ML için Databricks Runtime 6.4 (desteklenmiyor)

Databricks bu görüntüyü Şubat 2020'de yayımladı.

Machine Learning için Databricks Runtime 6.4, Databricks Runtime 6.4(desteklenmeyen) tabanlı makine öğrenmesi ve veri bilimi için kullanıma hazır bir ortam sağlar. Databricks Runtime ML, TensorFlow, PyTorch, Keras ve XGBoost gibi birçok popüler makine öğrenmesi kitaplığı içerir. Horovod kullanarak dağıtılmış derin öğrenme eğitimini de destekler.

Databricks Runtime ML kümesi oluşturma yönergeleri de dahil olmak üzere daha fazla bilgi için bkz . Databricks'te AI ve Machine Learning.

Yeni özellikler

Databricks Runtime 6.4 ML, Databricks Runtime 6.4'ün üzerine kurulmuştur. Databricks Runtime 6.4'teki yenilikler hakkında bilgi için bkz . Databricks Runtime 6.4 (desteklenmeyen) sürüm notları.

İyileştirmeler

Kullanımdan kaldırılan özellikler

• Tek başına keras paket kullanım dışıdır ve ML için Databricks Runtime'ın gelecek ana sürümünde kaldırılacaktır. Databricks bunun yerine kullanmanızı tensorflow.kerasönerir.
• Paket pymongo kullanım dışı bırakılmıştır ve ML için Databricks Runtime'ın gelecek ana sürümünde kaldırılacaktır.

Yükseltilen makine öğrenmesi kitaplıkları

• PyTorch: 1.3.1 - 1.4.0
• Horovod: 0.18.2 - 1.19.0

Sistem ortamı

Databricks Runtime 6.4 ML'deki sistem ortamı, Databricks Runtime 6.4'ten aşağıdaki gibi farklıdır:

• DBUtils: Kitaplık yardımcı programını (dbutils.library) (eski) içermez.
• GPU kümeleri için aşağıdaki NVIDIA GPU kitaplıkları:
  • CUDA 10.0
  • cuDNN 7.6.4
  • NCCL 2.4.8

Kitaplık

Aşağıdaki bölümlerde Databricks Runtime 6.4 ML'de bulunan ve Databricks Runtime 6.4'teki kitaplıklardan farklı kitaplıklar listelenmiştir.

Bu bölümde:

• Üst katman kitaplıkları
• Python kitaplıkları
• R kitaplıkları
• Java ve Scala kitaplıkları (Scala 2.11 kümesi)

Üst katman kitaplıkları

Databricks Runtime 6.4 ML aşağıdaki üst katman kitaplıklarını içerir:

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

Python kitaplıkları

Databricks Runtime 6.4 ML, Python paket yönetimi için Conda kullanır ve birçok popüler ML paketi içerir. Aşağıdaki bölümde Databricks Runtime 6.4 ML için Conda ortamı açıklanmaktadır.

