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How to define a circle for a mongo db schema?
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Closed 6 years ago.
I'm getting in trouble when I try to run this code on mongodb
var partners = db.partners.find({})
var kmToRadius = function(km){
var earthRadiusInKm = 6378.1;
return km / earthRadiusInKm;
}
db.runCommand({
$centerSphere: [ [partners.loc], kmToRadius(partners.km) ] :{
$geoIntersects:{
$geometry: { type: "Point", coordinates: [ -73.93414657, 40.82302903 ] }
}
}
})
What I'm trying to do is get all the partners location (which are in geojson format), make a circle using $centerSphere and verify if there is intersection with a coordinate.
I know I can't store circles in GeoJson format, only polygons, which turns very difficult to do what I want. Someone knows if there is another way to make this work ? Thanks
My partners collection seems like this:
{
"_id" : ObjectId("583315cfa9d41218cc9c833f"),
"updatedAt" : ISODate("2016-11-21T15:42:07.703Z"),
"createdAt" : ISODate("2016-11-21T15:42:07.703Z"),
"name" : "partnerName",
"mainEmail" : "email",
"password" : "$2a$10$WJC6WzZNM8NyDKQgovJa.OICLOMV6Qp6xcGLE3fRcUGuBa8Zhy8qy",
"km" : 10,
"loc" : {
"type" : "Point",
"coordinates" : [
-46.62217,
-23.668224
]
},
"rate" : 4,
"nServices" : 35
}
But what I want to do is create a radius for each partner and check which partners intersects a point, instead of get the partners within a radius.
Related
I am using mongoose, nodejs with MVC architecture.
So, I have two collections crops and pesticides. I want a many to many relationship between these two collections.
For example, if I have 2 crops like below:
{
"_id" : ObjectId("5af1d1d54558fae1d0010bb4"),
"nameOfCrop" : "Tomato",
"imageOfCrop" : "tomatoimage",
"soilType" : " almost all soil types except heavy clay",
"waterNeeded" : "water once every two or three days",
"tagCrop" : "Vegetables",
"pesticideForCrop" : [ ]
}
{
"_id" : ObjectId("5af1d1d54558fae1d0010bb5"),
"nameOfCrop" : "Brinjal",
"imageOfCrop" : "brinjalimage",
"soilType" : "all types of soil varying from light sandy to heavy clay",
"waterNeeded" : "Regularly irrigated",
"tagCrop" : "Vegetables",
"pesticideForCrop" : [ ]
}
and two pesticides like below:
{
"_id" : ObjectId("5af7d3e735d4222b78a93838"),
"cropForPesticide" : [ ],
"nameOfPesticide" : "pesticide8",
"imageOfPesticide" : "p8image",
"__v" : 0
}
{
"_id" : ObjectId("5af7d49122b63e0824ed2d3d"),
"cropForPesticide" : [ ],
"nameOfPesticide" : "pesticide9",
"imageOfPesticide" : "p9image",
"__v" : 0
}
What I want is that tomato's pesticideForCrop key have object ids(suppose) of the pesticide pesticide8 and pesticide9 (meaning tomato can be treated with pesticide8 and pesticide9) and simultaneously I want a reference(_id) of tomato in the pesticide8's cropForPesticide key and pesticide9's cropForPesticide key.
I have a very vague approach in mind like firstly, I save a crop with the pesticideForCrop key being null at this point. Then I save a pesticide and while saving it, I can ask the user to select the crops which can be treated with that pesticide. I don't know how to code this. It would be nice if another feasible approach can be notified of or someone can point me in the right direction of how to code this.
