PySpark: How to fillna values in dataframe for specific columns?

Question

I have the following sample DataFrame:

a    | b    | c   | 

1    | 2    | 4   |
0    | null | null| 
null | 3    | 4   |

And I want to rep

Answer 1

Use a dictionary to fill values of certain columns:

df.fillna( { 'a':0, 'b':0 } )

Answer 2

df.fillna(0, subset=['a', 'b'])

There is a parameter named subset to choose the columns unless your spark version is lower than 1.3.1