如何从特定列中具有最大值的数据框中获取行? [英] How to get the row from a dataframe that has the maximum value in a specific column?

问题描述

我有一个这样的数据框

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，下面的这个对我有用，但是我不知道是否还有另一种更干净的方法

I want to get the row that have maximum p, this below works for me but I don't know if there is another cleaner way

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

推荐答案

只需排序，然后取:

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

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

或

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

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