How to update a field in a nested array in Bigquery? - google-bigquery

Question

I am trying to update a table that has STRUCT(a few fields, ARRAY(STRUCT)).
The field that I need to update is inside the array and I am having trouble with making it work.
Here is the layout of the the two tables:
CREATE TABLE mydatset.orders (
order_id string,
order_time timestamp,
trans STRUCT <
id string,
amount INT64,
accounts ARRAY<STRUCT <
role STRING ,
account_id STRING,
region STRING,
amount INT64> > >
)
CREATE TABLE mydatset.relocations (
account_id string,
region string
)
Trying to update the region of any account in the array accounts if that account exists in the relocations table:
update mydataset.orders a
set trans = (SELECT AS STRUCT trans.* REPLACE(ARRAY(SELECT STRUCT<role STRING, account_id STRING, region STRING, amount INT64>
(cp.role, cp.account_id,
case when cp.account_id = ll.account_id then ll.region else cp.region end ,
cp.amount
)
) as accounts )
from unnest(trans.accounts) cp
left join unnest(relocs.chgs) ll
on cp.account_id = ll.account_id
)
from (select array_agg(struct (account_id, region) ) chgs
from`mydataset.relocations`
) relocs
where true
The syntax works, but the sql doesn't perform the expected update. The account's region in the orders table is not changed after running the above update!
(I have seen BigQuery UPDATE nested array field and this case is slightly different. The array is inside a struct and itself is an array of struct)
Appreciate any help.

Answer 1

Below is for BigQuery Standard SQL
#standardSQL
UPDATE `project.dataset.orders`
SET trans = (SELECT AS STRUCT trans.* REPLACE(
ARRAY(SELECT AS STRUCT x.* REPLACE(IFNULL(y.region, x.region) AS region)
FROM UNNEST(trans.accounts) x
LEFT JOIN UNNEST(relocations) y
USING(account_id)
) AS accounts))
FROM (SELECT ARRAY_AGG(t) relocations FROM `project.dataset.relocations` t)
WHERE TRUE
It is tested with below dummy data
initial dummy data that looks like below
[
{
"order_id": "order_id1",
"order_time": "2019-06-28 01:05:16.346854 UTC",
"trans": {
"id": "id1",
"amount": "1",
"accounts": [
{
"role": "role1",
"account_id": "account_id1",
"region": "region1",
"amount": "11"
},
{
"role": "role2",
"account_id": "account_id2",
"region": "region2",
"amount": "12"
}
]
}
},
{
"order_id": "order_id2",
"order_time": "2019-06-28 01:05:16.346854 UTC",
"trans": {
"id": "id2",
"amount": "1",
"accounts": [
{
"role": "role3",
"account_id": "account_id1",
"region": "region4",
"amount": "13"
},
{
"role": "role4",
"account_id": "account_id3",
"region": "region3",
"amount": "14"
}
]
}
}
]
after applying below adjustments
[
{
"account_id": "account_id1",
"region": "regionA"
},
{
"account_id": "account_id2",
"region": "regionB"
}
]
result is
[
{
"id": "id1",
"amount": "1",
"accounts": [
{
"role": "role1",
"account_id": "account_id1",
"region": "regionA",
"amount": "11"
},
{
"role": "role2",
"account_id": "account_id2",
"region": "regionB",
"amount": "12"
}
]
},
{
"id": "id2",
"amount": "1",
"accounts": [
{
"role": "role3",
"account_id": "account_id1",
"region": "regionA",
"amount": "13"
},
{
"role": "role4",
"account_id": "account_id3",
"region": "region3",
"amount": "14"
}
]
}
]