I have a list of coordinates for each of them I need to perform $geoIntersects query. For one coordinate the query looks like this:
db.polygons.find({
geometry: {
$geoIntersects: {
$geometry: {
type: "Point", coordinates: [24.053640, 49.812427]
}
}
}
})
The problem is that there is a list of input coordinates and for each of them I need to find a polygon. The only way I've found so far is to iterate over them in application code and execute query N times.
Is it possible to do it with one MongoDB query? If not, any ideas on how this can optimized are appreciated.
One possible solution is replacing the Point geometry type with the MultiPoint one, and passing in the the list of input coordinates as an array.
db.polygons.find({
geometry: {
$geoIntersects: {
$geometry: {
type: "MultiPoint", coordinates: [[24.053640, 49.812427],[...]...]
}
}
}
})
Related
I have a collection (users) with 356 documents and an index "2dsphere" on the field geodata. 120 documents have a field geodata:{type:"Point", coordinates:[X,Y]} where X and Y are coordinates within Germany.
If I execute the following aggregation:
db.users.aggregate(
[
{
"$geoNear":{
near: { type: "Point", coordinates: [48.783469, 9.181842] },
distanceField: "distanceCalculated",
spherical: true
}
},
{
"$sort":{"distanceCalculated":1}
}
]
)
I get 46 results, but as I understand, I should get at least 100 (standard for the limit parameter)
As I can see, all results are within ~210 kilometers is there any not documented standard maxDistance? I also tried different maxDistance values but never get more than 48 results.
My question is, what do I have to do to get all (120) results ordered by distance?
Found the pitfall:
All (120) documents had the type of geodata.coordinates set to object instead of array. Unfortunately I can't say why mongoDB nevertheless returned some results instead of null. I converted all entries using the following command, now it works:
db.users.find({ "geodata": { $exists: true, $ne: null }}).forEach((user)=> {
var coordinates = user.geodata.coordinates;
user.geodata.coordinates = [coordinates["0"], coordinates["1"]];
db.users.save(user);
});
I have a question about use of $near vs geonear in returning distance from stored points in database from the user entered point of interest, if more than one 2dsphere index is present in the schema storing the points.
The use case is below.
In my schema I have a source and a destination location as below. The query using Intracity.find works properly and gives me sorted entries from an entered point of interest.
var baseShippingSchema = new mongoose.Schema({
startDate : Date,
endDate : Date,
locSource: {
type: [Number],
index: '2dsphere'
},
locDest: {
type: [Number],
index: '2dsphere'
}
});
var search_begin = moment(request.body.startDate0, "DD-MM-YYYY").toDate();
var search_end = moment(request.body.endDate1, "DD-MM-YYYY").toDate();
var radius = 7000;
Intracity.find({
locSource: {
$near:{$geometry: {type: "Point",
coordinates: [request.body.lng0,request.body.lat0]},
$minDistance: 0,
$maxDistance: radius
}
}).where('startDate').gte(search_begin)
.where('endDate').lte(search_end)
.limit(limit).exec(function(err, results)
{
response.render('test.html', {results : results, error: error});
}
However, I also want to return the "distance" of the stored points from the point of interest, which as per my knowledge and findings, is not possible using $near but is possible using geonear api.
However, the documentation of geonear says the following.
geoNear requires a geospatial index. However, the geoNear command requires that a collection have at most only one 2d index and/or only one 2dsphere.
Since in my schema I have two 2dspehere indexes the following geonear api fails with the error "more than one 2d index, not sure which to run geoNear on"
var point = { name: 'locSource', type : "Point",
coordinates : [request.body.lng0 , request.body.lat0] };
Intracity.geoNear(point, { limit: 10, spherical: true, maxDistance:radius, startDate:{ $gte: search_begin}, endDate:{ $lte:search_end}}, function(err, results, stats) {
if (err){return done(err);}
response.render('test.html', {results : results, error: error});
});
So my question is how can I also get the distance for each of these stored points, from entered point of interest using the schema described above.
Any help would be really great, as my Internet search is not going anywhere.
Thank you
Mrunal
As you noted the mongodb docs state that
The geoNear command and the $geoNear pipeline stage require that a collection have at most only one 2dsphere index and/or only one 2d index
On the other hand calculating distances inside mongo is only possible with the aggregation framework as it is a specialized projection. If you do not want to take option
relational DB approach: maintaining a separate distance table between all items
then your other option is to
document store approach: calculate distances in your server side JS code. You would have to cover memory limits by paginating results.
The spatial reference of my data is based on BaiDu Map,now I'd like to create a 2dsphere index.so Did I need to make the coordinate conversion from the spatial reference of BaiDu Map to WGS84? Thank you very much!
The 2dsphere index overwiew in MongoDB documentation seems to say so:
The default datum for an earth-like sphere is WGS84. Coordinate-axis order is longitude, latitude.
What is important to remember is that your location data need to include geometry data.
You can't create a 2dsphere index on:
location : { coordinates: [ -73.97, 40.77 ] }
But you can on:
location : { type: "Point", coordinates: [ -73.97, 40.77 ] }
I am using the following example to better explain my need.
