zhengruifeng commented on code in PR #42717:
URL: https://github.com/apache/spark/pull/42717#discussion_r1309674635
##########
python/pyspark/sql/functions.py:
##########
@@ -723,27 +750,67 @@ def desc(col: "ColumnOrName") -> Column:
Parameters
----------
col : :class:`~pyspark.sql.Column` or str
- target column to sort by in the descending order.
+ Target column to sort by in the descending order.
Returns
-------
:class:`~pyspark.sql.Column`
- the column specifying the order.
+ The column specifying the sort order.
Examples
--------
- Sort by the column 'id' in the descending order.
+ Example 1: Sort DataFrame by 'id' column in descending order.
- >>> spark.range(5).orderBy(desc("id")).show()
- +---+
- | id|
- +---+
- | 4|
- | 3|
- | 2|
- | 1|
- | 0|
- +---+
+ >>> from pyspark.sql.functions import desc
+ >>> df = spark.createDataFrame([(4, 'B'), (3, 'A'), (2, 'C')], ['id',
'value'])
+ >>> df.sort(desc("id")).show()
+ +---+-----+
+ | id|value|
+ +---+-----+
+ | 4| B|
+ | 3| A|
+ | 2| C|
+ +---+-----+
+
+ Example 2: Use `desc` in `orderBy` function to sort the DataFrame.
+
+ >>> from pyspark.sql.functions import desc
+ >>> df = spark.createDataFrame([(4, 'B'), (3, 'A'), (2, 'C')], ['id',
'value'])
+ >>> df.orderBy(desc("value")).show()
+ +---+-----+
+ | id|value|
+ +---+-----+
+ | 2| C|
+ | 4| B|
+ | 3| A|
+ +---+-----+
+
+ Example 3: Combine `asc` with `desc` to sort by multiple columns.
+
+ >>> from pyspark.sql.functions import asc, desc
Review Comment:
On second thought, I will try to change all the imports in functions.py in
one batch.
So no need to make a follow up :)
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