CPU kümelerinde Python

name: databricks-ml
channels:
  - Databricks
  - pytorch
  - defaults
dependencies:
  - _libgcc_mutex=0.1=main
  - _py-xgboost-mutex=2.0=cpu_0
  - _tflow_select=2.3.0=mkl
  - absl-py=0.9.0=py37_0
  - asn1crypto=0.24.0=py37_0
  - astor=0.8.0=py37_0
  - backcall=0.1.0=py37_0
  - backports=1.0=py_2
  - bcrypt=3.1.7=py37h7b6447c_0
  - blas=1.0=mkl
  - boto=2.49.0=py37_0
  - boto3=1.9.162=py_0
  - botocore=1.12.163=py_0
  - c-ares=1.15.0=h7b6447c_1001
  - ca-certificates=2019.1.23=0
  - certifi=2019.3.9=py37_0
  - cffi=1.12.2=py37h2e261b9_1
  - chardet=3.0.4=py37_1003
  - click=7.0=py_0
  - cloudpickle=0.8.0=py37_0
  - colorama=0.4.1=py_0
  - configparser=3.7.4=py37_0
  - cpuonly=1.0=0
  - cryptography=2.6.1=py37h1ba5d50_0
  - cycler=0.10.0=py37_0
  - cython=0.29.6=py37he6710b0_0
  - decorator=4.4.0=py37_1
  - docutils=0.14=py37_0
  - entrypoints=0.3=py37_0
  - et_xmlfile=1.0.1=py37_0
  - flask=1.0.2=py37_1
  - freetype=2.9.1=h8a8886c_1
  - future=0.17.1=py37_0
  - gast=0.2.2=py37_0
  - gitdb2=2.0.6=py_0
  - gitpython=2.1.11=py37_0
  - google-pasta=0.1.8=py_0
  - grpcio=1.16.1=py37hf8bcb03_1
  - gunicorn=19.9.0=py37_0
  - h5py=2.9.0=py37h7918eee_0
  - hdf5=1.10.4=hb1b8bf9_0
  - html5lib=1.0.1=py_0
  - icu=58.2=h9c2bf20_1
  - idna=2.8=py37_0
  - intel-openmp=2019.3=199
  - ipykernel=5.1.0=py37h39e3cac_0
  - ipython=7.4.0=py37h39e3cac_0
  - ipython_genutils=0.2.0=py37_0
  - itsdangerous=1.1.0=py_0
  - jdcal=1.4=py37_0
  - jedi=0.13.3=py37_0
  - jinja2=2.10=py37_0
  - jmespath=0.9.4=py_0
  - jpeg=9b=h024ee3a_2
  - jupyter_client=5.2.4=py37_0
  - jupyter_core=4.4.0=py37_0
  - keras-applications=1.0.8=py_0
  - keras-preprocessing=1.1.0=py_1
  - kiwisolver=1.0.1=py37hf484d3e_0
  - krb5=1.16.1=h173b8e3_7
  - libedit=3.1.20181209=hc058e9b_0
  - libffi=3.2.1=hd88cf55_4
  - libgcc-ng=8.2.0=hdf63c60_1
  - libgfortran-ng=7.3.0=hdf63c60_0
  - libpng=1.6.36=hbc83047_0
  - libpq=11.2=h20c2e04_0
  - libprotobuf=3.11.4=hd408876_0
  - libsodium=1.0.16=h1bed415_0
  - libstdcxx-ng=8.2.0=hdf63c60_1
  - libtiff=4.0.10=h2733197_2
  - libxgboost=0.90=he6710b0_1
  - libxml2=2.9.9=hea5a465_1
  - libxslt=1.1.33=h7d1a2b0_0
  - llvmlite=0.28.0=py37hd408876_0
  - lxml=4.3.2=py37hefd8a0e_0
  - mako=1.0.10=py_0
  - markdown=3.1.1=py37_0
  - markupsafe=1.1.1=py37h7b6447c_0
  - mkl=2019.3=199
  - mkl_fft=1.0.10=py37ha843d7b_0
  - mkl_random=1.0.2=py37hd81dba3_0
  - ncurses=6.1=he6710b0_1
  - networkx=2.2=py37_1
  - ninja=1.9.0=py37hfd86e86_0
  - nose=1.3.7=py37_2
  - numba=0.43.1=py37h962f231_0
  - numpy=1.16.2=py37h7e9f1db_0
  - numpy-base=1.16.2=py37hde5b4d6_0
  - olefile=0.46=py_0
  - openpyxl=2.6.1=py37_1
  - openssl=1.1.1b=h7b6447c_1
  - opt_einsum=3.1.0=py_0
  - pandas=0.24.2=py37he6710b0_0
  - paramiko=2.4.2=py37_0
  - parso=0.3.4=py37_0
  - pathlib2=2.3.3=py37_0
  - patsy=0.5.1=py37_0
  - pexpect=4.6.0=py37_0
  - pickleshare=0.7.5=py37_0
  - pillow=5.4.1=py37h34e0f95_0
  - pip=19.0.3=py37_0
  - ply=3.11=py37_0
  - prompt_toolkit=2.0.9=py37_0
  - protobuf=3.11.4=py37he6710b0_0
  - psutil=5.6.1=py37h7b6447c_0
  - psycopg2=2.7.6.1=py37h1ba5d50_0
  - ptyprocess=0.6.0=py37_0
  - py-xgboost=0.90=py37he6710b0_1
  - py-xgboost-cpu=0.90=py37_1
  - pyasn1=0.4.8=py_0
  - pycparser=2.19=py_0
  - pygments=2.3.1=py37_0
  - pymongo=3.8.0=py37he6710b0_1
  - pynacl=1.3.0=py37h7b6447c_0
  - pyopenssl=19.0.0=py37_0
  - pyparsing=2.3.1=py37_0
  - pysocks=1.6.8=py37_0
  - python=3.7.3=h0371630_0
  - python-dateutil=2.8.0=py37_0
  - python-editor=1.0.4=py_0
  - pytorch=1.4.0=py3.7_cpu_0
  - pytz=2018.9=py37_0
  - pyyaml=5.1=py37h7b6447c_0
  - pyzmq=18.0.0=py37he6710b0_0
  - readline=7.0=h7b6447c_5
  - requests=2.21.0=py37_0
  - s3transfer=0.2.1=py37_0
  - scikit-learn=0.20.3=py37hd81dba3_0
  - scipy=1.2.1=py37h7c811a0_0
  - setuptools=40.8.0=py37_0
  - simplejson=3.16.0=py37h14c3975_0
  - singledispatch=3.4.0.3=py37_0
  - six=1.12.0=py37_0
  - smmap2=2.0.5=py_0
  - sqlite=3.27.2=h7b6447c_0
  - sqlparse=0.3.0=py_0
  - statsmodels=0.9.0=py37h035aef0_0
  - tabulate=0.8.3=py37_0
  - tensorboard=1.15.0+db2=pyhb230dea_0
  - tensorflow=1.15.0+db2=mkl_py37hc5fbf04_0
  - tensorflow-base=1.15.0+db2=mkl_py37h2ae1e84_0
  - tensorflow-estimator=1.15.1+db2=pyh2649769_0
  - tensorflow-mkl=1.15.0+db2=h4fcabd2_0
  - termcolor=1.1.0=py37_1
  - tk=8.6.8=hbc83047_0
  - torchvision=0.5.0=py37_cpu
  - tornado=6.0.2=py37h7b6447c_0
  - tqdm=4.31.1=py37_1
  - traitlets=4.3.2=py37_0
  - urllib3=1.24.1=py37_0
  - virtualenv=16.0.0=py37_0
  - wcwidth=0.1.7=py37_0
  - webencodings=0.5.1=py37_1
  - websocket-client=0.56.0=py37_0
  - werkzeug=0.14.1=py37_0
  - wheel=0.33.1=py37_0
  - wrapt=1.11.1=py37h7b6447c_0
  - xz=5.2.4=h14c3975_4
  - yaml=0.1.7=had09818_2
  - zeromq=4.3.1=he6710b0_3
  - zlib=1.2.11=h7b6447c_3
  - zstd=1.3.7=h0b5b093_0
  - pip:
    - argparse==1.4.0
    - databricks-cli==0.9.1
    - deprecated==1.2.7
    - docker==4.2.0
    - fusepy==2.0.4
    - gorilla==0.3.0
    - horovod==0.19.0
    - hyperopt==0.2.2.db1
    - keras==2.2.5
    - matplotlib==3.0.3
    - mleap==0.8.1
    - mlflow==1.5.0
    - nose-exclude==0.5.0
    - pyarrow==0.13.0
    - querystring-parser==1.2.4
    - seaborn==0.9.0
    - tensorboardx==1.9
prefix: /databricks/conda/envs/databricks-ml

