我想在下面的数据集中作为sum（quantity）列进行聚合，并根据sum选择相关的行值，如下所述：
输入：

val df = Seq(
  ("Acc1","111","1111","Sec1",-4000),
  ("Acc2","222","2222","Sec1",2000),
  ("Acc3","333","3333","Sec1",1000),
  ("Acc4","444","4444","Sec1",-10000)
  ).toDF("ACCOUNT_NO","LONG_IND","SHORT_IND","SECURITY_ID","QUANTITY")

How to aggregation based on the SUM(QUANTITY) such that, in final result
  (a) if Sum is negative, the row values with the maximum negative value (-10000 in this case) should take precedence
  (b) if Sum is positive, the row values with the maximum positive value (2000) should take precedence 

  In this case, SUM is negative = -4000+2000+1000-10000 = -11000, so case (a) should take precedence in above dataset, to give result as below:

Desired Output after aggregation:  
+-----------+----------+--------+---------+--------+
|SECURITY_ID|ACCOUNT_NO|LONG_IND|SHORT_IND|QUANTITY|
+-----------+----------+--------+---------+--------+
|       SEC1|      ACC4|     444|     4444|  -11000|
+-----------+----------+--------+---------+--------+

尝试的方法：

val resultDF = df
    .groupBy("SECURITY_ID")
    .agg(
      max($"SECURITY_ID").as("SECURITY_ID"),
      max($"ACCOUNT_NO").as("ACCOUNT_NO"),
      max(when($"SUM_QUANTITY" > 0, $"LONG_IND")).as("LONG_IND"),
      max(when($"SUM_QUANTITY" < 0, $"SHORT_IND")).as("SHORT_IND"),
      sum($"QUANTITY").cast("Long").as("SUM_QUANTITY")
    )
    .toDF("SECURITY_ID", "ACCOUNT_NO","LONG_IND","SHORT_IND","QUANTITY")

有没有可能以某种方式使用秩来得到这个结果？