1
  - asn1crypto=1.4.0=py_0
  - astor=0.8.1=py38h06a4308_0
  - async-timeout=3.0.1=py38h06a4308_0
  - attrs=20.3.0=pyhd3eb1b0_0
  - backcall=0.2.0=pyhd3eb1b0_0
  - bcrypt=3.2.0=py38h7b6447c_0
  - blas=1.0=mkl
  - blinker=1.4=py38h06a4308_0
  - boto3=1.16.7=pyhd3eb1b0_0
  - botocore=1.19.7=pyhd3eb1b0_0
  - brotlipy=0.7.0=py38h27cfd23_1003
  - bzip2=1.0.8=h7b6447c_0
  - ca-certificates=2021.5.25=h06a4308_1
  - cachetools=4.2.2=pyhd3eb1b0_0
  - certifi=2021.5.30=py38h06a4308_0
  - cffi=1.14.3=py38h261ae71_2
  - chardet=3.0.4=py38h06a4308_1003
  - click=7.1.2=pyhd3eb1b0_0
  - cloudpickle=1.6.0=py_0
  - configparser=5.0.1=py_0
  - cpuonly=1.0=0
  - cryptography=3.1.1=py38h1ba5d50_0
  - cycler=0.10.0=py38_0
  - cython=0.29.21=py38h2531618_0
  - decorator=4.4.2=pyhd3eb1b0_0
  - dill=0.3.2=py_0
  - docutils=0.15.2=py38h06a4308_1
  - entrypoints=0.3=py38_0
  - ffmpeg=4.2.2=h20bf706_0
  - flask=1.1.2=pyhd3eb1b0_0
  - freetype=2.10.4=h5ab3b9f_0
  - fsspec=0.8.3=py_0
  - future=0.18.2=py38_1
  - gast=0.4.0=py_0
  - gitdb=4.0.7=pyhd3eb1b0_0
  - gitpython=3.1.12=pyhd3eb1b0_1
  - gmp=6.1.2=h6c8ec71_1
  - gnutls=3.6.15=he1e5248_0
  - google-auth=1.22.1=py_0
  - google-auth-oauthlib=0.4.2=pyhd3eb1b0_2
  - google-pasta=0.2.0=py_0
  - gunicorn=20.0.4=py38h06a4308_0
  - hdf5=1.10.4=hb1b8bf9_0
  - icu=58.2=he6710b0_3
  - idna=2.10=pyhd3eb1b0_0
  - importlib-metadata=2.0.0=py_1
  - intel-openmp=2019.4=243
  - ipykernel=5.3.4=py38h5ca1d4c_0
  - ipython=7.19.0=py38hb070fc8_1
  - ipython_genutils=0.2.0=pyhd3eb1b0_1
  - isodate=0.6.0=py_1
  - itsdangerous=1.1.0=pyhd3eb1b0_0
  - jedi=0.17.2=py38h06a4308_1
  - jinja2=2.11.2=pyhd3eb1b0_0
  - jmespath=0.10.0=py_0
  - joblib=0.17.0=py_0
  - jpeg=9b=h024ee3a_2
  - jupyter_client=6.1.7=py_0
  - jupyter_core=4.6.3=py38_0
  - kiwisolver=1.3.0=py38h2531618_0
  - krb5=1.17.1=h173b8e3_0
  - lame=3.100=h7b6447c_0
  - lcms2=2.11=h396b838_0
  - ld_impl_linux-64=2.33.1=h53a641e_7
  - libedit=3.1.20191231=h14c3975_1
  - libffi=3.3=he6710b0_2
  - libgcc-ng=9.1.0=hdf63c60_0
  - libgfortran-ng=7.3.0=hdf63c60_0
  - libidn2=2.3.1=h27cfd23_0
  - libopus=1.3.1=h7b6447c_0
  - libpng=1.6.37=hbc83047_0
  - libpq=12.2=h20c2e04_0
  - libprotobuf=3.13.0.1=hd408876_0
  - libsodium=1.0.18=h7b6447c_0
  - libstdcxx-ng=9.1.0=hdf63c60_0
  - libtasn1=4.16.0=h27cfd23_0
  - libtiff=4.1.0=h2733197_1
  - libunistring=0.9.10=h27cfd23_0
  - libuv=1.40.0=h7b6447c_0
  - libvpx=1.7.0=h439df22_0
  - lightgbm=3.1.1=py38h2531618_0