GPU kümelerinde Python

name: databricks-ml-gpu
channels:
  - Databricks
  - pytorch
  - defaults
dependencies:
  - _libgcc_mutex=0.1=main
  - _py-xgboost-mutex=1.0=gpu_0
  - _tflow_select=2.1.0=gpu
  - absl-py=0.9.0=py37_0
  - asn1crypto=0.24.0=py37_0
  - astor=0.8.0=py37_0
  - backcall=0.1.0=py37_0
  - backports=1.0=py_2
  - bcrypt=3.1.7=py37h7b6447c_0
  - blas=1.0=mkl
  - boto=2.49.0=py37_0
  - boto3=1.9.162=py_0
  - botocore=1.12.163=py_0
  - c-ares=1.15.0=h7b6447c_1001
  - ca-certificates=2019.1.23=0
  - certifi=2019.3.9=py37_0
  - cffi=1.12.2=py37h2e261b9_1
  - chardet=3.0.4=py37_1003
  - click=7.0=py_0
  - cloudpickle=0.8.0=py37_0
  - colorama=0.4.1=py_0
  - configparser=3.7.4=py37_0
  - cryptography=2.6.1=py37h1ba5d50_0
  - cudatoolkit=10.0.130=0
  - cudnn=7.6.4=cuda10.0_0
  - cupti=10.0.130=0
  - cycler=0.10.0=py37_0
  - cython=0.29.6=py37he6710b0_0
  - decorator=4.4.0=py37_1
  - docutils=0.14=py37_0
  - entrypoints=0.3=py37_0
  - et_xmlfile=1.0.1=py37_0
  - flask=1.0.2=py37_1
  - freetype=2.9.1=h8a8886c_1
  - future=0.17.1=py37_0
  - gast=0.2.2=py37_0
  - gitdb2=2.0.6=py_0
  - gitpython=2.1.11=py37_0
  - google-pasta=0.1.8=py_0
  - grpcio=1.16.1=py37hf8bcb03_1
  - gunicorn=19.9.0=py37_0
  - h5py=2.9.0=py37h7918eee_0
  - hdf5=1.10.4=hb1b8bf9_0
  - html5lib=1.0.1=py_0
  - icu=58.2=h9c2bf20_1
  - idna=2.8=py37_0
  - intel-openmp=2019.3=199
  - ipykernel=5.1.0=py37h39e3cac_0
  - ipython=7.4.0=py37h39e3cac_0
  - ipython_genutils=0.2.0=py37_0
  - itsdangerous=1.1.0=py_0
  - jdcal=1.4=py37_0
  - jedi=0.13.3=py37_0
  - jinja2=2.10=py37_0
  - jmespath=0.9.4=py_0
  - jpeg=9b=h024ee3a_2
  - jupyter_client=5.2.4=py37_0
  - jupyter_core=4.4.0=py37_0
  - keras-applications=1.0.8=py_0
  - keras-preprocessing=1.1.0=py_1
  - kiwisolver=1.0.1=py37hf484d3e_0
  - krb5=1.16.1=h173b8e3_7
  - libedit=3.1.20181209=hc058e9b_0
  - libffi=3.2.1=hd88cf55_4
  - libgcc-ng=8.2.0=hdf63c60_1
  - libgfortran-ng=7.3.0=hdf63c60_0
  - libpng=1.6.36=hbc83047_0
  - libpq=11.2=h20c2e04_0
  - libprotobuf=3.11.4=hd408876_0
  - libsodium=1.0.16=h1bed415_0
  - libstdcxx-ng=8.2.0=hdf63c60_1
  - libtiff=4.0.10=h2733197_2
  - libxgboost=0.90=h688424c_0
  - libxml2=2.9.9=hea5a465_1
  - libxslt=1.1.33=h7d1a2b0_0
  - llvmlite=0.28.0=py37hd408876_0
  - lxml=4.3.2=py37hefd8a0e_0
  - mako=1.0.10=py_0
  - markdown=3.1.1=py37_0
  - markupsafe=1.1.1=py37h7b6447c_0
  - mkl=2019.3=199
  - mkl_fft=1.0.10=py37ha843d7b_0
  - mkl_random=1.0.2=py37hd81dba3_0
  - ncurses=6.1=he6710b0_1
  - networkx=2.2=py37_1
  - ninja=1.9.0=py37hfd86e86_0
  - nose=1.3.7=py37_2
  - numba=0.43.1=py37h962f231_0
  - numpy=1.16.2=py37h7e9f1db_0
  - numpy-base=1.16.2=py37hde5b4d6_0
