How to delete columns in pyspark dataframe

>>> a
DataFrame[id: bigint, julian_date: string, user_id: bigint]
>>> b
DataFrame[id: bigint, quan_created_money: decimal(10,0), quan_created_cnt: bigint]
>>> a.join(b, a.id==b.id, 'outer')
DataFrame[id: bigint, julian_date: string, user_id: bigint, id: bigint, quan_created_money: decimal(10,0), quan_created_cnt: bigint]

There are two id: bigint and I want to delete one. How can I do?

Solution 1:

Reading the Spark documentation I found an easier solution.

Since version 1.4 of spark there is a function drop(col) which can be used in pyspark on a dataframe.

You can use it in two ways

1. df.drop('age')
2. df.drop(df.age)

Pyspark Documentation - Drop

Solution 2:

Adding to @Patrick's answer, you can use the following to drop multiple columns

columns_to_drop = ['id', 'id_copy']
df = df.drop(*columns_to_drop)