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

I have the following sample DataFrame:

a | b | c   |
1 | 2 | 4   |
0 | null | null|
null | 3 | 4   |

And I want to replace null values only in the first 2 columns - Column "a" and "b":

a | b | c   |
1 | 2 | 4   |
0 | 0 | null|
0 | 3 | 4   |
 

Here is the code to create sample dataframe:

rdd = sc.parallelize([(1,2,4), (0,None,None), (None,3,4)])
df2 = sqlContext.createDataFrame(rdd, ["a", "b", "c"])

I know how to replace all null values using:

df2 = df2.fillna(0)

And when I try this, I lose the third column:

df2 = df2.select(df2.columns[0:1]).fillna(0)