  - olefile=0.46=py_0
  - openpyxl=2.6.1=py37_1
  - openssl=1.1.1b=h7b6447c_1
  - opt_einsum=3.1.0=py_0
  - pandas=0.24.2=py37he6710b0_0
  - paramiko=2.4.2=py37_0
  - parso=0.3.4=py37_0
  - pathlib2=2.3.3=py37_0
  - patsy=0.5.1=py37_0
  - pexpect=4.6.0=py37_0
  - pickleshare=0.7.5=py37_0
  - pillow=5.4.1=py37h34e0f95_0
  - pip=19.0.3=py37_0
  - ply=3.11=py37_0
  - prompt_toolkit=2.0.9=py37_0
  - protobuf=3.11.4=py37he6710b0_0
  - psutil=5.6.1=py37h7b6447c_0
  - psycopg2=2.7.6.1=py37h1ba5d50_0
  - ptyprocess=0.6.0=py37_0
  - py-xgboost=0.90=py37h688424c_0
  - py-xgboost-gpu=0.90=py37h28bbb66_0
  - pyasn1=0.4.8=py_0
  - pycparser=2.19=py_0
  - pygments=2.3.1=py37_0
  - pymongo=3.8.0=py37he6710b0_1
  - pynacl=1.3.0=py37h7b6447c_0
  - pyopenssl=19.0.0=py37_0
  - pyparsing=2.3.1=py37_0
  - pysocks=1.6.8=py37_0
  - python=3.7.3=h0371630_0
  - python-dateutil=2.8.0=py37_0
  - python-editor=1.0.4=py_0
  - pytorch=1.4.0=py3.7_cuda10.0.130_cudnn7.6.3_0
  - pytz=2018.9=py37_0
  - pyyaml=5.1=py37h7b6447c_0
  - pyzmq=18.0.0=py37he6710b0_0
  - readline=7.0=h7b6447c_5
  - requests=2.21.0=py37_0
  - s3transfer=0.2.1=py37_0
  - scikit-learn=0.20.3=py37hd81dba3_0
  - scipy=1.2.1=py37h7c811a0_0
  - setuptools=40.8.0=py37_0
  - simplejson=3.16.0=py37h14c3975_0
  - singledispatch=3.4.0.3=py37_0
  - six=1.12.0=py37_0
  - smmap2=2.0.5=py_0
  - sqlite=3.27.2=h7b6447c_0
  - sqlparse=0.3.0=py_0
  - statsmodels=0.9.0=py37h035aef0_0
  - tabulate=0.8.3=py37_0
  - tensorboard=1.15.0+db2=pyhb230dea_0
  - tensorflow=1.15.0+db2=gpu_py37h9fd0ff8_0
  - tensorflow-base=1.15.0+db2=gpu_py37hd56f5dd_0
  - tensorflow-estimator=1.15.1+db2=pyh2649769_0
  - tensorflow-gpu=1.15.0+db2=h0d30ee6_0
  - termcolor=1.1.0=py37_1
  - tk=8.6.8=hbc83047_0
  - torchvision=0.5.0=py37_cu100
  - tornado=6.0.2=py37h7b6447c_0
  - tqdm=4.31.1=py37_1
  - traitlets=4.3.2=py37_0
  - urllib3=1.24.1=py37_0
  - virtualenv=16.0.0=py37_0
  - wcwidth=0.1.7=py37_0
  - webencodings=0.5.1=py37_1
  - websocket-client=0.56.0=py37_0
  - werkzeug=0.14.1=py37_0
  - wheel=0.33.1=py37_0
  - wrapt=1.11.1=py37h7b6447c_0
  - xz=5.2.4=h14c3975_4
  - yaml=0.1.7=had09818_2
  - zeromq=4.3.1=he6710b0_3
  - zlib=1.2.11=h7b6447c_3
  - zstd=1.3.7=h0b5b093_0
  - pip:
    - argparse==1.4.0
    - databricks-cli==0.9.1
    - deprecated==1.2.7
    - docker==4.2.0
    - fusepy==2.0.4
    - gorilla==0.3.0
    - horovod==0.19.0
    - hyperopt==0.2.2.db1
    - keras==2.2.5
    - matplotlib==3.0.3
    - mleap==0.8.1
    - mlflow==1.5.0
    - nose-exclude==0.5.0
    - pyarrow==0.13.0
    - querystring-parser==1.2.4
    - seaborn==0.9.0
    - tensorboardx==1.9
prefix: /databricks/conda/envs/databricks-ml-gpu

