Large data (over 1million rows) aggregate - mongodb

Question

I am currently using the following query but hitting a small issue - It's really slow.
Is there any way that mongooseJS can either:
a) split this into smaller queries and run it in segments
b) a better way to query this data.
My query
[
{
$project: {
"location": 1,
"year": { "$year": "$timestamp" }
}
},
{
$match: { "year": 2020 }
},
{
$group: {
"_id": "$location.coordinates",
"count": { "$sum": 1 }
}
},
{
$project: {
"_id": 0,
"count": 1,
"location.coordinates": {
"$map": {
"input": "$_id",
"in": { "$toString": "$$this" }
}
}
}
},
{
$sort: { count: -1 }
}
])
in NodeJS I am querying it like I have M10 atlas so no issue running the query it works in Mongodb compass
router.get('/pastlocation', (req, res) =>{
const pastlocation = require('mongoose').model('pastlistenerslocation');
pastlocation.aggregate([
{
$project: {
"location": 1,
"year": { "$year": "$timestamp" }
}
},
{
$match: { "year": 2020 }
},
{
$group: {
"_id": "$location.coordinates",
"count": { "$sum": 1 }
}
},
{
$project: {
"_id": 0,
"count": 1,
"location.coordinates": {
"$map": {
"input": "$_id",
"in": { "$toString": "$$this" }
}
}
}
},
{ $sort: { count: -1 } }
])).allowDiskUse(true).exec(function(err,result) {
if(err){console.log(err)}
res.json(result);
});
});
Data looks like this:
{
"UUID": "9B3640AC-3AA9-4313-94DB-9DFFEC7362E1",
"location": {
"coordinates": [115.8802288492358, -31.92553401927643],
"type": "Point"
},
"timestamp": {
"$date": "2020-11-04T13:20:58.224Z"
},
"__v": 0
}