regexp_extract insert new row for each comma - sql

Question

Suppose we have this table and it has a column with multiple values separated by commas. I need to be able to separate the comma values and make a separate row out of it.
SELECT * FROM the_table
customer_id customer_value
1 aaa,bbb,ccc
2 ddd,ggg,ttt,lll
3 ppp,nnn,mmm,kkk,fff
I do not know if regexp_extract is the right function to use here but I am unable to create a new row.
SELECT *,
regexp_extract(customer_value,"^(?:[^,]*,){0}([^,]*)(?:[^,]*,){1}([^,]*)",1) as value_1,
regexp_extract(customer_value,"^(?:[^,]*,){0}([^,]*)(?:[^,]*,){1}([^,]*)",2) as value_2
FROM the_table
customer_id customer_value value_1 value_2
1 aaa,bbb,ccc aaa bbb
2 ddd,ggg,ttt,lll ddd ggg
3 ppp,nnn,mmm,kkk,fff ppp nnn
What I am looking for:
SELECT * FROM the_table
customer_id customer_value customer_value_comma
1 aaa,bbb,ccc aaa
1 aaa,bbb,ccc bbb
1 aaa,bbb,ccc ccc
2 ddd,ggg,ttt,lll ddd
2 ddd,ggg,ttt,lll ggg
2 ddd,ggg,ttt,lll ttt
2 ddd,ggg,ttt,lll lll.........

Answer 1

Here's your SQL:
SELECT
*,
explode( -- turn array into rows
split(customer_value, ",") -- make an array
as customer_value_comma -- rename column
)
FROM the_table
Here's it in pyspark:
from pyspark.sql.functions import split, explode, col
data = [(1,"aaa,bbb,ccc"),
(2,"ddd,ggg,ttt,lll"),
(3,"ppp,nnn,mmm,kkk,fff")]
df = sc.parallelize(data).toDF(["customer_id","customer_value"])
df.withColumn("cust_value_array",explode(split(col("customer_value"),","))).show()