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Databricks Runtime 7.1 untuk ML (EoS)

  • Artikel

Catatan

Dukungan untuk versi Databricks Runtime ini telah berakhir. Untuk tanggal akhir dukungan, lihat Riwayat akhir dukungan. Untuk semua versi Runtime Databricks yang didukung, lihat Versi dan kompatibilitas catatan rilis Databricks Runtime.

Databricks merilis versi ini pada Juli 2020.

Databricks Runtime 7.1 untuk Pembelajaran Mesin menyediakan lingkungan siap pakai untuk pembelajaran mesin dan ilmu data berdasarkan Databricks Runtime 7.1 (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 baru dan perubahan besar

Databricks Runtime 7.1 ML dibangun di atas Runtime Databricks 7.1. Untuk informasi tentang apa yang baru di Databricks Runtime 7.1, termasuk Apache Spark MLlib dan SparkR, lihat catatan rilis Databricks Runtime 7.1 (EoS).

Perubahan besar pada lingkungan Phyton ML Databricks Runtime

Bagian ini menjelaskan perubahan besar pada lingkungan Databricks Runtime ML Python yang diinstal dibandingkan dengan Databricks Runtime 7.0 ML (EoS). Anda juga harus meninjau perubahan besar pada lingkungan Databricks Runtime Python di Databricks Runtime 7.1 (EoS). Untuk daftar lengkap paket Python yang diinstal dan versinya, lihat pustaka Python .

perintah ajaib pip dan conda sekarang diaktifkan secara default (Pratinjau Umum)

Di Databricks Runtime ML 6.4 ke atas, perintah ajaib %pip dan %conda tersedia melalui pengaturan konfigurasi kluster. Perintah tersebut sekarang diaktifkan secara default. Untuk informasi selengkapnya, lihat Pustaka Python cakupan buku catatan.

Paket Phyton ditingkatkan

  • pillow 7.0.0 -> 7.1.0
  • pytorch 1.5.0 -> 1.5.1
  • torchvision 0.6.0 -> 0.6.1
  • horovod 0.19.1 -> 0.19.5
  • mlflow 1.8.0 -> 1.9.1

Paket Python yang ditambahkan

  • spark-tensorflow-distributor: 0.1.0

Perubahan pada paket ML Spark, pustaka Java, dan Scala

Paket-paket berikut ditingkatkan:

  • mlflow-client: 1.9.1

Lingkungan sistem

Lingkungan sistem di Databricks Runtime 7.1 ML berbeda dari Databricks Runtime 7.1 sebagai berikut:

Pustaka

Bagian berikut mencantumkan pustaka yang disertakan dalam Databricks Runtime 7.1 ML, yang berbeda dari yang disertakan dalam Databricks Runtime 7.1.

Di bagian ini:

Pustaka tingkat atas

Databricks Runtime 7.1 ML mencakup pustaka tingkat atas berikut:

Pustaka Python

Databricks Runtime 7.1 ML menggunakan Conda untuk manajemen paket Phyton dan mencakup banyak paket ML populer. Bagian berikut menjelaskan lingkungan Conda untuk Databricks Runtime 7.1 ML.

