I have a table that looks like this
keyA | data:{"value":false}}
keyB | data:{"value":3}}
keyC | data:{"value":{"paid":10,"unpaid":20}}}
For keyA
,keyB
I can easily extract a single value with JSON_EXTRACT_SCALAR
, but for keyC
I would like to return multiple values and change the key name, so the final output looks like this:
keyA | false
keyB | 3
keyC-paid | 10
keyD-unpaid | 20
I know I can use UNNEST and JSON_EXTRACT multiple values and create additional but unsure how to combine them to adjust the key column name as well?
CodePudding user response:
Try this one:
WITH sample AS (
SELECT 'keyA' AS col, '{"value":false}' AS data
UNION ALL
SELECT 'keyB' AS col, '{"value":3}' AS data
UNION ALL
SELECT 'keyC' AS col, '{"value":{"paid":10,"unpaid":20}}' AS data
)
SELECT col || IFNULL('-' || k, '') AS col,
IFNULL(v, JSON_VALUE(data, '$.value')) AS data
FROM (
SELECT col, data,
`bqutil.fn.json_extract_keys`(JSON_QUERY(data, '$.value')) AS keys,
`bqutil.fn.json_extract_values`(JSON_QUERY(data, '$.value')) AS vals
FROM sample
) LEFT JOIN UNNEST(keys) k WITH OFFSET ki
LEFT JOIN UNNEST(vals) v WITH OFFSET vi ON ki = vi;
CodePudding user response:
Even more generic 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 extract_all_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 col || replace(replace(key, 'value', ''), '.', '-') as col, value,
from your_table,
unnest([struct(extract_all_leaves(data) as json)]),
unnest(extract_keys(json)) key with offset
join unnest(extract_values(json)) value with offset
using(offset)
if applied to sample data in your question - output is
Benefit of this approach is that it is quite generic and thus can handle any level of nesting in json
For example for below data/table
the output is