BigQuery - Extract nested children JSON as rows - sql

Question

I have a JSON structure in a field that looks like this. I'm trying to extract the task viewed and completed date, there could be any number of tasks in each field.
Sample data
"task_1a232445": {
"completedDate": {
"_seconds": 1670371200,
"_nanoseconds": 516000000
},
"viewedDate": {
"_seconds": 1666652400,
"_nanoseconds": 667000000
}
},
"task_1a233445": {
"completedDate": {
"_seconds": 1670198400,
"_nanoseconds": 450000000
},
"viewedDate": {
"_seconds": 1674000000,
"_nanoseconds": 687000000
}
}
}
I have tried to adapt this previous question I asked, but where there are multiple tasks in a single row (as sample data) I can only return the first completedDate

Answer 1

Consider below approach
create temp function extract_keys(input string) returns array<string> language js as """
return Object.keys(JSON.parse(input));
""";
create temp function extract_values(input string) returns array<string> language js as """
return Object.values(JSON.parse(input));
""";
create temp function get_leaves(input string) returns string language js as '''
function flattenObj(obj, parent = '', res = {}){
for(let key in obj){
let propName = parent ? parent + '.' + key : key;
if(typeof obj[key] == 'object'){
flattenObj(obj[key], propName, res);
} else {
res[propName] = obj[key];
}
}
return JSON.stringify(res);
}
return flattenObj(JSON.parse(input));
''';
select * from (
select
arr[safe_offset(0)] task,
arr[safe_offset(1)] date,
date(timestamp_seconds(cast(val as int64))) val
from your_table, unnest([get_leaves(json)]) leaves,
unnest(extract_keys(leaves)) key with offset
join unnest(extract_values(leaves)) val with offset
using(offset),
unnest([struct(split(key, '.') as arr)])
where arr[safe_offset(2)] = '_seconds'
)
pivot (any_value(val) for date in ('completedDate', 'viewedDate'))
if applied to sample data in your question
with your_table as (
select '''{
"task_1a232445": {
"completedDate": {
"_seconds": 1670371200,
"_nanoseconds": 516000000
},
"viewedDate": {
"_seconds": 1666652400,
"_nanoseconds": 667000000
}
},
"task_1a233445": {
"completedDate": {
"_seconds": 1670198400,
"_nanoseconds": 450000000
},
"viewedDate": {
"_seconds": 1674000000,
"_nanoseconds": 687000000
}
}
}
''' as json
)
output is