In find query you need to use location
instead of location.coordinates
.
router.get("/test", async (req, res) => {
const lat = 59.9165591;
const lng = 10.7881978;
const maxDistanceInMeters = 1000;
const result = await model
.find({
location: {
$near: {
$geometry: {
type: "Point",
coordinates: [lng, lat],
},
$maxDistance: maxDistanceInMeters,
},
},
})
.sort("-score");
res.send(result);
});
For $near to work you need an 2dsphere index on the related collection:
db.collection.createIndex( { "location" : "2dsphere" } )
In mongodb $near docs it says:
$near sorts documents by distance. If you also include a sort() for
the query, sort() re-orders the matching documents, effectively
overriding the sort operation already performed by $near. When using
sort() with geospatial queries, consider using $geoWithin operator,
which does not sort documents, instead of $near.
Since you are not interested in sorting by distance, as Nic indicated using $near is unnecessary, better to use $geoWithin like this:
router.get("/test", async (req, res) => {
const lat = 59.9165591;
const lng = 10.7881978;
const distanceInKilometer = 1;
const radius = distanceInKilometer / 6378.1;
const result = await model
.find({
location: { $geoWithin: { $centerSphere: [[lng, lat], radius] } },
})
.sort("-score");
res.send(result);
});
To calculate radius we divide kilometer to 6378.1, and miles to 3963.2 as described here.
So this will find the locations inside 1km radius.
Sample docs:
[
{
"location": {
"type": "Point",
"coordinates": [
10.7741692,
59.9262198
]
},
"score": 50,
"_id": "5ea9d4391e468428c8e8f505",
"name": "Name1"
},
{
"location": {
"type": "Point",
"coordinates": [
10.7736078,
59.9246991
]
},
"score": 70,
"_id": "5ea9d45c1e468428c8e8f506",
"name": "Name2"
},
{
"location": {
"type": "Point",
"coordinates": [
10.7635027,
59.9297932
]
},
"score": 30,
"_id": "5ea9d47b1e468428c8e8f507",
"name": "Name3"
},
{
"location": {
"type": "Point",
"coordinates": [
10.7635027,
59.9297932
]
},
"score": 40,
"_id": "5ea9d4971e468428c8e8f508",
"name": "Name4"
},
{
"location": {
"type": "Point",
"coordinates": [
10.7768093,
59.9287668
]
},
"score": 90,
"_id": "5ea9d4bd1e468428c8e8f509",
"name": "Name5"
},
{
"location": {
"type": "Point",
"coordinates": [
10.795769,
59.9190384
]
},
"score": 60,
"_id": "5ea9d4e71e468428c8e8f50a",
"name": "Name6"
},
{
"location": {
"type": "Point",
"coordinates": [
10.1715157,
59.741873
]
},
"score": 110,
"_id": "5ea9d7d216bdf8336094aa92",
"name": "Name7"
}
]
Output: (within 1km and sorted by descending score)
[
{
"location": {
"type": "Point",
"coordinates": [
10.7768093,
59.9287668
]
},
"score": 90,
"_id": "5ea9d4bd1e468428c8e8f509",
"name": "Name5"
},
{
"location": {
"type": "Point",
"coordinates": [
10.7736078,
59.9246991
]
},
"score": 70,
"_id": "5ea9d45c1e468428c8e8f506",
"name": "Name2"
},
{
"location": {
"type": "Point",
"coordinates": [
10.795769,
59.9190384
]
},
"score": 60,
"_id": "5ea9d4e71e468428c8e8f50a",
"name": "Name6"
},
{
"location": {
"type": "Point",
"coordinates": [
10.7741692,
59.9262198
]
},
"score": 50,
"_id": "5ea9d4391e468428c8e8f505",
"name": "Name1"
}
]