Python pada kluster CPU

name: databricks-ml
channels:
  - pytorch
  - defaults
dependencies:
  - _libgcc_mutex=0.1=main
  - absl-py=0.9.0=py37_0
  - asn1crypto=1.3.0=py37_0
  - astor=0.8.0=py37_0
  - backcall=0.1.0=py37_0
  - backports=1.0=py_2
  - bcrypt=3.1.7=py37h7b6447c_1
  - blas=1.0=mkl
  - blinker=1.4=py37_0
  - boto3=1.12.0=py_0
  - botocore=1.15.0=py_0
  - c-ares=1.15.0=h7b6447c_1001
  - ca-certificates=2020.6.24=0
  - cachetools=4.1.0=py_1
  - certifi=2020.6.20=py37_0
  - cffi=1.14.0=py37h2e261b9_0
  - chardet=3.0.4=py37_1003
  - click=7.0=py37_0
  - cloudpickle=1.3.0=py_0
  - configparser=3.7.4=py37_0
  - cpuonly=1.0=0
  - cryptography=2.8=py37h1ba5d50_0
  - cycler=0.10.0=py37_0
  - cython=0.29.15=py37he6710b0_0
  - decorator=4.4.1=py_0
  - dill=0.3.1.1=py37_1
  - docutils=0.15.2=py37_0
  - entrypoints=0.3=py37_0
  - flask=1.1.1=py_1
  - freetype=2.9.1=h8a8886c_1
  - future=0.18.2=py37_1
  - gast=0.3.3=py_0
  - gitdb=4.0.5=py_0
  - gitdb2=4.0.2=py_0
  - gitpython=3.0.5=py_0
  - google-auth=1.11.2=py_0
  - google-auth-oauthlib=0.4.1=py_2
  - google-pasta=0.2.0=py_0
  - grpcio=1.27.2=py37hf8bcb03_0
  - gunicorn=20.0.4=py37_0
  - h5py=2.10.0=py37h7918eee_0
  - hdf5=1.10.4=hb1b8bf9_0
  - icu=58.2=he6710b0_3
  - idna=2.8=py37_0
  - intel-openmp=2020.0=166
  - ipykernel=5.1.4=py37h39e3cac_0
  - ipython=7.12.0=py37h5ca1d4c_0
  - ipython_genutils=0.2.0=py37_0
  - isodate=0.6.0=py_1
  - itsdangerous=1.1.0=py37_0
  - jedi=0.14.1=py37_0
  - jinja2=2.11.1=py_0
  - jmespath=0.9.4=py_0
  - joblib=0.14.1=py_0
  - jpeg=9b=h024ee3a_2
  - jupyter_client=5.3.4=py37_0
  - jupyter_core=4.6.1=py37_0
  - kiwisolver=1.1.0=py37he6710b0_0
  - krb5=1.16.4=h173b8e3_0
  - ld_impl_linux-64=2.33.1=h53a641e_7
  - libedit=3.1.20181209=hc058e9b_0
  - libffi=3.2.1=hd88cf55_4
  - libgcc-ng=9.1.0=hdf63c60_0
  - libgfortran-ng=7.3.0=hdf63c60_0
  - libpng=1.6.37=hbc83047_0
  - libpq=11.2=h20c2e04_0
  - libprotobuf=3.11.4=hd408876_0
  - libsodium=1.0.16=h1bed415_0
  - libstdcxx-ng=9.1.0=hdf63c60_0
  - libtiff=4.1.0=h2733197_0
  - lightgbm=2.3.0=py37he6710b0_0
  - lz4-c=1.8.1.2=h14c3975_0
  - mako=1.1.2=py_0
  - markdown=3.1.1=py37_0
  - markupsafe=1.1.1=py37h7b6447c_0
  - matplotlib-base=3.1.3=py37hef1b27d_0
  - mkl=2020.0=166
  - mkl-service=2.3.0=py37he904b0f_0
  - mkl_fft=1.0.15=py37ha843d7b_0
  - mkl_random=1.1.0=py37hd6b4f25_0
  - ncurses=6.2=he6710b0_1
  - networkx=2.4=py_0
  - ninja=1.9.0=py37hfd86e86_0
  - nltk=3.4.5=py37_0
  - numpy=1.18.1=py37h4f9e942_0
  - numpy-base=1.18.1=py37hde5b4d6_1
  - oauthlib=3.1.0=py_0
  - olefile=0.46=py37_0
  - openssl=1.1.1g=h7b6447c_0
