如何仅使用rdd而不是数据帧从spark中的csv中获取N（th）列

Question

I want to select a column from a csv file using only rdd function, not dataframe in spark. I have written code for it.

Some of the other columns have an empty value.

rdd = spark.sparkContext.textFile(filename)    
rdd_parc = rdd.map(lambda x: x.split(","))
rdd1 = rdd_parc.map(lambda x: x[6] != "")

But this solution seems that it will not select the column 6 but it instead selects the element 6 of the map.

Sample data:

Lachine,H,0,,,,"SUMMERLEA, PARC",FR,2016,287826.19201900001,5033164.33193000030,-73.7169573579999,45.4382054
Lachine,H,0,,,,"SUMMERLEA, PARC",FR,2016,287826.19201900001,5033164.33193000030,-73.7169573579999,45.4382054

You can see that some values are empty. I want my answer to be

SUMMERLEA, PARC
SUMMERLEA, PARC

Answer 1

Done try using to to convert to rdd first by

rdd = spark.read.csv(filename, header=True).rdd

Then extract the sixth column by

rdd_parc = rdd.map(lambda x: x[6])

You will get the desired output