Spark Scala - 如何在数据框中迭代行，并将计算值添加为数据框的新列

Question

我有一个包含两列“date”和“value”的数据框，如何在数据框中添加2个新列“value_mean”和“value_sd”，其中“value_mean”是过去10天内“value”的平均值（包括“date”中指定的当前日期和“value_sd”是过去10天内“值”的标准差？

Answer 1

Spark sql provide the various dataframe function like avg,mean,sum etc.

you just have to apply on dataframe column using spark sql column

import org.apache.spark.sql.types._
import org.apache.spark.sql.functions._
import org.apache.spark.sql.Column

Create private method for standard deviation

private def stddev(col: Column): Column = sqrt(avg(col * col) - avg(col) * avg(col))

Now you can create sql Column for average and standard deviation

val value_sd: org.apache.spark.sql.Column = stddev(df.col("value")).as("value_sd")
val value_mean: org.apache.spark.sql.Column = avg(df.col("value").as("value_mean"))

Filter your dataframe for last 10 days or as you want

val filterDF=df.filter("")//put your filter condition 

Now yon can apply the aggregate function on your filterDF

filterDF.agg(stdv, value_mean).show