Get percentiles as a column in SparkR dataframe

Question

I have a Spark data frame as below (dummy data) and would want to add percentiles as a column to it using SparkR :

UserId Values
  U1     5
  U2     50
  U3     76
  .
  .
  .
  . 
  .
  U1000   8

Example:

 UserId Values   Percentile
      U1     5     0.011144
      U2     50    0.212245
      U3     76    0.811986 
      .
      .
      .
      . 
      .
      U1000   8    0.0134567

Answer 1

Well, there is a function, percent_rank , but it only operates on window partitions; adapting the documentation example:

library(SparkR)
library(magrittr)
sparkR.version()
# [1] "2.2.0"    

df <- createDataFrame(mtcars)
ws <- orderBy(windowPartitionBy("am"), "hp")
out <- select(df, over(percent_rank(), ws), df$hp, df$am)
out <- out %>% withColumnRenamed(colnames(out)[1], 'percentile') # get rid of the ridiculously long column name 
head(out)
#   percentile  hp am
# 1 0.00000000  62  0
# 2 0.05555556  95  0
# 3 0.11111111  97  0
# 4 0.16666667 105  0
# 5 0.22222222 110  0
# 6 0.27777778 123  0

If you don't want a window partition but a global percentile, as in your case, the easiest way I can think of is to add first a dummy constant column and group by this, which you can subsequently drop. So, here is the above example, but this time without partitioning by am :

df_new = df %>% withColumn("dummy", lit("N"))
ws <- orderBy(windowPartitionBy('dummy'), "hp")
out <- select(df_new, over(percent_rank(), ws), df_new$hp)
out <- out %>% withColumnRenamed(colnames(out)[1], 'percentile')

The result of collect(out) is

   percentile  hp
1  0.00000000  52
2  0.03225806  62
3  0.06451613  65
4  0.09677419  66
5  0.09677419  66
6  0.16129032  91
7  0.19354839  93
8  0.22580645  95
9  0.25806452  97
10 0.29032258 105
11 0.32258065 109
12 0.35483871 110
13 0.35483871 110
14 0.35483871 110
15 0.45161290 113
16 0.48387097 123
17 0.48387097 123
18 0.54838710 150
19 0.54838710 150
20 0.61290323 175
21 0.61290323 175
22 0.61290323 175
23 0.70967742 180
24 0.70967742 180
25 0.70967742 180
26 0.80645161 205
27 0.83870968 215
28 0.87096774 230
29 0.90322581 245
30 0.90322581 245
31 0.96774194 264
32 1.00000000 335