  - packaging=20.1=py_0
  - pandas=1.0.1=py37h0573a6f_0
  - paramiko=2.7.1=py_0
  - parso=0.5.2=py_0
  - patsy=0.5.1=py37_0
  - pexpect=4.8.0=py37_0
  - pickleshare=0.7.5=py37_0
  - pillow=7.0.0=py37hb39fc2d_0
  - pip=20.0.2=py37_3
  - plotly=4.8.1=py_0
  - prompt_toolkit=3.0.3=py_0
  - protobuf=3.11.4=py37he6710b0_0
  - psutil=5.6.7=py37h7b6447c_0
  - psycopg2=2.8.4=py37h1ba5d50_0
  - ptyprocess=0.6.0=py37_0
  - pyasn1=0.4.8=py_0
  - pyasn1-modules=0.2.7=py_0
  - pycparser=2.19=py37_0
  - pygments=2.5.2=py_0
  - pyjwt=1.7.1=py37_0
  - pynacl=1.3.0=py37h7b6447c_0
  - pyodbc=4.0.30=py37he6710b0_0
  - pyopenssl=19.1.0=py37_0
  - pyparsing=2.4.6=py_0
  - pysocks=1.7.1=py37_0
  - python=3.7.6=h0371630_2
  - python-dateutil=2.8.1=py_0
  - python-editor=1.0.4=py_0
  - pytorch=1.5.1=py3.7_cpu_0
  - pytz=2019.3=py_0
  - pyzmq=18.1.1=py37he6710b0_0
  - readline=7.0=h7b6447c_5
  - requests=2.22.0=py37_1
  - requests-oauthlib=1.3.0=py_0
  - retrying=1.3.3=py37_2
  - rsa=4.0=py_0
  - s3transfer=0.3.3=py37_0
  - scikit-learn=0.22.1=py37hd81dba3_0
  - scipy=1.4.1=py37h0b6359f_0
  - setuptools=45.2.0=py37_0
  - simplejson=3.17.0=py37h7b6447c_0
  - six=1.14.0=py37_0
  - smmap=3.0.2=py_0
  - sqlite=3.31.1=h62c20be_1
  - sqlparse=0.3.0=py_0
  - statsmodels=0.11.0=py37h7b6447c_0
  - tabulate=0.8.3=py37_0
  - tk=8.6.8=hbc83047_0
  - torchvision=0.6.1=py37_cpu
  - tornado=6.0.3=py37h7b6447c_3
  - tqdm=4.42.1=py_0
  - traitlets=4.3.3=py37_0
  - unixodbc=2.3.7=h14c3975_0
  - urllib3=1.25.8=py37_0
  - wcwidth=0.1.8=py_0
  - websocket-client=0.56.0=py37_0
  - werkzeug=1.0.0=py_0
  - wheel=0.34.2=py37_0
  - wrapt=1.11.2=py37h7b6447c_0
  - xz=5.2.4=h14c3975_4
  - zeromq=4.3.1=he6710b0_3
  - zlib=1.2.11=h7b6447c_3
  - zstd=1.3.7=h0b5b093_0
  - pip:
      - astunparse==1.6.3
      - azure-core==1.6.0
      - azure-storage-blob==12.3.2
      - databricks-cli==0.11.0
      - diskcache==4.1.0
      - docker==4.2.2
      - gorilla==0.3.0
      - horovod==0.19.5
      - hyperopt==0.2.4.db2
      - keras-preprocessing==1.1.2
      - koalas==1.0.1
      - mleap==0.16.0
      - mlflow==1.9.1
      - msrest==0.6.17
      - opt-einsum==3.2.1
      - petastorm==0.9.2
      - pyarrow==0.15.1
      - pyyaml==5.3.1
      - querystring-parser==1.2.4
      - seaborn==0.10.0
      - spark-tensorflow-distributor==0.1.0
      - sparkdl==2.1.0-db1
      - tensorboard==2.2.2
      - tensorboard-plugin-wit==1.7.0
      - tensorflow-cpu==2.2.0
      - tensorflow-estimator==2.2.0
      - termcolor==1.1.0
      - xgboost==1.1.1
prefix: /databricks/conda/envs/databricks-ml

