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gurwls223 pushed a commit to branch branch-3.0
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The following commit(s) were added to refs/heads/branch-3.0 by this push:
     new 18925c3  [SPARK-31739][PYSPARK][DOCS][MINOR] Fix docstring syntax 
issues and misplaced space characters
18925c3 is described below

commit 18925c34ffc403c1422dd8ac8ae731c213521387
Author: David Toneian <da...@toneian.com>
AuthorDate: Mon May 18 20:25:02 2020 +0900

    [SPARK-31739][PYSPARK][DOCS][MINOR] Fix docstring syntax issues and 
misplaced space characters
    
    This commit is published into the public domain.
    
    Some syntax issues in docstrings have been fixed.
    
    In some places, the documentation did not render as intended, e.g. 
parameter documentations were not formatted as such.
    
    Slight improvements in documentation.
    
    Manual testing and `dev/lint-python` run. No new Sphinx warnings arise due 
to this change.
    
    Closes #28559 from DavidToneian/SPARK-31739.
    
    Authored-by: David Toneian <da...@toneian.com>
    Signed-off-by: HyukjinKwon <gurwls...@apache.org>
---
 python/pyspark/ml/clustering.py  |  2 +-
 python/pyspark/ml/regression.py  |  2 +-
 python/pyspark/ml/util.py        |  1 +
 python/pyspark/mllib/util.py     |  4 ++--
 python/pyspark/sql/dataframe.py  |  6 +++---
 python/pyspark/sql/readwriter.py | 14 +++++++-------
 python/pyspark/sql/streaming.py  | 26 +++++++++++++-------------
 7 files changed, 28 insertions(+), 27 deletions(-)

diff --git a/python/pyspark/ml/clustering.py b/python/pyspark/ml/clustering.py
index 7465cef..e1c2732 100644
--- a/python/pyspark/ml/clustering.py
+++ b/python/pyspark/ml/clustering.py
@@ -795,7 +795,7 @@ class BisectingKMeansModel(JavaModel, 
_BisectingKMeansParams, JavaMLWritable, Ja
         Computes the sum of squared distances between the input points
         and their corresponding cluster centers.
 
-        ..note:: Deprecated in 3.0.0. It will be removed in future versions. 
Use
+        .. note:: Deprecated in 3.0.0. It will be removed in future versions. 
Use
            ClusteringEvaluator instead. You can also get the cost on the 
training dataset in the
            summary.
         """
diff --git a/python/pyspark/ml/regression.py b/python/pyspark/ml/regression.py
index a4c9782..f367bb8 100644
--- a/python/pyspark/ml/regression.py
+++ b/python/pyspark/ml/regression.py
@@ -53,7 +53,7 @@ class JavaRegressor(JavaPredictor, _JavaPredictorParams):
 class JavaRegressionModel(JavaPredictionModel, _JavaPredictorParams):
     """
     Java Model produced by a ``_JavaRegressor``.
-    To be mixed in with class:`pyspark.ml.JavaModel`
+    To be mixed in with :class:`pyspark.ml.JavaModel`
 
     .. versionadded:: 3.0.0
     """
diff --git a/python/pyspark/ml/util.py b/python/pyspark/ml/util.py
index 35ad551..aac2b38 100644
--- a/python/pyspark/ml/util.py
+++ b/python/pyspark/ml/util.py
@@ -563,6 +563,7 @@ class DefaultParamsReader(MLReader):
 class HasTrainingSummary(object):
     """
     Base class for models that provides Training summary.
+
     .. versionadded:: 3.0.0
     """
 
diff --git a/python/pyspark/mllib/util.py b/python/pyspark/mllib/util.py
index 1a0ce42..f0f9cda 100644
--- a/python/pyspark/mllib/util.py
+++ b/python/pyspark/mllib/util.py
@@ -372,7 +372,7 @@ class Saveable(object):
          * human-readable (JSON) model metadata to path/metadata/
          * Parquet formatted data to path/data/
 
-        The model may be loaded using py:meth:`Loader.load`.
+        The model may be loaded using :py:meth:`Loader.load`.
 
         :param sc: Spark context used to save model data.
         :param path: Path specifying the directory in which to save
@@ -412,7 +412,7 @@ class Loader(object):
     def load(cls, sc, path):
         """
         Load a model from the given path. The model should have been
-        saved using py:meth:`Saveable.save`.
+        saved using :py:meth:`Saveable.save`.
 
