val avgDF = Seq((Seq("Lily","Kerry","Mona"), 10),
      (Seq("Kerry", "Mona"), 2),
      (Seq("Mona"), 0)
  ).toDF("names", "sentiment")

  val avgDF1 = avgDF.withColumn("name", explode('names))
  val avgResultDF = avgDF1.groupBy("name").agg(avg(col("sentiment")))

  avgResultDF.show(false)
  //      +-----+--------------+
  //      |name |avg(sentiment)|
  //      +-----+--------------+
  //      |Lily |10.0          |
  //      |Kerry|6.0           |
  //      |Mona |4.0           |
  //      +-----+--------------+

只需分解数组，然后分组
Pypark当量

import pyspark.sql.functions as f
df1 = df.select(f.explode('names').alias('name'),'sentiment')

df1.groupBy('name').agg(f.avg('sentiment').alias('sentiment')).show()