  - lz4-c=1.9.2=heb0550a_3
  - mako=1.1.3=py_0
  - markdown=3.3.3=py38h06a4308_0
  - markupsafe=1.1.1=py38h7b6447c_0
  - matplotlib-base=3.2.2=py38hef1b27d_0
  - mkl=2019.4=243
  - mkl-service=2.3.0=py38he904b0f_0
  - mkl_fft=1.2.0=py38h23d657b_0
  - mkl_random=1.1.0=py38h962f231_0
  - more-itertools=8.6.0=pyhd3eb1b0_0
  - multidict=5.1.0=py38h27cfd23_2
  - ncurses=6.2=he6710b0_1
  - nettle=3.7.3=hbbd107a_1
  - networkx=2.5.1=pyhd3eb1b0_0
  - ninja=1.10.2=hff7bd54_1
  - nltk=3.5=py_0
  - numpy=1.19.2=py38h54aff64_0
  - numpy-base=1.19.2=py38hfa32c7d_0
  - oauthlib=3.1.0=py_0
  - olefile=0.46=py_0
  - openh264=2.1.0=hd408876_0
  - openssl=1.1.1k=h27cfd23_0
  - packaging=20.4=py_0
  - pandas=1.1.5=py38ha9443f7_0
  - paramiko=2.7.2=py_0
  - parso=0.7.0=py_0
  - patsy=0.5.1=py38_0
  - pexpect=4.8.0=pyhd3eb1b0_3
  - pickleshare=0.7.5=pyhd3eb1b0_1003
  - pillow=8.0.1=py38he98fc37_0
  - pip=20.2.4=py38h06a4308_0
  - plotly=4.14.3=pyhd3eb1b0_0
  - prompt-toolkit=3.0.8=py_0
  - prompt_toolkit=3.0.8=0
  - protobuf=3.13.0.1=py38he6710b0_1
  - psutil=5.7.2=py38h7b6447c_0
  - psycopg2=2.8.5=py38h3c74f83_1
  - ptyprocess=0.6.0=pyhd3eb1b0_2
  - pyasn1=0.4.8=py_0
  - pyasn1-modules=0.2.8=py_0
  - pycparser=2.20=py_2
  - pygments=2.7.2=pyhd3eb1b0_0
  - pyjwt=1.7.1=py38_0
  - pynacl=1.4.0=py38h7b6447c_1
  - pyodbc=4.0.30=py38he6710b0_0
  - pyopenssl=19.1.0=pyhd3eb1b0_1
  - pyparsing=2.4.7=pyhd3eb1b0_0
  - pysocks=1.7.1=py38h06a4308_0
  - python=3.8.8=hdb3f193_4
  - python-dateutil=2.8.1=pyhd3eb1b0_0
  - python-editor=1.0.4=py_0
  - pytorch=1.9.0=py3.8_cpu_0
  - pytz=2020.5=pyhd3eb1b0_0
  - pyzmq=19.0.2=py38he6710b0_1
  - readline=8.0=h7b6447c_0
  - regex=2020.10.15=py38h7b6447c_0
  - requests=2.24.0=py_0
  - requests-oauthlib=1.3.0=py_0
  - retrying=1.3.3=py_2
  - rsa=4.7.2=pyhd3eb1b0_1
  - s3transfer=0.3.6=pyhd3eb1b0_0
  - scikit-learn=0.23.2=py38h0573a6f_0
  - scipy=1.5.2=py38h0b6359f_0
  - setuptools=50.3.1=py38h06a4308_1
  - simplejson=3.17.2=py38h27cfd23_2
  - six=1.15.0=py38h06a4308_0
  - smmap=3.0.5=pyhd3eb1b0_0
  - sqlite=3.33.0=h62c20be_0
  - sqlparse=0.4.1=py_0
  - statsmodels=0.12.0=py38h7b6447c_0
  - tabulate=0.8.7=py38h06a4308_0
  - threadpoolctl=2.1.0=pyh5ca1d4c_0
  - tk=8.6.10=hbc83047_0
  - torchvision=0.10.0=py38_cpu
  - tornado=6.0.4=py38h7b6447c_1
  - tqdm=4.50.2=py_0
  - traitlets=5.0.5=pyhd3eb1b0_0
  - typing-extensions=3.7.4.3=hd3eb1b0_0
  - typing_extensions=3.7.4.3=pyh06a4308_0
  - unixodbc=2.3.9=h7b6447c_0
