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[doc] Integrate pyspark module into sphinx doc [skip ci] #8066

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Jul 17, 2022
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[doc] Integrate pyspark module into sphinx doc [skip ci] #8066

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3 changes: 2 additions & 1 deletion doc/conf.py
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Original file line number Diff line number Diff line change
Expand Up @@ -207,10 +207,11 @@
"python": ("https://docs.python.org/3.6", None),
"numpy": ("https://docs.scipy.org/doc/numpy/", None),
"scipy": ("https://docs.scipy.org/doc/scipy/reference/", None),
"pandas": ("http://pandas-docs.github.io/pandas-docs-travis/", None),
"pandas": ("https://pandas.pydata.org/pandas-docs/stable/", None),
"sklearn": ("https://scikit-learn.org/stable", None),
"dask": ("https://docs.dask.org/en/stable/", None),
"distributed": ("https://distributed.dask.org/en/stable/", None),
"pyspark": ("https://spark.apache.org/docs/latest/api/python/", None),
}


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26 changes: 26 additions & 0 deletions doc/python/python_api.rst
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Expand Up @@ -147,3 +147,29 @@ Dask API
:members:
:inherited-members:
:show-inheritance:


PySpark API
-----------

.. automodule:: xgboost.spark

.. autoclass:: xgboost.spark.SparkXGBClassifier
:members:
:inherited-members:
:show-inheritance:

.. autoclass:: xgboost.spark.SparkXGBClassifierModel
:members:
:inherited-members:
:show-inheritance:

.. autoclass:: xgboost.spark.SparkXGBRegressor
:members:
:inherited-members:
:show-inheritance:

.. autoclass:: xgboost.spark.SparkXGBRegressorModel
:members:
:inherited-members:
:show-inheritance:
4 changes: 3 additions & 1 deletion doc/requirements.txt
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Expand Up @@ -9,4 +9,6 @@ graphviz
numpy
recommonmark
xgboost_ray
sphinx-gallery
sphinx-gallery
pyspark
cloudpickle
27 changes: 16 additions & 11 deletions python-package/xgboost/spark/estimator.py
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Expand Up @@ -15,12 +15,13 @@ class SparkXGBRegressor(_SparkXGBEstimator):
"""
SparkXGBRegressor is a PySpark ML estimator. It implements the XGBoost regression
algorithm based on XGBoost python library, and it can be used in PySpark Pipeline
and PySpark ML meta algorithms like CrossValidator/TrainValidationSplit/OneVsRest.
and PySpark ML meta algorithms like :py:class:`~pyspark.ml.tuning.CrossValidator`/
:py:class:`~pyspark.ml.tuning.TrainValidationSplit`/
:py:class:`~pyspark.ml.classification.OneVsRest`

SparkXGBRegressor automatically supports most of the parameters in
`xgboost.XGBRegressor` constructor and most of the parameters used in
`xgboost.XGBRegressor` fit and predict method (see `API docs <https://xgboost.readthedocs\
.io/en/latest/python/python_api.html#xgboost.XGBRegressor>`_ for details).
:py:class:`xgboost.XGBRegressor` fit and predict method.

SparkXGBRegressor doesn't support setting `gpu_id` but support another param `use_gpu`,
see doc below for more details.
Expand Down Expand Up @@ -65,7 +66,8 @@ class SparkXGBRegressor(_SparkXGBEstimator):

.. Note:: This API is experimental.

**Examples**
Examples
--------

>>> from xgboost.spark import SparkXGBRegressor
>>> from pyspark.ml.linalg import Vectors
Expand Down Expand Up @@ -104,15 +106,16 @@ def _pyspark_model_cls(cls):


class SparkXGBClassifier(_SparkXGBEstimator, HasProbabilityCol, HasRawPredictionCol):
"""
SparkXGBClassifier is a PySpark ML estimator. It implements the XGBoost classification
algorithm based on XGBoost python library, and it can be used in PySpark Pipeline
and PySpark ML meta algorithms like CrossValidator/TrainValidationSplit/OneVsRest.
"""SparkXGBClassifier is a PySpark ML estimator. It implements the XGBoost
classification algorithm based on XGBoost python library, and it can be used in
PySpark Pipeline and PySpark ML meta algorithms like
:py:class:`~pyspark.ml.tuning.CrossValidator`/
:py:class:`~pyspark.ml.tuning.TrainValidationSplit`/
:py:class:`~pyspark.ml.classification.OneVsRest`

SparkXGBClassifier automatically supports most of the parameters in
`xgboost.XGBClassifier` constructor and most of the parameters used in
`xgboost.XGBClassifier` fit and predict method (see `API docs <https://xgboost.readthedocs\
.io/en/latest/python/python_api.html#xgboost.XGBClassifier>`_ for details).
:py:class:`xgboost.XGBClassifier` fit and predict method.

SparkXGBClassifier doesn't support setting `gpu_id` but support another param `use_gpu`,
see doc below for more details.
Expand All @@ -127,6 +130,7 @@ class SparkXGBClassifier(_SparkXGBEstimator, HasProbabilityCol, HasRawPrediction

Parameters
----------

callbacks:
The export and import of the callback functions are at best effort. For
details, see :py:attr:`xgboost.spark.SparkXGBClassifier.callbacks` param doc.
Expand Down Expand Up @@ -166,7 +170,8 @@ class SparkXGBClassifier(_SparkXGBEstimator, HasProbabilityCol, HasRawPrediction

.. Note:: This API is experimental.

**Examples**
Examples
--------

>>> from xgboost.spark import SparkXGBClassifier
>>> from pyspark.ml.linalg import Vectors
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