Python PySpark：从列的有序连接创建列

我在pyspark数据帧上从两个现有列的有序连接创建新列时遇到问题，即：

+------+------+--------+
| Col1 | Col2 | NewCol |
+------+------+--------+
| ORD  | DFW  | DFWORD |
| CUN  | MCI  | CUNMCI |
| LAX  | JFK  | JFKLAX |
+------+------+--------+

换句话说，我想抓取Col1和Col2，按字母顺序排列并连接它们

---

有什么建议吗？

结合

concat\u ws

、

array

和

sort\u array

from pyspark.sql.functions import concat_ws, array, sort_array

df = spark.createDataFrame(
    [("ORD", "DFW"), ("CUN", "MCI"), ("LAX", "JFK")],
    ("Col1", "Col2"))

df.withColumn("NewCol", concat_ws("", sort_array(array("Col1", "Col2")))).show()
# +----+----+------+        
# |Col1|Col2|NewCol|
# +----+----+------+
# | ORD| DFW|DFWORD|
# | CUN| MCI|CUNMCI|
# | LAX| JFK|JFKLAX|
# +----+----+------+

---

组合

concat\u ws

、

array

和

sort\u array

from pyspark.sql.functions import concat_ws, array, sort_array

df = spark.createDataFrame(
    [("ORD", "DFW"), ("CUN", "MCI"), ("LAX", "JFK")],
    ("Col1", "Col2"))

df.withColumn("NewCol", concat_ws("", sort_array(array("Col1", "Col2")))).show()
# +----+----+------+        
# |Col1|Col2|NewCol|
# +----+----+------+
# | ORD| DFW|DFWORD|
# | CUN| MCI|CUNMCI|
# | LAX| JFK|JFKLAX|
# +----+----+------+