I would like to calculate group quantiles on a Spark dataframe (using PySpark). Either an approximate or exact result would be fine. I prefer a solution that I can use withi
I guess you don't need it anymore. But will leave it here for future generations (i.e. me next week when I forget).
from pyspark.sql import Window
import pyspark.sql.functions as F
grp_window = Window.partitionBy('grp')
magic_percentile = F.expr('percentile_approx(val, 0.5)')
df.withColumn('med_val', magic_percentile.over(grp_window))
Or to address exactly your question, this also works:
df.groupBy('grp').agg(magic_percentile.alias('med_val'))
And as a bonus, you can pass an array of percentiles:
quantiles = F.expr('percentile_approx(val, array(0.25, 0.5, 0.75))')
And you'll get a list in return.