From 2b01d3c701c58f07fa42afd570523dd161384882 Mon Sep 17 00:00:00 2001
From: hyukjinkwon <gurwls223@gmail.com>
Date: Fri, 7 Oct 2016 11:49:34 +0100
Subject: [SPARK-16960][SQL] Deprecate approxCountDistinct, toDegrees and
 toRadians according to FunctionRegistry

## What changes were proposed in this pull request?

It seems `approxCountDistinct`, `toDegrees` and `toRadians` are also missed while matching the names to the ones in `FunctionRegistry`. (please see [approx_count_distinct](https://github.com/apache/spark/blob/5c2ae79bfcf448d8dc9217efafa1409997c739de/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/FunctionRegistry.scala#L244), [degrees](https://github.com/apache/spark/blob/5c2ae79bfcf448d8dc9217efafa1409997c739de/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/FunctionRegistry.scala#L203) and [radians](https://github.com/apache/spark/blob/5c2ae79bfcf448d8dc9217efafa1409997c739de/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/FunctionRegistry.scala#L222) in `FunctionRegistry`).

I took a scan between `functions.scala` and `FunctionRegistry` and it seems these are all left. For `countDistinct` and `sumDistinct`, they are not registered in `FunctionRegistry`.

This PR deprecates `approxCountDistinct`, `toDegrees` and `toRadians` and introduces `approx_count_distinct`, `degrees` and `radians`.

## How was this patch tested?

Existing tests should cover this.

Author: hyukjinkwon <gurwls223@gmail.com>
Author: Hyukjin Kwon <gurwls223@gmail.com>

Closes #14538 from HyukjinKwon/SPARK-16588-followup.
---
 python/pyspark/sql/functions.py | 33 ++++++++++++++++++++++++---------
 1 file changed, 24 insertions(+), 9 deletions(-)

(limited to 'python/pyspark/sql/functions.py')

diff --git a/python/pyspark/sql/functions.py b/python/pyspark/sql/functions.py
index 45d6bf944b..7fa3fd2de7 100644
--- a/python/pyspark/sql/functions.py
+++ b/python/pyspark/sql/functions.py
@@ -112,11 +112,8 @@ _functions_1_4 = {
     'sinh': 'Computes the hyperbolic sine of the given value.',
     'tan': 'Computes the tangent of the given value.',
     'tanh': 'Computes the hyperbolic tangent of the given value.',
-    'toDegrees': 'Converts an angle measured in radians to an approximately equivalent angle ' +
-                 'measured in degrees.',
-    'toRadians': 'Converts an angle measured in degrees to an approximately equivalent angle ' +
-                 'measured in radians.',
-
+    'toDegrees': '.. note:: Deprecated in 2.1, use degrees instead.',
+    'toRadians': '.. note:: Deprecated in 2.1, use radians instead.',
     'bitwiseNOT': 'Computes bitwise not.',
 }
 
@@ -135,7 +132,15 @@ _functions_1_6 = {
     'kurtosis': 'Aggregate function: returns the kurtosis of the values in a group.',
     'collect_list': 'Aggregate function: returns a list of objects with duplicates.',
     'collect_set': 'Aggregate function: returns a set of objects with duplicate elements' +
-                   ' eliminated.'
+                   ' eliminated.',
+}
+
+_functions_2_1 = {
+    # unary math functions
+    'degrees': 'Converts an angle measured in radians to an approximately equivalent angle ' +
+               'measured in degrees.',
+    'radians': 'Converts an angle measured in degrees to an approximately equivalent angle ' +
+               'measured in radians.',
 }
 
 # math functions that take two arguments as input
@@ -182,21 +187,31 @@ for _name, _doc in _window_functions.items():
     globals()[_name] = since(1.6)(_create_window_function(_name, _doc))
 for _name, _doc in _functions_1_6.items():
     globals()[_name] = since(1.6)(_create_function(_name, _doc))
+for _name, _doc in _functions_2_1.items():
+    globals()[_name] = since(2.1)(_create_function(_name, _doc))
 del _name, _doc
 
 
 @since(1.3)
 def approxCountDistinct(col, rsd=None):
+    """
+    .. note:: Deprecated in 2.1, use approx_count_distinct instead.
+    """
+    return approx_count_distinct(col, rsd)
+
+
+@since(2.1)
+def approx_count_distinct(col, rsd=None):
     """Returns a new :class:`Column` for approximate distinct count of ``col``.
 
-    >>> df.agg(approxCountDistinct(df.age).alias('c')).collect()
+    >>> df.agg(approx_count_distinct(df.age).alias('c')).collect()
     [Row(c=2)]
     """
     sc = SparkContext._active_spark_context
     if rsd is None:
-        jc = sc._jvm.functions.approxCountDistinct(_to_java_column(col))
+        jc = sc._jvm.functions.approx_count_distinct(_to_java_column(col))
     else:
-        jc = sc._jvm.functions.approxCountDistinct(_to_java_column(col), rsd)
+        jc = sc._jvm.functions.approx_count_distinct(_to_java_column(col), rsd)
     return Column(jc)
 
 
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