rebase upstream

Author: JihongMA

python/pyspark/sql/functions.py

@@ -122,6 +122,21 @@ def _():
     'bitwiseNOT': 'Computes bitwise not.',
 }
 
+_functions_1_6 = {
+    # unary math functions
+    "stddev": "Aggregate function: returns the unbiased sample standard deviation of" +
+              " the expression in a group.",
+    "stddev_samp": "Aggregate function: returns the unbiased sample standard deviation of" +
+              " the expression in a group.",
+    "stddev_pop": "Aggregate function: returns population standard deviation of" +
+              " the expression in a group.",
+    "variance": "Aggregate function: returns the population variance of the values in a group.",
+    "var_samp": "Aggregate function: returns the unbiased variance of the values in a group.",
+    "var_pop":  "Aggregate function: returns the population variance of the values in a group.",
+    "skewness": "Aggregate function: returns the skewness of the values in a group.",
+    "kurtosis": "Aggregate function: returns the kurtosis of the values in a group."
+}
+
 # math functions that take two arguments as input
 _binary_mathfunctions = {
     'atan2': 'Returns the angle theta from the conversion of rectangular coordinates (x, y) to' +
@@ -172,6 +187,8 @@ def _():
     globals()[_name] = since(1.4)(_create_binary_mathfunction(_name, _doc))
 for _name, _doc in _window_functions.items():
     globals()[_name] = since(1.4)(_create_window_function(_name, _doc))
+for _name, _doc in _functions_1_6.items():
+    globals()[_name] = since(1.6)(_create_function(_name, _doc))
 del _name, _doc
 
 

python/pyspark/sql/group.py

@@ -167,6 +167,94 @@ def sum(self, *cols):
         [Row(sum(age)=7, sum(height)=165)]
         """
 
+    @df_varargs_api
+    @since(1.6)
+    def stddev(self, *cols):
+        """Compute the sample standard deviation for each numeric columns for each group.
+
+        :param cols: list of column names (string). Non-numeric columns are ignored.
+
+        >>> df3.groupBy().stddev('age', 'height').collect()
+        [Row(STDDEV(age)=2.12..., STDDEV(height)=3.53...)]
+        """
+
+    @df_varargs_api
+    @since(1.6)
+    def stddev_samp(self, *cols):
+        """Compute the sample standard deviation for each numeric columns for each group.
+
+        :param cols: list of column names (string). Non-numeric columns are ignored.
+
+        >>> df3.groupBy().stddev_samp('age', 'height').collect()
+        [Row(STDDEV_SAMP(age)=2.12..., STDDEV_SAMP(height)=3.53...)]
+        """
+
+    @df_varargs_api
+    @since(1.6)
+    def stddev_pop(self, *cols):
+        """Compute the population standard deviation for each numeric columns for each group.
+
+        :param cols: list of column names (string). Non-numeric columns are ignored.
+
+        >>> df3.groupBy().stddev_pop('age', 'height').collect()
+        [Row(STDDEV_POP(age)=1.5, STDDEV_POP(height)=2.5)]
+        """
+
+    @df_varargs_api
+    @since(1.6)
+    def variance(self, *cols):
+        """Compute the sample variance for each numeric columns for each group.
+
+        :param cols: list of column names (string). Non-numeric columns are ignored.
+
+        >>> df3.groupBy().variance('age', 'height').collect()
+        [Row(VARIANCE(age)=2.25, VARIANCE(height)=6.25)]
+        """
+
+    @df_varargs_api
+    @since(1.6)
+    def var_pop(self, *cols):
+        """Compute the sample variance for each numeric columns for each group.
+
+        :param cols: list of column names (string). Non-numeric columns are ignored.
+
+        >>> df3.groupBy().var_pop('age', 'height').collect()
+        [Row(VAR_POP(age)=2.25, VAR_POP(height)=6.25)]
+        """
+
+    @df_varargs_api
+    @since(1.6)
+    def var_samp(self, *cols):
+        """Compute the sample variance for each numeric columns for each group.
+
+        :param cols: list of column names (string). Non-numeric columns are ignored.
+
+        >>> df3.groupBy().var_samp('age', 'height').collect()
+        [Row(VAR_SAMP(age)=4.5, VAR_SAMP(height)=12.5)]
+        """
+
+    @df_varargs_api
+    @since(1.6)
+    def skewness(self, *cols):
+        """Compute the skewness for each numeric columns for each group.
+
+        :param cols: list of column names (string). Non-numeric columns are ignored.
+
+        >>> df3.groupBy().skewness('age', 'height').collect()
+        [Row(SKEWNESS(age)=0.0, SKEWNESS(height)=0.0)]
+        """
+
+    @df_varargs_api
+    @since(1.6)
+    def kurtosis(self, *cols):
+        """Compute the kurtosis for each numeric columns for each group.
+
+        :param cols: list of column names (string). Non-numeric columns are ignored.
+
+        >>> df3.groupBy().kurtosis('age', 'height').collect()
+        [Row(KURTOSIS(age)=-2.0, KURTOSIS(height)=-2.0)]
+        """
+
 