  - urllib3=1.25.11=py_0
  - wcwidth=0.2.5=py_0
  - websocket-client=0.57.0=py38_2
  - werkzeug=1.0.1=pyhd3eb1b0_0
  - wheel=0.35.1=pyhd3eb1b0_0
  - wrapt=1.12.1=py38h7b6447c_1
  - x264=1!157.20191217=h7b6447c_0
  - xz=5.2.5=h7b6447c_0
  - yarl=1.6.3=py38h27cfd23_0
  - zeromq=4.3.3=he6710b0_3
  - zipp=3.4.0=pyhd3eb1b0_0
  - zlib=1.2.11=h7b6447c_3
  - zstd=1.4.5=h9ceee32_0
  - pip:
      - argon2-cffi==20.1.0
      - astunparse==1.6.3
      - async-generator==1.10
      - azure-core==1.11.0
      - azure-storage-blob==12.7.1
      - bleach==3.3.0
      - bottleneck==1.3.2
      - convertdate==2.3.2
      - databricks-cli==0.14.3
      - defusedxml==0.7.1
      - diskcache==5.2.1
      - docker==4.4.4
      - facets-overview==1.0.0
      - flatbuffers==1.12
      - grpcio==1.34.1
      - h5py==3.1.0
      - hijri-converter==2.1.3
      - holidays==0.10.5.2
      - horovod==0.22.1
      - htmlmin==0.1.12
      - imagehash==4.2.0
      - ipywidgets==7.6.3
      - joblibspark==0.3.0
      - jsonschema==3.2.0
      - jupyterlab-pygments==0.1.2
      - jupyterlab-widgets==1.0.0
      - keras-nightly==2.5.0.dev2021032900
      - keras-preprocessing==1.1.2
      - koalas==1.8.1
      - korean-lunar-calendar==0.2.1
      - llvmlite==0.36.0
      - missingno==0.4.2
      - mistune==0.8.4
      - mleap==0.17.0
      - mlflow-skinny==1.18.0
      - msrest==0.6.21
      - multimethod==1.4
      - nbclient==0.5.3
      - nbconvert==6.1.0
      - nbformat==5.1.3
      - nest-asyncio==1.5.1
      - notebook==6.4.0
      - numba==0.53.1
      - opt-einsum==3.3.0
      - pandas-profiling==3.0.0
      - pandocfilters==1.4.3
      - petastorm==0.11.1
      - phik==0.11.2
      - prometheus-client==0.11.0
      - pyarrow==1.0.1
      - pydantic==1.8.2
      - pymeeus==0.5.11
      - pyrsistent==0.18.0
      - pywavelets==1.1.1
      - pyyaml==5.4.1
      - querystring-parser==1.2.4
      - seaborn==0.10.0
      - send2trash==1.7.1
      - shap==0.39.0
      - slicer==0.0.7
      - spark-tensorflow-distributor==0.1.0
      - tangled-up-in-unicode==0.1.0
      - tensorboard==2.5.0
      - tensorboard-data-server==0.6.1
      - tensorboard-plugin-wit==1.8.0
      - tensorflow-cpu==2.5.0
      - tensorflow-estimator==2.5.0
      - termcolor==1.1.0
      - terminado==0.10.1
      - testpath==0.5.0
      - visions==0.7.1
      - webencodings==0.5.1
      - widgetsnbextension==3.5.1
      - xgboost==1.4.2
prefix: /databricks/conda/envs/databricks-ml