Python pada kluster GPU

name: databricks-ml-gpu
channels:
  - pytorch
  - defaults
dependencies:
  - _libgcc_mutex=0.1=main
  - absl-py=0.9.0=py37_0
  - asn1crypto=1.3.0=py37_0
  - astor=0.8.0=py37_0
  - backcall=0.1.0=py37_0
  - backports=1.0=py_2
  - bcrypt=3.1.7=py37h7b6447c_1
  - blas=1.0=mkl
  - blinker=1.4=py37_0
  - boto3=1.12.0=py_0
  - botocore=1.15.0=py_0
  - c-ares=1.15.0=h7b6447c_1001
  - ca-certificates=2020.6.24=0
  - cachetools=4.1.0=py_1
  - certifi=2020.6.20=py37_0
  - cffi=1.14.0=py37h2e261b9_0
  - chardet=3.0.4=py37_1003
  - click=7.0=py37_0
  - cloudpickle=1.3.0=py_0
  - configparser=3.7.4=py37_0
  - cryptography=2.8=py37h1ba5d50_0
  - cudatoolkit=10.1.243=h6bb024c_0
  - cycler=0.10.0=py37_0
  - cython=0.29.15=py37he6710b0_0
  - decorator=4.4.1=py_0
  - dill=0.3.1.1=py37_1
  - docutils=0.15.2=py37_0
  - entrypoints=0.3=py37_0
  - flask=1.1.1=py_1
  - freetype=2.9.1=h8a8886c_1
  - future=0.18.2=py37_1
  - gast=0.3.3=py_0
  - gitdb=4.0.5=py_0
  - gitdb2=4.0.2=py_0
  - gitpython=3.0.5=py_0
  - google-auth=1.11.2=py_0
  - google-auth-oauthlib=0.4.1=py_2
  - google-pasta=0.2.0=py_0
  - grpcio=1.27.2=py37hf8bcb03_0
  - gunicorn=20.0.4=py37_0
  - h5py=2.10.0=py37h7918eee_0
  - hdf5=1.10.4=hb1b8bf9_0
  - icu=58.2=he6710b0_3
  - idna=2.8=py37_0
  - intel-openmp=2020.0=166
  - ipykernel=5.1.4=py37h39e3cac_0
  - ipython=7.12.0=py37h5ca1d4c_0
  - ipython_genutils=0.2.0=py37_0
  - isodate=0.6.0=py_1
  - itsdangerous=1.1.0=py37_0
  - jedi=0.14.1=py37_0
  - jinja2=2.11.1=py_0
  - jmespath=0.9.4=py_0
  - joblib=0.14.1=py_0
  - jpeg=9b=h024ee3a_2
  - jupyter_client=5.3.4=py37_0
  - jupyter_core=4.6.1=py37_0
  - kiwisolver=1.1.0=py37he6710b0_0
  - krb5=1.16.4=h173b8e3_0
  - ld_impl_linux-64=2.33.1=h53a641e_7
  - libedit=3.1.20181209=hc058e9b_0
  - libffi=3.2.1=hd88cf55_4
  - libgcc-ng=9.1.0=hdf63c60_0
  - libgfortran-ng=7.3.0=hdf63c60_0
  - libpng=1.6.37=hbc83047_0
  - libpq=11.2=h20c2e04_0
  - libprotobuf=3.11.4=hd408876_0
  - libsodium=1.0.16=h1bed415_0
  - libstdcxx-ng=9.1.0=hdf63c60_0
  - libtiff=4.1.0=h2733197_0
  - lightgbm=2.3.0=py37he6710b0_0
  - lz4-c=1.8.1.2=h14c3975_0
  - mako=1.1.2=py_0
  - markdown=3.1.1=py37_0
  - markupsafe=1.1.1=py37h7b6447c_0
  - matplotlib-base=3.1.3=py37hef1b27d_0
  - mkl=2020.0=166
  - mkl-service=2.3.0=py37he904b0f_0
  - mkl_fft=1.0.15=py37ha843d7b_0
  - mkl_random=1.1.0=py37hd6b4f25_0
  - ncurses=6.2=he6710b0_1
  - networkx=2.4=py_0
  - ninja=1.9.0=py37hfd86e86_0
  - nltk=3.4.5=py37_0
  - numpy=1.18.1=py37h4f9e942_0
  - numpy-base=1.18.1=py37hde5b4d6_1
  - oauthlib=3.1.0=py_0
  - olefile=0.46=py37_0
  - openssl=1.1.1g=h7b6447c_0
  - packaging=20.1=py_0
  - pandas=1.0.1=py37h0573a6f_0
  - paramiko=2.7.1=py_0
  - parso=0.5.2=py_0
  - patsy=0.5.1=py37_0
  - pexpect=4.8.0=py37_0
  - pickleshare=0.7.5=py37_0
  - pillow=7.0.0=py37hb39fc2d_0
  - pip=20.0.2=py37_3
  - plotly=4.8.1=py_0
  - prompt_toolkit=3.0.3=py_0
  - protobuf=3.11.4=py37he6710b0_0
