[GitHub] [spark] HyukjinKwon commented on a diff in pull request #37434: [SPARK-40003][PYTHON] Add function 'median' to PySpark

[GitBox <gi...@apache.org>]

HyukjinKwon commented on code in PR #37434:
URL: https://github.com/apache/spark/pull/37434#discussion_r939975832


##########
python/pyspark/sql/functions.py:
##########
@@ -305,6 +305,40 @@ def mean(col: "ColumnOrName") -> Column:
     return _invoke_function_over_columns("mean", col)
 
 
+def median(col: "ColumnOrName") -> Column:
+    """
+    Returns the median of the values in a group.
+
+    .. versionadded:: 3.4.0
+
+    Parameters
+    ----------
+    col : :class:`~pyspark.sql.Column` or str
+        target column that the value will be returned
+
+    Returns
+    -------
+    :class:`~pyspark.sql.Column`
+        value associated with the maximum value of ord.
+
+    Examples
+    --------
+    >>> df = spark.createDataFrame([
+    ...     ("Java", 2012, 20000), ("dotNET", 2012, 5000),
+    ...     ("Java", 2012, 22000), ("dotNET", 2012, 10000),
+    ...     ("dotNET", 2013, 48000), ("Java", 2013, 30000)],
+    ...     schema=("course", "year", "earnings"))
+    >>> df.groupby("course").agg(median("earnings")).show()
+    +------+----------------+
+    |course|median(earnings)|
+    +------+----------------+
+    |  Java|         22000.0|
+    |dotNET|         10000.0|
+    +------+----------------+
+    """
+    return _invoke_function_over_columns("median", col)

Review Comment:
   Can we use `percentile_approx` instead? Percentile implementation is actually super slow.



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