Pustaka Phyton di kluster GPU

name: databricks-ml-gpu
channels:
  - defaults
dependencies:
  - _libgcc_mutex=0.1=main
  - absl-py=0.11.0=pyhd3eb1b0_1
  - aiohttp=3.7.4=py38h27cfd23_1
  - asn1crypto=1.4.0=py_0
  - astor=0.8.1=py38h06a4308_0
  - async-timeout=3.0.1=py38h06a4308_0
  - attrs=20.3.0=pyhd3eb1b0_0
  - backcall=0.2.0=pyhd3eb1b0_0
  - bcrypt=3.2.0=py38h7b6447c_0
  - blas=1.0=mkl
  - blinker=1.4=py38h06a4308_0
  - boto3=1.16.7=pyhd3eb1b0_0
  - botocore=1.19.7=pyhd3eb1b0_0
  - brotlipy=0.7.0=py38h27cfd23_1003
  - ca-certificates=2021.5.25=h06a4308_1
  - cachetools=4.2.2=pyhd3eb1b0_0
  - certifi=2021.5.30=py38h06a4308_0
  - cffi=1.14.3=py38h261ae71_2
  - chardet=3.0.4=py38h06a4308_1003
  - click=7.1.2=pyhd3eb1b0_0
  - cloudpickle=1.6.0=py_0
  - configparser=5.0.1=py_0
  - cryptography=3.1.1=py38h1ba5d50_0
  - cycler=0.10.0=py38_0
  - cython=0.29.21=py38h2531618_0
  - decorator=4.4.2=pyhd3eb1b0_0
  - dill=0.3.2=py_0
  - docutils=0.15.2=py38h06a4308_1
  - entrypoints=0.3=py38_0
  - flask=1.1.2=pyhd3eb1b0_0
  - freetype=2.10.4=h5ab3b9f_0
  - fsspec=0.8.3=py_0
  - future=0.18.2=py38_1
  - gast=0.4.0=py_0
  - gitdb=4.0.7=pyhd3eb1b0_0
  - gitpython=3.1.12=pyhd3eb1b0_1
  - google-auth=1.22.1=py_0
  - google-auth-oauthlib=0.4.2=pyhd3eb1b0_2
  - google-pasta=0.2.0=py_0
  - gunicorn=20.0.4=py38h06a4308_0
  - hdf5=1.10.4=hb1b8bf9_0
  - icu=58.2=he6710b0_3
  - idna=2.10=pyhd3eb1b0_0
  - importlib-metadata=2.0.0=py_1
  - intel-openmp=2019.4=243
  - ipykernel=5.3.4=py38h5ca1d4c_0
  - ipython=7.19.0=py38hb070fc8_1
  - ipython_genutils=0.2.0=pyhd3eb1b0_1
  - isodate=0.6.0=py_1
  - itsdangerous=1.1.0=pyhd3eb1b0_0
  - jedi=0.17.2=py38h06a4308_1
  - jinja2=2.11.2=pyhd3eb1b0_0
  - jmespath=0.10.0=py_0
  - joblib=0.17.0=py_0
  - jpeg=9b=h024ee3a_2
  - jupyter_client=6.1.7=py_0
  - jupyter_core=4.6.3=py38_0
  - kiwisolver=1.3.0=py38h2531618_0
  - krb5=1.17.1=h173b8e3_0
  - lcms2=2.11=h396b838_0
  - ld_impl_linux-64=2.33.1=h53a641e_7
  - libedit=3.1.20191231=h14c3975_1
  - libffi=3.3=he6710b0_2
  - libgcc-ng=9.1.0=hdf63c60_0
  - libgfortran-ng=7.3.0=hdf63c60_0
  - libpng=1.6.37=hbc83047_0
  - libpq=12.2=h20c2e04_0
  - libprotobuf=3.13.0.1=hd408876_0
  - libsodium=1.0.18=h7b6447c_0
  - libstdcxx-ng=9.1.0=hdf63c60_0
  - libtiff=4.1.0=h2733197_1
  - lightgbm=3.1.1=py38h2531618_0
  - lz4-c=1.9.2=heb0550a_3
  - mako=1.1.3=py_0
  - markdown=3.3.3=py38h06a4308_0
  - markupsafe=1.1.1=py38h7b6447c_0
