MongoDB convert Select from UNION with Group By with sum - mysql

Question

I'm building a COVID API in NodeJS which have very in-depth detail about my country.
Due huge bill I decided to rewrite my whole database from MySQL to NoSQL which is more affordable for me.
Basically what I have to do is, if date_onset is empty then I will use date_specimen as proxy.
I have the following MySQL query which I need to convert to NoSQL.
SELECT count(a.cases) as cases, a.date FROM
(SELECT date_specimen AS cases, date_specimen AS date from case_informations WHERE (date_specimen <> '' AND date_onset = '')
UNION ALL
SELECT date_onset AS cases, date_onset AS date FROM case_informations WHERE date_onset <> '') AS a
GROUP BY a.date ORDER BY a.date ASC
The Document:
{
"_id": {
"$oid": "5f29a6dcc4ce73be6be928ff"
},
"case_code": "C611583",
"age": 20,
"age_group": "20-24",
"sex": "female",
"date_specimen": "",
"date_result_release": "2020-04-22",
"date_rep_conf": "2020-04-24",
"date_died": "",
"date_recover": "",
"removal_type": "recovered",
"admitted": "no",
"region_res": "NCR",
"prov_res": "",
"city_mun_res": "",
"city_muni_psgc": "",
"health_status": "recovered",
"quarantined": "no",
"date_onset": "",
"pregnant_tab": "no",
"validation_status": "Removal Type is \"Recovered\", but no Recovered Date is recorded\nRemoval Type is \"Recovered\", but no Recovered Date is recorded\nHealth Status is \"Recovered\", but no Date Recovered is recorded\nHealth Status is \"Recovered\", but no Date Recovered is recorded"
}
This is the closest I can get:
collection.aggregate([
{$project: {date_specimen: 1, date_onset: 1}},
{$lookup:
{
from: 'case_informations',
pipeline: [
{$match: {date_specimen: {$exists: true}, date_onset: ''}},
{$group: {_id: '$date_specimen', cases: {$sum: 1}}},
{$sort: {_id: 1}},
],
as: 'a',
},
},
{$lookup:
{
from: 'case_informations',
pipeline: [
{$match: {date_onset: {$exists: true}}},
{$group: {_id: '$date_onset', cases: {$sum: 1}}},
{$sort: {_id: 1}},
],
as: 'b',
},
},
{$project: {'a': 1, 'b': 1}},
]).limit(1);
result:
{
_id: 5f29a6dcc4ce73be6be928fc,
a: [
{ _id: '2020-03-04', cases: 1 },
{ _id: '2020-03-06', cases: 8 },
{ _id: '2020-03-07', cases: 48 },
{...}
],
b: [
{ _id: '2020-03-03', cases: 45 },
{ _id: '2020-03-04', cases: 32 },
{ _id: '2020-03-05', cases: 55 },
{...}
]
}
expected:
{
_id: 5f29a6dcc4ce73be6be928fc,
UnionOfAandC: [
{ _id: '2020-03-03', cases: 45 },
{ _id: '2020-03-04', cases: 33 }, // merge object with same date
{ _id: '2020-03-05', cases: 55 },
{ _id: '2020-03-06', cases: 8 },
{ _id: '2020-03-07', cases: 48 },
{...},
],
}

Answer 1

After some trial and error I finally solved it
await collection.aggregate([
{$match: {$or: [{'date_onset': {'$ne': ''}}, {'date_specimen': {'$ne': ''}}]}},
{
$group: {
_id: {
'date': {
$cond: {
if: {$eq: ['$date_onset', '']}, then: '$date_specimen', else: '$date_onset',
},
},
},
cases: {$sum: 1},
},
},
{$sort: {'_id.date': 1}},
{$project: {'_id': 0, 'date': '$_id.date', 'cases': 1}},
]);