Apache spark 基于包含concat值的现有列添加新列Spark dataframe

我想根据以下条件在我的数据帧中创建一个新列

我的数据帧如下所示：

my_string 

2020 test 

2020 prod 

2020 dev 

我的情况：

value1=subtract string after space from my_string

value2=subtract first four digit from my_string

If value 1 contains string 'test' then new_col=value2+"01"

If value 1 contains string 'prod' then new_col=value2+"kk"

If value 1 contains string 'dev' then new_col=value2+"ff"

我需要这样的结果：

my_string 

2020 test 

2020 prod 

2020 dev 

有人能帮我吗？

使用id单调递增的行数窗口函数

更新：

使用when+others语句

df.withColumn("dyn_col",when(lower(split(col("my_string")," ")[1]) =="prod","kk").\
when(lower(split(col("my_string")," ")[1]) =="dev","ff").\
when(lower(split(col("my_string")," ")[1]) =="test","01").\
otherwise("null")).\
withColumn("new_col",concat(split(col("my_string")," ")[0], col("dyn_col"))).\
drop("dyn_col").\
show()
#+---------+-------+
#|my_string|new_col|
#+---------+-------+
#|2020 test| 202001|
#|2020 prod| 2020kk|
#| 2020 dev| 2020ff|
#+---------+-------+

在Scala中：

---

你能把你的输入和预期输出格式化成表格格式吗？因此，它是可读的&您可以为任何人提供简单的解决方案..：这不是我刚才给的示例的行数，它可能会像任何重新编辑的字符串一样变化。非常感谢您，我将尝试

df.withColumn("dyn_col",when(lower(split(col("my_string")," ")[1]) =="prod","kk").\
when(lower(split(col("my_string")," ")[1]) =="dev","ff").\
when(lower(split(col("my_string")," ")[1]) =="test","01").\
otherwise("null")).\
withColumn("new_col",concat(split(col("my_string")," ")[0], col("dyn_col"))).\
drop("dyn_col").\
show()
#+---------+-------+
#|my_string|new_col|
#+---------+-------+
#|2020 test| 202001|
#|2020 prod| 2020kk|
#| 2020 dev| 2020ff|
#+---------+-------+

df.withColumn("dyn_col",when(lower(split(col("my_string")," ")(1)) ==="prod","kk").
when(lower(split(col("my_string")," ")(1)) ==="dev","ff").
when(lower(split(col("my_string")," ")(1)) ==="test","01").
otherwise("null")).
withColumn("new_col",concat(split(col("my_string")," ")(0), col("dyn_col"))).
drop("dyn_col").
show()

//+---------+-------+
//|my_string|new_col|
//+---------+-------+
//|2020 test| 202001|
//|2020 prod| 2020kk|
//| 2020 dev| 2020ff|
//+---------+-------+