使用窗口函数获取 sum(countnum) 然后 divide Example: Approach1: Using window functions ```
df.show()
//+---------+--------+
//| product|countnum|
//+---------+--------+
//| Resistor| 2|
//|capacitor| 2|
//| inductor| 3|
//+---------+--------+

import org.apache.spark.sql.expressions._
import org.apache.spark.sql.functions._
val w=Window.orderBy("countnum").rowsBetween(Window.unboundedPreceding,Window.unboundedFollowing)

df.withColumn("overallprofit",col("countnum")/sum(col("countnum")).over(w)*100).show()
//+---------+--------+------------------+
//| product|countnum| overallprofit|
//+---------+--------+------------------+
//| Resistor| 2| 28.57142857142857|
//|capacitor| 2| 28.57142857142857|
//| inductor| 3|42.857142857142854|
//+---------+--------+------------------+
`Approach2: Without using window functions`
val df1=df.select(sum("countnum").alias("overall_sum"))
df.crossJoin(df1).withColumn("overallprofit",col("countnum")/col("overall_sum")*100).
drop("overall_sum").
show()
//+---------+--------+------------------+
//| product|countnum| overallprofit|
//+---------+--------+------------------+
//| Resistor| 2| 28.57142857142857|
//|capacitor| 2| 28.57142857142857|
//| inductor| 3|42.857142857142854|
//+---------+--------+------------------+

//rounding
df.crossJoin(df1).withColumn("overallprofit",concat(round(col("countnum")/col("overall_sum")*100,2),lit("%"))).drop("overall_sum").show()
//+---------+--------+-------------+
//| product|countnum|overallprofit|
//+---------+--------+-------------+
//| Resistor| 2| 28.57%|
//|capacitor| 2| 28.57%|
//| inductor| 3| 42.86%|
//+---------+--------+-------------+

//cast to decimal with one precision
df.crossJoin(df1).
withColumn("overallprofit",concat((col("countnum")/col("overall_sum")*100).cast("decimal(10,1)"),lit("%"))).
drop("overall_sum").
show()
//+---------+--------+-------------+
//| product|countnum|overallprofit|
//+---------+--------+-------------+
//| Resistor| 2| 28.6%|
//|capacitor| 2| 28.6%|
//| inductor| 3| 42.9%|
//+---------+--------+-------------+

下面的代码可能对您有所帮助。

import org.apache.spark.sql.expressions._
import org.apache.spark.sql.functions._

val df = sc.parallelize(Seq(("Resistor", 2), ("Capacitor",2), ("Inductor", 3))).toDF("Product", "countnum")
df.show()
/*
+---------+--------+                                                            
|  Product|countnum|
+---------+--------+
| Resistor|       2|
|Capacitor|       2|
| Inductor|       3|
+---------+--------+

* /

df.groupBy("Product").agg(sum("countnum").alias("sum")).withColumn("fraction", round(((col("sum") /  sum("sum").over()) *100),2)).show()
/*
+---------+---+--------+                                                        
|  Product|sum|fraction|
+---------+---+--------+
| Inductor|  3|   42.86|
| Resistor|  2|   28.57|
|Capacitor|  2|   28.57|
+---------+---+--------+

* /