[MINOR][PYSPARK][DOC] Fix wrongly formatted examples in PySpark documentation

## What changes were proposed in this pull request?

This PR fixes wrongly formatted examples in PySpark documentation as below:

- **`SparkSession`**

  - **Before**

    ![2016-07-06 11 34 41](https://cloud.githubusercontent.com/assets/6477701/16605847/ae939526-436d-11e6-8ab8-6ad578362425.png)

  - **After**

    ![2016-07-06 11 33 56](https://cloud.githubusercontent.com/assets/6477701/16605845/ace9ee78-436d-11e6-8923-b76d4fc3e7c3.png)

- **`Builder`**

  - **Before**
    ![2016-07-06 11 34 44](https://cloud.githubusercontent.com/assets/6477701/16605844/aba60dbc-436d-11e6-990a-c87bc0281c6b.png)

  - **After**
    ![2016-07-06 1 26 37](https://cloud.githubusercontent.com/assets/6477701/16607562/586704c0-437d-11e6-9483-e0af93d8f74e.png)

This PR also fixes several similar instances across the documentation in `sql` PySpark module.

## How was this patch tested?

N/A

Author: hyukjinkwon <gurwls223@gmail.com>

Closes #14063 from HyukjinKwon/minor-pyspark-builder.

6 files changed, 26 insertions, 23 deletions

diff --git a/python/pyspark/mllib/clustering.py b/python/pyspark/mllib/clustering.py
index 93a0b64569..c38c543972 100644
--- a/python/pyspark/mllib/clustering.py
+++ b/python/pyspark/mllib/clustering.py
@@ -571,14 +571,14 @@ class PowerIterationClusteringModel(JavaModelWrapper, JavaSaveable, JavaLoader):
 
     >>> import math
     >>> def genCircle(r, n):
-    ...   points = []
-    ...   for i in range(0, n):
-    ...     theta = 2.0 * math.pi * i / n
-    ...     points.append((r * math.cos(theta), r * math.sin(theta)))
-    ...   return points
+    ...     points = []
+    ...     for i in range(0, n):
+    ...         theta = 2.0 * math.pi * i / n
+    ...         points.append((r * math.cos(theta), r * math.sin(theta)))
+    ...     return points
     >>> def sim(x, y):
-    ...   dist2 = (x[0] - y[0]) * (x[0] - y[0]) + (x[1] - y[1]) * (x[1] - y[1])
-    ...   return math.exp(-dist2 / 2.0)
+    ...     dist2 = (x[0] - y[0]) * (x[0] - y[0]) + (x[1] - y[1]) * (x[1] - y[1])
+    ...     return math.exp(-dist2 / 2.0)
     >>> r1 = 1.0
     >>> n1 = 10
     >>> r2 = 4.0
diff --git a/python/pyspark/sql/dataframe.py b/python/pyspark/sql/dataframe.py
index e44b01bba9..a0ac7a9342 100644
--- a/python/pyspark/sql/dataframe.py
+++ b/python/pyspark/sql/dataframe.py
@@ -1045,10 +1045,10 @@ class DataFrame(object):
         :func:`drop_duplicates` is an alias for :func:`dropDuplicates`.
 
         >>> from pyspark.sql import Row
-        >>> df = sc.parallelize([ \
-            Row(name='Alice', age=5, height=80), \
-            Row(name='Alice', age=5, height=80), \
-            Row(name='Alice', age=10, height=80)]).toDF()
+        >>> df = sc.parallelize([ \\
+        ...     Row(name='Alice', age=5, height=80), \\
+        ...     Row(name='Alice', age=5, height=80), \\
+        ...     Row(name='Alice', age=10, height=80)]).toDF()
         >>> df.dropDuplicates().show()
         +---+------+-----+
         |age|height| name|
diff --git a/python/pyspark/sql/functions.py b/python/pyspark/sql/functions.py
index 7a7345170c..92d709ee40 100644
--- a/python/pyspark/sql/functions.py
+++ b/python/pyspark/sql/functions.py
@@ -1550,8 +1550,8 @@ def translate(srcCol, matching, replace):
     The translate will happen when any character in the string matching with the character
     in the `matching`.
 
