Postgres SQL aggregates query in BigQuery? - sql

Question

For Below Postgres SQL query, I do use PIVOT in BigQuery, beside PIVOT, any other method for such query in BigQuery?
-- Postgres SQL --
SELECT
Apple,
Orange,
Lemon,
CASE WHEN Apple >= 50 THEN 1 ELSE 0 END AS Apple50
CASE WHEN Orange >= 50 THEN 1 ELSE 0 END AS Orange50
CASE WHEN Lemon >= 50 THEN 1 ELSE 0 END AS Lemon50
FROM (
SELECT td.timestamp,
COALESCE(MAX(td.value) FILTER (WHERE attribute_id = 16), 0) as Apple,
COALESCE(MAX(td.value) FILTER (WHERE attribute_id = 17), 0) as Orange,
COALESCE(MAX(td.value) FILTER (WHERE attribute_id = 18), 0) as Lemon
FROM TableData td
WHERE td.attribute_id IN (16, 17, 18)
GROUP BY td.timestamp
ORDER BY timestamp;
) AS td2
-- My attempt BigQuery Query --
SELECT
value_16 as Apple,
value_17 as Orange,
value_18 as Lemon,
CASE WHEN value_16 >= 50 THEN 1 ELSE 0 END as Apple50
CASE WHEN value_17 >= 50 THEN 1 ELSE 0 END as Orange50
CASE WHEN value_18 >= 50 THEN 1 ELSE 0 END AS Lemon50
FROM (
SELECT * FROM(
SELECT
timestamp,
attribute_id,
value
FROM `PROJECT_ID.DB_NAME.FRUITS` as td
WHERE td.attribute_id IN (16,17,18)
)PIVOT
(
MAX(value) as value
FOR attribute_id IN (16,17,18)
)
)as td2
Below is the sample relation of the table.
-- TableData --
attribute_id | value | timestamp |
--------------+-----------+------------+
17 | 100 | 1618822794 |
17 | 100 | 1618822861 |
16 | 50 | 1618822794 |
16 | 50 | 1618822861 |
-- TableAttribute --
id | name |
--------------+----------+
16 | Apple |
17 | Orange |
18 | Lemon |
-- Expected Result --
timestamp | Apple | Orange | Lemon | Apple50 | Orange50 | Lemon50 |
--------------+---------+--------+-------+---------+----------+---------+
1618822794 | 50 | 100 | 0 | 1 | 1 | 0
1618822861 | 50 | 100 | 0 | 1 | 1 | 0

Answer 1

Pivot is likely the best way to achieve what you're wanting. Consider the following approach though as it might be simpler to manage:
with aggregate_data as (
select td.timestamp
, ta.name
, td.value as value
from TableData td
full outer join TableAttribute ta
on td.attribute_id = ta.id
)
select timestamp
, value_Apple as Apple
, value_Orange as Orange
, value_Lemon as Lemon
, _50_Apple as Apple50
, _50_Orange as Orange50
, _50_Lemon as Lemon50
from aggregate_data
pivot(max(value) value, max(case when value >=50 then 1 else 0 end) _50 for name in ('Apple', 'Orange', 'Lemon'))
where timestamp is not null