Forward-fill missing data in PySpark not working - pyspark

Question

I have a simple dataset as shown under.
| id| name| country| languages|
|1 | Bob| USA| Spanish|
|2 | Angelina| France| null|
|3 | Carl| Brazil| null|
|4 | John| Australia| English|
|5 | Anne| Nepal| null|
I am trying to impute the null values in languages with the last non-null value using pyspark.sql.window to create a window over certain rows but nothing is happening. The column which is supposed to be have null values filled, temp_filled_spark, remains unchanged i.e a copy of original languages column.
from pyspark.sql import Window
from pyspark.sql.functions import last
window = Window.partitionBy('name').orderBy('country').rowsBetween(-sys.maxsize, 0)
filled_column = last(df['languages'], ignorenulls=True).over(window)
df = df.withColumn('temp_filled_spark', filled_column)
df.orderBy('name', 'country').show(100)
I expect the output column to be:
|temp_filled_spark|
| Spanish|
| Spanish|
| Spanish|
| English|
| English|
Could anybody help pointing out the mistake?

Answer 1

we can create window considering entire dataframe as one partition as,
from pyspark.sql import functions as F
>>> df1.show()
+---+--------+---------+---------+
| id| name| country|languages|
+---+--------+---------+---------+
| 1| Bob| USA| Spanish|
| 2|Angelina| France| null|
| 3| Carl| Brazil| null|
| 4| John|Australia| English|
| 5| Anne| Nepal| null|
+---+--------+---------+---------+
>>> w = Window.partitionBy(F.lit(1)).orderBy(F.lit(1)).rowsBetween(-sys.maxsize, 0)
>>> df1.select("*",F.last('languages',True).over(w).alias('newcol')).show()
+---+--------+---------+---------+-------+
| id| name| country|languages| newcol|
+---+--------+---------+---------+-------+
| 1| Bob| USA| Spanish|Spanish|
| 2|Angelina| France| null|Spanish|
| 3| Carl| Brazil| null|Spanish|
| 4| John|Australia| English|English|
| 5| Anne| Nepal| null|English|
+---+--------+---------+---------+-------+
Hope this helps.!