When I am firing this query on MongoDB, I am getting all the places in the proximity of 500 miles to the specified co-ordinates. But I want to know the exact distance between the specified co-ordinates and the result location.
db.new_stores.find({ "geometry": { $nearSphere: { $geometry: { type: "Point", coordinates: [ -81.093699, 32.074673 ] }, $maxDistance: 500 * 3963 } } } ).pretty()
My Output looks like:
{
"_id" : ObjectId("565172058bc200b0db0f75b1"),
"type" : "Feature",
"geometry" : {
"type" : "Point",
"coordinates" : [
-80.148826,
25.941116
]
},
"properties" : {
"Name" : "Anthony's Coal Fired Pizza",
"Address" : "17901 Biscayne Blvd, Aventura, FL"
}
}
I also want to know the distance of this place from the specified co-ordinate. I created 2dsphere index on geometry.
You can use the $geoNear aggregate pipeline stage to produce a distance from the queried point:
db.new_stores.aggregate([
{ "$geoNear": {
"near": {
"type": "Point",
"coordinates": [ -81.093699, 32.074673 ]
},
"maxDistance": 500 * 1609,
"key" : "myLocation",
"spherical": true,
"distanceField": "distance",
"distanceMultiplier": 0.000621371
}}
]).pretty()
This allows you to specify "distanceField" which will produce another field in the output documents containing the distance from the queried point. You can also use "distanceMultiplier" to apply any conversion to the output distance as required ( i.e meters to miles, and noting that all GeoJSON distances are returned in meters )
There is also the geoNear command with similar options, but it of course does not return a cursor as output.
if you have more than one 2dsphere, you should specify a "key".
MongoDB provides a $geoNear aggregator for calculating the distance of documents in a collection with GeoJson coordinates.
Let us understand it with a simple example.
Consider a simple collection shops
1. Create Collection
db.createCollection('shops')
2. Insert documents in shops collections
db.shops.insert({name:"Galaxy store",address:{type:"Point",coordinates:[28.442894,77.341299]}})
db.shops.insert({name:"A2Z store",address:{type:"Point",coordinates:[28.412894,77.311299]}})
db.shops.insert({name:"Mica store",address:{type:"Point",coordinates:[28.422894,77.342299]}})
db.shops.insert({name:"Full Stack developer",address:{type:"Point",coordinates:[28.433894,77.334299]}})
3. create GeoIndex on "address" fields
db.shops.createIndex({address: "2dsphere" } )
4. Now use a $geoNear aggregator
to find out the documents with distance.
db.shops.aggregate([{$geoNear:{near:{type:"Point",coordinates:[28.411134,77.331801]},distanceField: "shopDistance",$maxDistance:150000,spherical: true}}]).pretty()
Here coordinates:[28.411134,77.331801] is the center position or quired position from where documents will be fetched.
distanceField:"shopDistance" , $geoNear Aggregator return shopDistance as fields in result.
Result:
{ "_id" : ObjectId("5ef047a4715e6ae00d0893ca"), "name" : "Full Stack developer", "address" : { "type" : "Point", "coordinates" : [ 28.433894, 77.334299 ] }, "shopDistance" : 621.2848190449148 }
{ "_id" : ObjectId("5ef0479e715e6ae00d0893c9"), "name" : "Mica store", "address" : { "type" : "Point", "coordinates" : [ 28.422894, 77.342299 ] }, "shopDistance" : 1203.3456146763526 }
{ "_id" : ObjectId("5ef0478a715e6ae00d0893c7"), "name" : "Galaxy store", "address" : { "type" : "Point", "coordinates" : [ 28.442894, 77.341299 ] }, "shopDistance" : 1310.9612119555288 }
{ "_id" : ObjectId("5ef04792715e6ae00d0893c8"), "name" : "A2Z store", "address" : { "type" : "Point", "coordinates" : [ 28.412894, 77.311299 ] }, "shopDistance" : 2282.6640175038788 }
Here shopDistance will be in meter.
maxDistance -> Optional. The maximum distance from the center point that the documents can be. MongoDB limits the results to those documents that fall within the specified distance from the center point.
Specify the distance in meters if the specified point is GeoJSON and in radians if the specified point is legacy coordinate pairs.
In the docs it says if you use legacy pairs , eg : near : [long , lat] , then specify the maxDistance in radians.
