How to replace None or null by preceding or next values in Apache Spark dataframe?

Question

Inspired by the How to replace NaNs by preceding or next values in pandas DataFrame?

Is there a way to replace every None, empty or null value with the first non-empty value in the same column above it? If you have a dataframe like:

    0   1   2
0   1   2   3
1   4  None None
2 None None 9

to become like:

   0  1  2
0  1  2  3
1  4  2  3
2  4  2  9

Spark has pyspark.sql.DataFrame.fillna but option like (method='ffill') is not available.