  - psutil=5.6.7=py37h7b6447c_0
  - psycopg2=2.8.4=py37h1ba5d50_0
  - ptyprocess=0.6.0=py37_0
  - pyasn1=0.4.8=py_0
  - pyasn1-modules=0.2.7=py_0
  - pycparser=2.19=py37_0
  - pygments=2.5.2=py_0
  - pyjwt=1.7.1=py37_0
  - pynacl=1.3.0=py37h7b6447c_0
  - pyodbc=4.0.30=py37he6710b0_0
  - pyopenssl=19.1.0=py37_0
  - pyparsing=2.4.6=py_0
  - pysocks=1.7.1=py37_0
  - python=3.7.6=h0371630_2
  - python-dateutil=2.8.1=py_0
  - python-editor=1.0.4=py_0
  - pytorch=1.5.1=py3.7_cuda10.1.243_cudnn7.6.3_0
  - pytz=2019.3=py_0
  - pyzmq=18.1.1=py37he6710b0_0
  - readline=7.0=h7b6447c_5
  - requests=2.22.0=py37_1
  - requests-oauthlib=1.3.0=py_0
  - retrying=1.3.3=py37_2
  - rsa=4.0=py_0
  - s3transfer=0.3.3=py37_0
  - scikit-learn=0.22.1=py37hd81dba3_0
  - scipy=1.4.1=py37h0b6359f_0
  - setuptools=45.2.0=py37_0
  - simplejson=3.17.0=py37h7b6447c_0
  - six=1.14.0=py37_0
  - smmap=3.0.2=py_0
  - sqlite=3.31.1=h62c20be_1
  - sqlparse=0.3.0=py_0
  - statsmodels=0.11.0=py37h7b6447c_0
  - tabulate=0.8.3=py37_0
  - tk=8.6.8=hbc83047_0
  - torchvision=0.6.1=py37_cu101
  - tornado=6.0.3=py37h7b6447c_3
  - tqdm=4.42.1=py_0
  - traitlets=4.3.3=py37_0
  - unixodbc=2.3.7=h14c3975_0
  - urllib3=1.25.8=py37_0
  - wcwidth=0.1.8=py_0
  - websocket-client=0.56.0=py37_0
  - werkzeug=1.0.0=py_0
  - wheel=0.34.2=py37_0
  - wrapt=1.11.2=py37h7b6447c_0
  - xz=5.2.4=h14c3975_4
  - zeromq=4.3.1=he6710b0_3
  - zlib=1.2.11=h7b6447c_3
  - zstd=1.3.7=h0b5b093_0
  - pip:
      - astunparse==1.6.3
      - azure-core==1.6.0
      - azure-storage-blob==12.3.2
      - databricks-cli==0.11.0
      - diskcache==4.1.0
      - docker==4.2.2
      - gorilla==0.3.0
      - horovod==0.19.5
      - hyperopt==0.2.4.db1
      - keras-preprocessing==1.1.2
      - koalas==1.0.1
      - mleap==0.16.0
      - mlflow==1.9.1
      - msrest==0.6.17
      - opt-einsum==3.2.1
      - petastorm==0.9.2
      - pyarrow==0.15.1
      - pyyaml==5.3.1
      - querystring-parser==1.2.4
      - seaborn==0.10.0
      - spark-tensorflow-distributor==0.1.0
      - sparkdl==2.1.0-db1
      - tensorboard==2.2.2
      - tensorboard-plugin-wit==1.7.0
      - tensorflow==2.2.0
      - tensorflow-estimator==2.2.0
      - termcolor==1.1.0
      - xgboost==1.1.1
prefix: /databricks/conda/envs/databricks-ml-gpu

Paket Spark yang berisi modul Python

Paket Spark Modul Python Versi
graphframes graphframes 0.8.0-db2-spark3.0

Pustaka R

Pustaka R ini identik dengan Pustaka R di Databricks Runtime 7.1.

Pustaka Java dan Scala (Kluster Scala 2.12)

Selain pustaka Java dan Scala di Databricks Runtime 7.1, Databricks Runtime 7.1 ML berisi JAR berikut:

ID Grup ID Artefak Versi
com.typesafe.akka akka-actor_2.12 2.5.23
ml.combust.mleap mleap-databricks-runtime_2.12 0.17.1-4882dc3
ml.dmlc xgboost4j-spark_2.12 1.0.0
ml.dmlc xgboost4j_2.12 1.0.0
org.mlflow mlflow-client 1.9.1
org.scala-lang.modules scala-java8-compat_2.12 0.8.0
org.tensorflow spark-tensorflow-connector_2.12 1.15.0