 def _test():
     import doctest

sql/core/src/main/scala/org/apache/spark/sql/functions.scala

@@ -254,14 +254,6 @@ object functions {
    */
   def kurtosis(e: Column): Column = Kurtosis(e.expr)
 
-  /**
-   * Aggregate function: returns the kurtosis of the values in a group.
-   *
-   * @group agg_funcs
-   * @since 1.6.0
-   */
-  def kurtosis(columnName: String): Column = kurtosis(Column(columnName))
-
   /**
    * Aggregate function: returns the last value in a group.
    *
@@ -354,32 +346,14 @@ object functions {
   def stddev(e: Column): Column = Stddev(e.expr)
 
   /**
-   * Aggregate function: returns the population standard deviation of
-   * the expression in a group.
-   *
-   * @group agg_funcs
-   * @since 1.6.0
-   */
-  def stddev(columnName: String): Column = stddev(Column(columnName))
-
-  /**
-   * Aggregate function: returns the unbiased sample standard deviation of
+   * Aggregate function: returns the sample standard deviation of
    * the expression in a group.
    *
    * @group agg_funcs
    * @since 1.6.0
    */
   def stddev_samp(e: Column): Column = StddevSamp(e.expr)
 
-  /**
-   * Aggregate function: returns the unbiased sample standard deviation of
-   * the expression in a group.
-   *
-   * @group agg_funcs
-   * @since 1.6.0
-   */
-  def stddev_samp(columnName: String): Column = stddev_samp(Column(columnName))
-
   /**
    * Aggregate function: returns the population standard deviation of
    * the expression in a group.
@@ -389,15 +363,6 @@ object functions {
    */
   def stddev_pop(e: Column): Column = StddevPop(e.expr)
 
-  /**
-   * Aggregate function: returns the population standard deviation of
-   * the expression in a group.
-   *
-   * @group agg_funcs
-   * @since 1.6.0
-   */
-  def stddev_pop(columnName: String): Column = stddev_pop(Column(columnName))
-
   /**
    * Aggregate function: returns the sum of all values in the expression.
    *
@@ -438,14 +403,6 @@ object functions {
    */
   def variance(e: Column): Column = Variance(e.expr)
 
-  /**
-   * Aggregate function: returns the population variance of the values in a group.
-   *
-   * @group agg_funcs
-   * @since 1.6.0
-   */
-  def variance(columnName: String): Column = variance(Column(columnName))
-
   /**
    * Aggregate function: returns the unbiased variance of the values in a group.
    *
@@ -454,14 +411,6 @@ object functions {
    */
   def var_samp(e: Column): Column = VarianceSamp(e.expr)
 
-  /**
-   * Aggregate function: returns the unbiased variance of the values in a group.
-   *
-   * @group agg_funcs
-   * @since 1.6.0
-   */
-  def var_samp(columnName: String): Column = var_samp(Column(columnName))
-
   /**
    * Aggregate function: returns the population variance of the values in a group.
    *
@@ -470,14 +419,6 @@ object functions {
    */
   def var_pop(e: Column): Column = VariancePop(e.expr)
 
-  /**
-   * Aggregate function: returns the population variance of the values in a group.
-   *
-   * @group agg_funcs
-   * @since 1.6.0
-   */
-  def var_pop(columnName: String): Column = var_pop(Column(columnName))
-
   //////////////////////////////////////////////////////////////////////////////////////////////
   // Window functions
   //////////////////////////////////////////////////////////////////////////////////////////////