如何从数据帧中获取特定列中具有最大值的行？

Question

我有这样的数据帧

    df.show(5)
    kv   |list1     |list2                |p
   [k1,v2|[1,2,5,9  |[5,1,7,9,6,3,1,4,9]  |0.5
   [k1,v3|[1,2,5,8,9|[5,1,7,9,6,3,1,4,15] |0.9
   [k2,v2|[77,2,5,9]|[0,1,8,9,7,3,1,4,100]|0.01
   [k5,v5|[1,0,5,9  |[5,1,7,9,6,3,1,4,3]  |0.3
   [k9,v2|[1,2,5,9  |[5,1,7,9,6,3,1,4,200]|2.5
   df.count()
   5200158

我想获得最大p的行,这对我来说很有用,但我不知道是否有另一种清洁方式

     val f = df.select(max(struct(
    col("pp") +: df.columns.collect { case x if x != "p" => col(x) }: _*
  ))).first()

Answer 1

只需按顺序排序:

import org.apache.spark.sql.functions.desc

df.orderBy(desc("pp")).take(1)

要么

df.orderBy(desc("pp")).limit(1).first