zhengruifeng commented on code in PR #43145:
URL: https://github.com/apache/spark/pull/43145#discussion_r1338529056
##########
python/pyspark/sql/functions.py:
##########
@@ -12052,24 +12132,68 @@ def array_join(
Parameters
----------
col : :class:`~pyspark.sql.Column` or str
- target column to work on.
+ The input column containing the arrays to be joined.
delimiter : str
- delimiter used to concatenate elements
+ The string to be used as the delimiter when joining the array elements.
null_replacement : str, optional
- if set then null values will be replaced by this value
+ The string to replace null values within the array. If not set, null
values are ignored.
Returns
-------
:class:`~pyspark.sql.Column`
- a column of string type. Concatenated values.
+ A new column of string type, where each value is the result of joining
the corresponding
+ array from the input column.
Examples
--------
- >>> df = spark.createDataFrame([(["a", "b", "c"],), (["a", None],)],
['data'])
- >>> df.select(array_join(df.data, ",").alias("joined")).collect()
- [Row(joined='a,b,c'), Row(joined='a')]
- >>> df.select(array_join(df.data, ",", "NULL").alias("joined")).collect()
- [Row(joined='a,b,c'), Row(joined='a,NULL')]
+ Example 1: Basic usage of array_join function.
+
+ >>> from pyspark.sql import functions as sf
+ >>> df = spark.createDataFrame([(["a", "b", "c"],), (["a", "b"],)],
['data'])
+ >>> df.select(sf.array_join(df.data, ",").alias("joined")).show()
Review Comment:
let's remove all the alias in this PR, if possible
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