  - matplotlib-base=3.2.2=py38hef1b27d_0
  - mkl=2019.4=243
  - mkl-service=2.3.0=py38he904b0f_0
  - mkl_fft=1.2.0=py38h23d657b_0
  - mkl_random=1.1.0=py38h962f231_0
  - more-itertools=8.6.0=pyhd3eb1b0_0
  - multidict=5.1.0=py38h27cfd23_2
  - ncurses=6.2=he6710b0_1
  - networkx=2.5.1=pyhd3eb1b0_0
  - nltk=3.5=py_0
  - numpy=1.19.2=py38h54aff64_0
  - numpy-base=1.19.2=py38hfa32c7d_0
  - oauthlib=3.1.0=py_0
  - olefile=0.46=py_0
  - openssl=1.1.1k=h27cfd23_0
  - packaging=20.4=py_0
  - pandas=1.1.5=py38ha9443f7_0
  - paramiko=2.7.2=py_0
  - parso=0.7.0=py_0
  - patsy=0.5.1=py38_0
  - pexpect=4.8.0=pyhd3eb1b0_3
  - pickleshare=0.7.5=pyhd3eb1b0_1003
  - pillow=8.0.1=py38he98fc37_0
  - pip=20.2.4=py38h06a4308_0
  - plotly=4.14.3=pyhd3eb1b0_0
  - prompt-toolkit=3.0.8=py_0
  - prompt_toolkit=3.0.8=0
  - protobuf=3.13.0.1=py38he6710b0_1
  - psutil=5.7.2=py38h7b6447c_0
  - psycopg2=2.8.5=py38h3c74f83_1
  - ptyprocess=0.6.0=pyhd3eb1b0_2
  - pyasn1=0.4.8=py_0
  - pyasn1-modules=0.2.8=py_0
  - pycparser=2.20=py_2
  - pygments=2.7.2=pyhd3eb1b0_0
  - pyjwt=1.7.1=py38_0
  - pynacl=1.4.0=py38h7b6447c_1
  - pyodbc=4.0.30=py38he6710b0_0
  - pyopenssl=19.1.0=pyhd3eb1b0_1
  - pyparsing=2.4.7=pyhd3eb1b0_0
  - pysocks=1.7.1=py38h06a4308_0
  - python=3.8.8=hdb3f193_4
  - python-dateutil=2.8.1=pyhd3eb1b0_0
  - python-editor=1.0.4=py_0
  - pytz=2020.5=pyhd3eb1b0_0
  - pyzmq=19.0.2=py38he6710b0_1
  - readline=8.0=h7b6447c_0
  - regex=2020.10.15=py38h7b6447c_0
  - requests=2.24.0=py_0
  - requests-oauthlib=1.3.0=py_0
  - retrying=1.3.3=py_2
  - rsa=4.7.2=pyhd3eb1b0_1
  - s3transfer=0.3.6=pyhd3eb1b0_0
  - scikit-learn=0.23.2=py38h0573a6f_0
  - scipy=1.5.2=py38h0b6359f_0
  - setuptools=50.3.1=py38h06a4308_1
  - simplejson=3.17.2=py38h27cfd23_2
  - six=1.15.0=py38h06a4308_0
  - smmap=3.0.5=pyhd3eb1b0_0
  - sqlite=3.33.0=h62c20be_0
  - sqlparse=0.4.1=py_0
  - statsmodels=0.12.0=py38h7b6447c_0
  - tabulate=0.8.7=py38h06a4308_0
  - threadpoolctl=2.1.0=pyh5ca1d4c_0
  - tk=8.6.10=hbc83047_0
  - tornado=6.0.4=py38h7b6447c_1
  - tqdm=4.50.2=py_0
  - traitlets=5.0.5=pyhd3eb1b0_0
  - typing-extensions=3.7.4.3=hd3eb1b0_0
  - typing_extensions=3.7.4.3=pyh06a4308_0
  - unixodbc=2.3.9=h7b6447c_0
  - urllib3=1.25.11=py_0
  - wcwidth=0.2.5=py_0
  - websocket-client=0.57.0=py38_2
  - werkzeug=1.0.1=pyhd3eb1b0_0
  - wheel=0.35.1=pyhd3eb1b0_0
  - wrapt=1.12.1=py38h7b6447c_1
  - xz=5.2.5=h7b6447c_0
  - yarl=1.6.3=py38h27cfd23_0
  - zeromq=4.3.3=he6710b0_3
  - zipp=3.4.0=pyhd3eb1b0_0
