pyspark - Join two data frames, select all columns from one and some columns from the other

Question

Let's say I have a spark data frame df1, with several columns (among which the column id) and data frame df2 with two columns, id and other.

Is there a way to replicate the following command

sqlContext.sql("SELECT df1.*, df2.other FROM df1 JOIN df2 ON df1.id = df2.id")

by using only pyspark functions such as join(), select() and the like?

I have to implement this join in a function and I don't want to be forced to have sqlContext as a function parameter.

Thanks!

Answer 1

Asterisk (*) works with alias. Ex:

from pyspark.sql.functions import *

df1 = df1.alias('df1')
df2 = df2.alias('df2')

df1.join(df2, df1.id == df2.id).select('df1.*')