         :param sc: Spark context used for loading model files.
         :param path: Path specifying the directory to which the model
diff --git a/python/pyspark/sql/dataframe.py b/python/pyspark/sql/dataframe.py
index 2a366dc..6f4fdd3 100644
--- a/python/pyspark/sql/dataframe.py
+++ b/python/pyspark/sql/dataframe.py
@@ -2138,7 +2138,7 @@ class DataFrame(PandasMapOpsMixin, PandasConversionMixin):
 
     @ignore_unicode_prefix
     def toDF(self, *cols):
-        """Returns a new class:`DataFrame` that with new specified column names
+        """Returns a new :class:`DataFrame` that with new specified column 
names
 
         :param cols: list of new column names (string)
 
@@ -2150,9 +2150,9 @@ class DataFrame(PandasMapOpsMixin, PandasConversionMixin):
 
     @since(3.0)
     def transform(self, func):
-        """Returns a new class:`DataFrame`. Concise syntax for chaining custom 
transformations.
+        """Returns a new :class:`DataFrame`. Concise syntax for chaining 
custom transformations.
 
-        :param func: a function that takes and returns a class:`DataFrame`.
+        :param func: a function that takes and returns a :class:`DataFrame`.
 
         >>> from pyspark.sql.functions import col
         >>> df = spark.createDataFrame([(1, 1.0), (2, 2.0)], ["int", "float"])
diff --git a/python/pyspark/sql/readwriter.py b/python/pyspark/sql/readwriter.py
index 6ad6377..336345e 100644
--- a/python/pyspark/sql/readwriter.py
+++ b/python/pyspark/sql/readwriter.py
@@ -223,15 +223,15 @@ class DataFrameReader(OptionUtils):
         :param mode: allows a mode for dealing with corrupt records during 
parsing. If None is
                      set, it uses the default value, ``PERMISSIVE``.
 
-                * ``PERMISSIVE`` : when it meets a corrupted record, puts the 
malformed string \
+                * ``PERMISSIVE``: when it meets a corrupted record, puts the 
malformed string \
                   into a field configured by ``columnNameOfCorruptRecord``, 
and sets malformed \
                   fields to ``null``. To keep corrupt records, an user can set 
a string type \
                   field named ``columnNameOfCorruptRecord`` in an user-defined 
schema. If a \
                   schema does not have the field, it drops corrupt records 
during parsing. \
                   When inferring a schema, it implicitly adds a 
``columnNameOfCorruptRecord`` \
                   field in an output schema.
-                *  ``DROPMALFORMED`` : ignores the whole corrupted records.
-                *  ``FAILFAST`` : throws an exception when it meets corrupted 
records.
+                *  ``DROPMALFORMED``: ignores the whole corrupted records.
+                *  ``FAILFAST``: throws an exception when it meets corrupted 
records.
 
         :param columnNameOfCorruptRecord: allows renaming the new field having 
malformed string
                                           created by ``PERMISSIVE`` mode. This 
overrides
@@ -470,7 +470,7 @@ class DataFrameReader(OptionUtils):
                      be controlled by 
``spark.sql.csv.parser.columnPruning.enabled``
                      (enabled by default).
 
-                * ``PERMISSIVE`` : when it meets a corrupted record, puts the 
malformed string \
+                * ``PERMISSIVE``: when it meets a corrupted record, puts the 
malformed string \
                   into a field configured by ``columnNameOfCorruptRecord``, 
and sets malformed \
                   fields to ``null``. To keep corrupt records, an user can set 
a string type \
                   field named ``columnNameOfCorruptRecord`` in an user-defined 
schema. If a \
@@ -479,8 +479,8 @@ class DataFrameReader(OptionUtils):
                   When it meets a record having fewer tokens than the length 
of the schema, \
                   sets ``null`` to extra fields. When the record has more 
tokens than the \
                   length of the schema, it drops extra tokens.
-                * ``DROPMALFORMED`` : ignores the whole corrupted records.
-                * ``FAILFAST`` : throws an exception when it meets corrupted 
records.
+                * ``DROPMALFORMED``: ignores the whole corrupted records.
+                * ``FAILFAST``: throws an exception when it meets corrupted 
records.
 
         :param columnNameOfCorruptRecord: allows renaming the new field having 
malformed string
                                           created by ``PERMISSIVE`` mode. This 
overrides
@@ -830,7 +830,7 @@ class DataFrameWriter(OptionUtils):
     def insertInto(self, tableName, overwrite=None):
         """Inserts the content of the :class:`DataFrame` to the specified 
table.
 
-        It requires that the schema of the class:`DataFrame` is the same as the
+        It requires that the schema of the :class:`DataFrame` is the same as 
the
         schema of the table.
 