  - zlib=1.2.11=h7b6447c_3
  - zstd=1.4.5=h9ceee32_0
  - pip:
      - argon2-cffi==20.1.0
      - astunparse==1.6.3
      - async-generator==1.10
      - azure-core==1.11.0
      - azure-storage-blob==12.7.1
      - bleach==3.3.0
      - bottleneck==1.3.2
      - convertdate==2.3.2
      - databricks-cli==0.14.3
      - defusedxml==0.7.1
      - diskcache==5.2.1
      - docker==4.4.4
      - facets-overview==1.0.0
      - flatbuffers==1.12
      - grpcio==1.34.1
      - h5py==3.1.0
      - hijri-converter==2.1.3
      - holidays==0.10.5.2
      - horovod==0.22.1
      - htmlmin==0.1.12
      - imagehash==4.2.0
      - ipywidgets==7.6.3
      - joblibspark==0.3.0
      - jsonschema==3.2.0
      - jupyterlab-pygments==0.1.2
      - jupyterlab-widgets==1.0.0
      - keras-nightly==2.5.0.dev2021032900
      - keras-preprocessing==1.1.2
      - koalas==1.8.1
      - korean-lunar-calendar==0.2.1
      - llvmlite==0.36.0
      - missingno==0.4.2
      - mistune==0.8.4
      - mleap==0.17.0
      - mlflow-skinny==1.18.0
      - msrest==0.6.21
      - multimethod==1.4
      - nbclient==0.5.3
      - nbconvert==6.1.0
      - nbformat==5.1.3
      - nest-asyncio==1.5.1
      - notebook==6.4.0
      - numba==0.53.1
      - opt-einsum==3.3.0
      - pandas-profiling==3.0.0
      - pandocfilters==1.4.3
      - petastorm==0.11.1
      - phik==0.11.2
      - pyarrow==1.0.1
      - pydantic==1.8.2
      - pymeeus==0.5.11
      - pyrsistent==0.17.3
      - pywavelets==1.1.1
      - pyyaml==5.4.1
      - querystring-parser==1.2.4
      - seaborn==0.10.0
      - send2trash==1.7.1
      - shap==0.39.0
      - slicer==0.0.7
      - spark-tensorflow-distributor==0.1.0
      - tangled-up-in-unicode==0.1.0
      - tensorboard==2.5.0
      - tensorboard-data-server==0.6.1
      - tensorboard-plugin-wit==1.8.0
      - tensorflow==2.5.0
      - tensorflow-estimator==2.5.0
      - termcolor==1.1.0
      - terminado==0.10.1
      - testpath==0.5.0
      - torch==1.9.0
      - torchvision==0.10.0
      - visions==0.7.1
      - webencodings==0.5.1
      - widgetsnbextension==3.5.1
      - xgboost==1.4.2
prefix: /databricks/conda/envs/databricks-ml-gpu

Paket Spark yang berisi modul Python

Pustaka R

Pustaka R identik dengan Pustaka R di Databricks Runtime 8.4.

Pustaka Java dan Scala (Kluster Scala 2.12)

Selain pustaka Java dan Skala di Databricks Runtime 8.4, Databricks Runtime 8.4 ML berisi JAR berikut:

Kluster CPU

Kluster GPU