首先，让我们简化一下if语句:

First thing, lets simplify that if statement:

if(k == "yes" && i.nonEmpty)
  if(maxDate - targetDate < 0)
    if (j.isEmpty) "pending" 
    else "approved"
  else "expired"
else ""

现在有两种主要方法可以实现这一目标

Now there are 2 main ways to accomplish this

1. 使用自定义UDF
2. 使用内置的spark功能:coalesce，when，otherwise

1. Using a custom UDF
2. Using spark built in functions: coalesce, when, otherwise

自定义UDF

现在，由于条件的复杂性，执行第2个操作将非常棘手.使用自定义UDF应该可以满足您的需求.

Custom UDF

Now due to the complexity of your conditions, it will be rather tricky to do number 2. Using a custom UDF should suit your needs.

def getState(i: String, j: String, k: String, maxDate: Long, targetDate: Long): String =  
  if(k == "yes" && i.nonEmpty)
    if(maxDate - targetDate < 0)
      if (j.isEmpty) "pending" 
      else "approved"
    else "expired"
  else ""

val stateUdf = udf(getState _)
df.withColumn("state", stateUdf($"i",$"j",$"k",lit(0),lit(0)))

只需将lit(0)和lit(0)更改为您的日期代码，这对您就可以使用.

Just change lit(0) and lit(0) to your date code, and this should work for you.

如果发现性能问题，则可以切换为使用coalesce，otherwise和when，它们看起来像这样:

If you notice performance issues, you can switch to using coalesce, otherwise, and when, which would look something like this:

val isApproved = df.withColumn("state", when($"k" === "yes" && $"i" =!= "" && (lit(max_date) - lit(target_date) < 0) && $"j" =!= "", "approved").otherwise(null))
val isPending = isApproved.withColumn("state", coalesce($"state", when($"k" === "yes" && $"i" =!= "" && (lit(max_date) - lit(target_date) < 0) && $"j" === "", "pending").otherwise(null)))
val isExpired = isPending.withColumn("state", coalesce($"state", when($"k" === "yes" && $"i" =!= "" && (lit(max_date) - lit(target_date) >= 0), "expired").otherwise(null)))
val finalDf = isExpired.withColumn("state", coalesce($"state", lit("")))

过去，我在大型输入源中使用自定义udf时没有问题，自定义udfs可以导致代码更具可读性，尤其是在这种情况下.

I've used custom udf's in the past with large input sources without issues, and custom udfs can lead to much more readable code, especially in this case.