Big query nested json strings to arrays then new tables - arrays

Question

Bigquery Database
I've got a webhook that's pushing to my big query table. The problem is it has lots of nested json strings which are brought in as strings. I ultimately want to make each column with these json strings into their own tables but I'm getting stuck because I can't figure out how to get them unnested and into an array.
[{"id":"63bddc8cfe21ec002d26b7f4","description":"General Admission", "src_currency":"USD","src_price":50.0,"src_fee":0.0,"src_commission":1.79,"src_discount":0.0,"applicable_pass_id":null,"seats_label":null,"seats_section_label":null,"seats_parent_type":null,"seats_parent_label":null,"seats_self_type":null,
"seats_self_label":null,"rate_type":"Rate","option_name":null,"price_level_id":null,"src_discount_price":50.0,"rate_id":"636d6d5cea8c6000222c640d","cost_item_id":"63bddc8cfe21ec002d26b7f4"}]
Here's the sample return from the original source and below is a screenshot of what I'm working with.
[Current Database
I've tried a number of things but the multiple nestings and string to array issue are really hampering everything I've tried.
I'm honestly not sure exactly what output/structure is best for this data set. I assume that each of the json returns probably just needs to be its own table and I can reference or join them based off that first "id" value in the json strings but I'm wide open to suggestions.

Answer 1

You can use a combination of JSON functions, and array functions to manipulate this kind of data.
JSON_EXTRACT_ARRAY can convert the JSON formatted string into an array, UNNEST then can make each entry into rows, and finally JSON_EXTRACT_SCALAR can pull out individual columns.
So here's an example of what I think you're trying to accomplish:
with sampledata as (
select """[{"id":"63bddc8cfe21ec002d26b7f4","description":"General Admission", "src_currency":"USD","src_price":50.0,"src_fee":0.0,"src_commission":1.79,"src_discount":0.0,"applicable_pass_id":null,"seats_label":null,"seats_section_label":null,"seats_parent_type":null,"seats_parent_label":null,"seats_self_type":null,"seats_self_label":null,"rate_type":"Rate","option_name":null,"price_level_id":null,"src_discount_price":50.0,"rate_id":"636d6d5cea8c6000222c640d","cost_item_id":"63bddc8cfe21ec002d26b7f4"},{"id":"63bddc8cfe21ec002d26b7f4","description":"General Admission", "src_currency":"USD","src_price":50.0,"src_fee":0.0,"src_commission":1.79,"src_discount":0.0,"applicable_pass_id":null,"seats_label":null,"seats_section_label":null,"seats_parent_type":null,"seats_parent_label":null,"seats_self_type":null,"seats_self_label":null,"rate_type":"Rate","option_name":null,"price_level_id":null,"src_discount_price":50.0,"rate_id":"636d6d5cea8c6000222c640d","cost_item_id":"63bddc8cfe21ec002d26b7f4"}]""" as my_json_string
)
select JSON_EXTRACT_SCALAR(f,'$.id') as id, JSON_EXTRACT_SCALAR(f,'$.rate_type') as rate_type, JSON_EXTRACT_SCALAR(f,'$.cost_item_id') as cost_item_id
from sampledata, UNNEST(JSON_EXTRACT_ARRAY(my_json_string)) as f
Which creates rows with specific columns from that data, like this: