Say I have a BQ table containing the following information
| id | test.name | test.score |
|---- |----------- |------------ |
| 1 | a
One option could be using conditional aggregation
select id,
max(case when test.name='a' then test.score end) as a,
max(case when test.name='b' then test.score end) as b,
max(case when test.name='c' then test.score end) as c
from
(
select a.id, t
from `table` as a,
unnest(test) as t
)A group by id
Below is generic/dynamic way to handle your case
EXECUTE IMMEDIATE (
SELECT """
SELECT id, """ ||
STRING_AGG("""MAX(IF(name = '""" || name || """', score, NULL)) AS """ || name, ', ')
|| """
FROM `project.dataset.table` t, t.test
GROUP BY id
"""
FROM (
SELECT DISTINCT name
FROM `project.dataset.table` t, t.test
ORDER BY name
)
);
If to apply to sample data from your question - output is
Row id a b c
1 1 5 7 null
2 2 8 null 3
Conditional aggregation is a good approach. If your tables are large, you might find that this has the best performance:
select t.id,
(select max(tt.score) from unnest(t.score) tt where tt.name = 'a') as a,
(select max(tt.score) from unnest(t.score) tt where tt.name = 'b') as b,
(select max(tt.score) from unnest(t.score) tt where tt.name = 'c') as c
from `table` t;
The reason I recommend this is because it avoids the outer aggregation. The unnest()
happens without shuffling the data around -- and I have found that this is a big win in terms of performance.