Python modülleri içeren Spark paketleri

Spark Paketi	Python Modülü	Sürüm
graf çerçeveleri	graf çerçeveleri	0.7.0-db1-spark2.4
spark-deep-learning	sparkdl	1.5.0-db12-spark2.4
tensorframes	tensorframes	0.8.2-s_2.11

R kitaplıkları

R kitaplıkları Databricks Runtime 6.4'teki R Kitaplıklarıyla aynıdır.

Java ve Scala kitaplıkları (Scala 2.11 kümesi)

Databricks Runtime 6.4'teki Java ve Scala kitaplıklarına ek olarak, Databricks Runtime 6.4 ML aşağıdaki JAR'leri içerir:

Grup Kimliği	Yapıt Kimliği	Sürüm
com.databricks	spark-deep-learning	1.5.0-db12-spark2.4
com.typesafe.akka	akka-actor_2.11	2.3.11
ml.combust.mleap	mleap-databricks-runtime_2.11	0.15.0
ml.dmlc	xgboost4j	0.90
ml.dmlc	xgboost4j-spark	0.90
org.graphframes	graphframes_2.11	0.7.0-db1-spark2.4
org.mlflow	mlflow-client	1.4.0
org.tensorflow	libtensorflow	1.15.0
org.tensorflow	libtensorflow_jni	1.15.0
org.tensorflow	spark-tensorflow-connector_2.11	1.15.0
org.tensorflow	tensorflow	1.15.0
org.tensorframes	tensorframes	0.8.2-s_2.11