I have a set of points(users) on a map and collection schema is as below
{
location:{
latlong:[long,lat]
},
maxDistance:Number
}
i have another collection with events happening in the area. schema is given below
{
eventLocation:{
latlong:[long,lat]
}
}
now users can add their location and the maximum distance they want to travel for to attend an event and save it.
whenever a new event is posted , all the users satisfying their preferences will get a notification. Now how do i query that. i tried following query on user schema
{
$where: {
'location.latlong': {
$near: {
$geometry: {
type: "Point",
coordinates: [long,lat]
},
$maxDistance: this.distance
}
}
}
}
got an error
error: {
"$err" : "Can't canonicalize query: BadValue $where got bad type",
"code" : 17287
}
how do i query the above case as maxDistance is defined by user and is not fixed. i am using 2dsphere index.
Presuming you have already worked out to act on the event data as you recieve it and have it in hand ( if you have not, then that is another question, but look at tailable cursors ), then you should have an object with that data for which to query the users with.
This is therefore not a case for JavaScript evaluation with $where, as it cannot access the query data returned from a $near operation anyway. What you want instead is $geoNear from the aggregation framework. This can project the "distance" found from the query, and allow a later stage to "filter" the results against the user stored value for the maximum distance they want to travel to published events:
// Represent retrieved event data
var eventData = {
eventLocation: {
latlong: [long,lat]
}
};
// Find users near that event within their stored distance
User.aggregate(
[
{ "$geoNear": {
"near": {
"type": "Point",
"coordinates": eventData.eventLocation.latlong
},
"distanceField": "eventDistance",
"limit": 100000,
"spherical": true
}},
{ "$redact": {
"$cond": {
"if": { "$lt": [ "$eventDistance", "$maxDistance" ] },
"then": "$$KEEP",
"else": "$$PRUNE"
}
}}
]
function(err,results) {
// Work with results in here
}
)
Now you do need to be careful with the returned number, as since you appear to be storing in "legacy coordinate pairs" instead of GeoJSON, then the distance returned from this operation will be in radians and not a standard distance. So presuming you are storing in "miles" or "kilometers" on the user objects then you need to calculate via the formula mentioned in the manual under "Calculate Distances Using Spherical Geometry" as mentioned in the manual.
The basics are that you need to divide by the equatorial radius of the earth, being either 3,963.2 miles or 6,378.1 kilometers to convert for a comparison to what you have stored.
The alternate is to store in GeoJSON instead, where there is a consistent measurement in meters.
Assuming "kilometers" that "if" line becomes:
"if": { "$lt": [
"$eventDistance",
{ "$divide": [ "$maxDistance", 6,378.1 ] }
]},
To reliably compare your stored kilometer value to the radian result retured.
The other thing to be aware of is that $geoNear has a default "limit" of 100 results, so you need to "pump up" the "limit" argument there to the number for expected users to possibly match. You might even want to do this in "range lists" of user id's for a really large system, but you can go as big as memory allows within a single aggreation operation and possibly add allowDiskUse where needed.
If you don't tune that parameter, then only the nearest 100 results ( default ) will be returned, which may well no even suit your next operation of filtering those "near" the event to start with. Use common sense though, as you surely have a max distance to even filter out potential users, and that can be added to the query as well.
As stated, the point here is returning the distance for comparison, so the next stage is the $redact operation which can fiter the user's own "travel distance" value against the returned distance from the event. The end result gives only those users that fall within their own distance contraint from the event who will qualify for notification.
That's the logic. You project the distance from the user to the event and then compare to the user stored value for what distance they are prepared to travel. No JavaScript, and all native operators that make it quite fast.
Also as noted in the options and the general commentary, I really do suggest you use a "2dsphere" index for accurate spherical distance calculation as well as converting to GeoJSON storage for your coordinate storage in your database Objects, as they are both general standards that produce consistent results.
Try it without embedding your query in $where: {. The $where operator is for passing a javascript function to the database, which you don't seem to want to do here (and is in fact something you should generally avoid for performance and security reasons). It has nothing to do with location.
{
'location.latlong': {
$near: {
$geometry: {
type: "Point",
coordinates: [long,lat]
},
$maxDistance: this.distance
}
}
}
im breaking my head with mongo and geospatial,
so maybe someone has some idea or solution how to solve this:
my object schema is like this sample for geoJSON taken from http://geojson.org/geojson-spec.html.
{
"name":"name",
"geoJSON":{
"type":"FeatureCollection",
"features":[
{"type":"Feature","geometry":{"type":"Polygon","coordinates":[[[100,0],[101,0],[101,1],[100,1],[100,0]]]},"properties":{}},
{"type":"Feature","geometry":{"type":"Polygon","coordinates":[[[100,0],[101,0],[101,1],[100,1],[100,0]]]},"properties":{}},
{"type":"Feature","geometry":{"type":"Polygon","coordinates":[[[100,0],[101,0],[101,1],[100,1],[100,0]]]},"properties":{}}
]}}
additional info: I'm using spring data but that shouldn't influence the answer.
main problem is how/where to put indexes in this schema. I need to make a query to find all documents for given Point if some polygon intersects.
thanks in advance.
By creating a 2d or 2dsphere index on geoJSON.features.geometry you should be able to create an index covering all of the geoJSON-objects.
To get all documents where at least one of the sub-object in the features array covers a certain point, you can use the $geoIntersects operator with a geoJSON Point:
db.yourcollection.find(
{ `geoJSON.features.geometry` :
{ $geoIntersects :
{ $geometry :
{ type : "Point" ,
coordinates: [ 100.5 , 0.5 ]
}
}
}
}
)