如何获取每个条目的所有行条目中scala-spark中数组类型列的平均值? [英] How to obtain the average of an array-type column in scala-spark over all row entries per entry?

问题描述

我有一个包含512个双元素的数组列，想要获得平均值.以length = 3的数组列为例:

I got an array column with 512 double elements, and want to get the average. Take an array column with length=3 as example:

val x = Seq("2 4 6", "0 0 0").toDF("value").withColumn("value", split($"value", " "))
x.printSchema()
x.show()


root
 |-- value: array (nullable = true)
 |    |-- element: string (containsNull = true)

+---------+
|    value|
+---------+
|[2, 4, 6]|
|[0, 0, 0]|
+---------+

需要以下结果:

x.select(..... as "avg_value").show()

------------
|avg_value |
------------
|[1,2,3]   |
------------

推荐答案

将每个数组元素视为列并计算平均值，然后使用这些列构造数组:

Consider each array element as column and calculate average then construct array with those columns:

val array_size = 3
val avgAgg = for (i <- 0 to array_size -1) yield avg($"value".getItem(i))
df.select(array(avgAgg: _*).alias("avg_value")).show(false)

赠予:

+---------------+
|avg_value      |
+---------------+
|[1.0, 2.0, 3.0]|
+---------------+

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