-    >>> spark.createDataFrame([('translate',)], ['a']).select(translate('a', "rnlt", "123")\
-    .alias('r')).collect()
+    >>> spark.createDataFrame([('translate',)], ['a']).select(translate('a', "rnlt", "123") \\
+    ...     .alias('r')).collect()
     [Row(r=u'1a2s3ae')]
     """
     sc = SparkContext._active_spark_context
@@ -1670,8 +1670,8 @@ def get_json_object(col, path):
 
     >>> data = [("1", '''{"f1": "value1", "f2": "value2"}'''), ("2", '''{"f1": "value12"}''')]
     >>> df = spark.createDataFrame(data, ("key", "jstring"))
-    >>> df.select(df.key, get_json_object(df.jstring, '$.f1').alias("c0"), \
-                          get_json_object(df.jstring, '$.f2').alias("c1") ).collect()
+    >>> df.select(df.key, get_json_object(df.jstring, '$.f1').alias("c0"), \\
+    ...                   get_json_object(df.jstring, '$.f2').alias("c1") ).collect()
     [Row(key=u'1', c0=u'value1', c1=u'value2'), Row(key=u'2', c0=u'value12', c1=None)]
     """
     sc = SparkContext._active_spark_context
diff --git a/python/pyspark/sql/group.py b/python/pyspark/sql/group.py
index a423206554..f2092f9c63 100644
--- a/python/pyspark/sql/group.py
+++ b/python/pyspark/sql/group.py
@@ -179,10 +179,12 @@ class GroupedData(object):
         :param values: List of values that will be translated to columns in the output DataFrame.
 
         # Compute the sum of earnings for each year by course with each course as a separate column
+
         >>> df4.groupBy("year").pivot("course", ["dotNET", "Java"]).sum("earnings").collect()
         [Row(year=2012, dotNET=15000, Java=20000), Row(year=2013, dotNET=48000, Java=30000)]
 
         # Or without specifying column values (less efficient)
+
         >>> df4.groupBy("year").pivot("course").sum("earnings").collect()
         [Row(year=2012, Java=20000, dotNET=15000), Row(year=2013, Java=30000, dotNET=48000)]
         """
diff --git a/python/pyspark/sql/session.py b/python/pyspark/sql/session.py
index 55f86a16f5..a360fbefa4 100644
--- a/python/pyspark/sql/session.py
+++ b/python/pyspark/sql/session.py
@@ -66,12 +66,11 @@ class SparkSession(object):
     tables, execute SQL over tables, cache tables, and read parquet files.
     To create a SparkSession, use the following builder pattern:
 
-    >>> spark = SparkSession.builder \
-            .master("local") \
-            .appName("Word Count") \
-            .config("spark.some.config.option", "some-value") \
-            .getOrCreate()
-
+    >>> spark = SparkSession.builder \\
+    ...     .master("local") \\
+    ...     .appName("Word Count") \\
+    ...     .config("spark.some.config.option", "some-value") \\
+    ...     .getOrCreate()
     """
 
     class Builder(object):
@@ -87,11 +86,13 @@ class SparkSession(object):
             both :class:`SparkConf` and :class:`SparkSession`'s own configuration.
 
             For an existing SparkConf, use `conf` parameter.
+
             >>> from pyspark.conf import SparkConf
             >>> SparkSession.builder.config(conf=SparkConf())
             <pyspark.sql.session...
 
             For a (key, value) pair, you can omit parameter names.
+
             >>> SparkSession.builder.config("spark.some.config.option", "some-value")
             <pyspark.sql.session...
 
diff --git a/python/pyspark/sql/types.py b/python/pyspark/sql/types.py
index a3679873e1..eea80684e2 100644
--- a/python/pyspark/sql/types.py
+++ b/python/pyspark/sql/types.py
@@ -486,8 +486,8 @@ class StructType(DataType):
                DataType object.
 
         >>> struct1 = StructType().add("f1", StringType(), True).add("f2", StringType(), True, None)
-        >>> struct2 = StructType([StructField("f1", StringType(), True),\
-         StructField("f2", StringType(), True, None)])
+        >>> struct2 = StructType([StructField("f1", StringType(), True), \\
+        ...     StructField("f2", StringType(), True, None)])
         >>> struct1 == struct2
         True
         >>> struct1 = StructType().add(StructField("f1", StringType(), True))