你可以用 withColumn 而不是 select ```
data = spark.createDataFrame([('1997/02/28 10:30:00',"test")], ['Time','Col_Test'])

df = data.withColumn("timestamp",unix_timestamp(data.Time, 'yyyy/MM/dd HH:mm:ss').cast(TimestampType()))

输出：

df.show()
+-------------------+--------+-------------------+
| Time|Col_Test| timestamp|
+-------------------+--------+-------------------+
|1997/02/28 10:30:00| test|1997-02-28 10:30:00|
+-------------------+--------+-------------------+

data.printSchema()
root
|-- Time: string (nullable = true)
|-- Col_Test: string (nullable = true)

df.printSchema()
root
|-- Time: string (nullable = true)
|-- Col_Test: string (nullable = true)
|-- timestamp: timestamp (nullable = true)