         Optionally overwriting any existing data.
diff --git a/python/pyspark/sql/streaming.py b/python/pyspark/sql/streaming.py
index 05cf331..2450a4c 100644
--- a/python/pyspark/sql/streaming.py
+++ b/python/pyspark/sql/streaming.py
@@ -461,15 +461,15 @@ class DataStreamReader(OptionUtils):
         :param mode: allows a mode for dealing with corrupt records during 
parsing. If None is
                      set, it uses the default value, ``PERMISSIVE``.
 
-                * ``PERMISSIVE`` : when it meets a corrupted record, puts the 
malformed string \
+                * ``PERMISSIVE``: when it meets a corrupted record, puts the 
malformed string \
                   into a field configured by ``columnNameOfCorruptRecord``, 
and sets malformed \
                   fields to ``null``. To keep corrupt records, an user can set 
a string type \
                   field named ``columnNameOfCorruptRecord`` in an user-defined 
schema. If a \
                   schema does not have the field, it drops corrupt records 
during parsing. \
                   When inferring a schema, it implicitly adds a 
``columnNameOfCorruptRecord`` \
                   field in an output schema.
-                *  ``DROPMALFORMED`` : ignores the whole corrupted records.
-                *  ``FAILFAST`` : throws an exception when it meets corrupted 
records.
+                *  ``DROPMALFORMED``: ignores the whole corrupted records.
+                *  ``FAILFAST``: throws an exception when it meets corrupted 
records.
 
         :param columnNameOfCorruptRecord: allows renaming the new field having 
malformed string
                                           created by ``PERMISSIVE`` mode. This 
overrides
@@ -707,7 +707,7 @@ class DataStreamReader(OptionUtils):
         :param mode: allows a mode for dealing with corrupt records during 
parsing. If None is
                      set, it uses the default value, ``PERMISSIVE``.
 
-                * ``PERMISSIVE`` : when it meets a corrupted record, puts the 
malformed string \
+                * ``PERMISSIVE``: when it meets a corrupted record, puts the 
malformed string \
                   into a field configured by ``columnNameOfCorruptRecord``, 
and sets malformed \
                   fields to ``null``. To keep corrupt records, an user can set 
a string type \
                   field named ``columnNameOfCorruptRecord`` in an user-defined 
schema. If a \
@@ -716,8 +716,8 @@ class DataStreamReader(OptionUtils):
                   When it meets a record having fewer tokens than the length 
of the schema, \
                   sets ``null`` to extra fields. When the record has more 
tokens than the \
                   length of the schema, it drops extra tokens.
-                * ``DROPMALFORMED`` : ignores the whole corrupted records.
-                * ``FAILFAST`` : throws an exception when it meets corrupted 
records.
+                * ``DROPMALFORMED``: ignores the whole corrupted records.
+                * ``FAILFAST``: throws an exception when it meets corrupted 
records.
 
         :param columnNameOfCorruptRecord: allows renaming the new field having 
malformed string
                                           created by ``PERMISSIVE`` mode. This 
overrides
@@ -795,11 +795,11 @@ class DataStreamWriter(object):
 
         Options include:
 
-        * `append`:Only the new rows in the streaming DataFrame/Dataset will 
be written to
+        * `append`: Only the new rows in the streaming DataFrame/Dataset will 
be written to
            the sink
-        * `complete`:All the rows in the streaming DataFrame/Dataset will be 
written to the sink
+        * `complete`: All the rows in the streaming DataFrame/Dataset will be 
written to the sink
            every time these is some updates
-        * `update`:only the rows that were updated in the streaming 
DataFrame/Dataset will be
+        * `update`: only the rows that were updated in the streaming 
DataFrame/Dataset will be
            written to the sink every time there are some updates. If the query 
doesn't contain
            aggregations, it will be equivalent to `append` mode.
 
@@ -1170,11 +1170,11 @@ class DataStreamWriter(object):
         :param outputMode: specifies how data of a streaming DataFrame/Dataset 
is written to a
                            streaming sink.
 
-            * `append`:Only the new rows in the streaming DataFrame/Dataset 
will be written to the
+            * `append`: Only the new rows in the streaming DataFrame/Dataset 
will be written to the
               sink
-            * `complete`:All the rows in the streaming DataFrame/Dataset will 
be written to the sink
-               every time these is some updates
-            * `update`:only the rows that were updated in the streaming 
DataFrame/Dataset will be
+            * `complete`: All the rows in the streaming DataFrame/Dataset will 
be written to the
+              sink every time these is some updates
+            * `update`: only the rows that were updated in the streaming 
DataFrame/Dataset will be
               written to the sink every time there are some updates. If the 
query doesn't contain
               aggregations, it will be equivalent to `append` mode.
         :param partitionBy: names of partitioning columns


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