If you user GeoJSON , eg : near : { type : "Point" , coordinates : [long ,lat] },
then specify the maxDistance in meters.
Use $geoNear to get the distance between a given location and users.
db.users.aggregate([
{"$geoNear": {
"near": {
"type": "Point",
"coordinates": [ longitude, latitude]
},
"distanceField": "distance",
"distanceMultiplier": 1/1000,
"query": {/* userConditions */},
}}
]).pretty()
In Node with Mongoose I want to find an object in the collection Content. It has a list of sub-documents called users which has the properties stream, user and added. I do this to get all documents with a certain user's _id property in there users.user field.
Content.find( { 'users.user': user._id } ).sort( { 'users.added': -1 } )
This seems to work (although I'm unsure if .sort is really working here. However, I want to match two fields, like this:
Content.find( { 'users.user': user._id, 'users.stream': stream } } ).sort( { 'users.added': -1 } )
That does not seem to work. What is the right way to do this?
Here is a sample document
{
"_id" : ObjectId("551c6b37859e51fb9e9fde83"),
"url" : "https://www.youtube.com/watch?v=f9v_XN7Wxh8",
"title" : "Playing Games in 360°",
"date" : "2015-03-10T00:19:53.000Z",
"author" : "Econael",
"description" : "Blinky is a proof of concept of enhanced peripheral vision in video games, showcasing different kinds of lens projections in Quake (a mod of Fisheye Quake, using the TyrQuake engine).\n\nDemo and additional info here:\nhttps://github.com/shaunlebron/blinky\n\nThanks to #shaunlebron for making this very interesting proof of concept!\n\nSubscribe: http://www.youtube.com/subscription_center?add_user=econaelgaming\nTwitter: https://twitter.com/EconaelGaming",
"duration" : 442,
"likes" : 516,
"dislikes" : 13,
"views" : 65568,
"users" : [
{
"user" : "54f6688c55407c0300b883f2",
"added" : 1427925815190,
"_id" : ObjectId("551c6b37859e51fb9e9fde84"),
"tags" : []
}
],
"images" : [
{
"hash" : "1ab544648d7dff6e15826cda7a170ddb",
"thumb" : "...",
"orig" : "..."
}
],
"tags" : [],
"__v" : 0
}
Use $elemMatch operator to specify multiple criteria on an array of embedded documents:
Content.find({"users": {$elemMatch: {"user": user.id, "stream": stream}}});
I have several documents in my Articles collection. Every document has a location value and some extra data. The location value looks like this:
"loc" : {
"type" : "Point",
"coordinates" : [
4,
54
]
}
I can build an index by executing the following command:
db.articles.ensureIndex({loc:"2dsphere"});
And I can query documents based on their location and a $maxDistance with the following query:
db.articles.find({ loc : { $near : {$geometry : {type : "Point" , coordinates : [4, 54] }, $maxDistance : 1000 } } });
This works perfectly!
However when I change the location of my "loc" object in my document, my query always returns zero results. My document should look like this (This is a minimized version):
{
"articledata" {
"content": {
"contact": {
"loc" : {
"type" : "Point",
"coordinates" : [
4.1,
54
]
}
}
}
}
}
When I rebuild my index query:
db.articles.ensureIndex({"articledata.content.contact.loc":"2dsphere"});
and execute my query again after changing my 'loc' location in the document:
db.articles.find({ "articledata.content.contact.loc" : { $near : {$geometry : {type : "Point" , coordinates : [4, 54] }, $maxDistance : 10000 } } });
There are no results.
It's probably some stupid mistake but I really can't find the problem...
Is there anyone who can help me out?
Thanks in advance!
I would like to get Kevin pub spots near a given position. Here is the userSpots collection :
{ user:'Kevin',
spots:[
{ name:'a',
type:'pub',
location:[x,y]
},
{ name:'b',
type:'gym',
location:[v,w]
}
]
},
{ user:'Layla',
spots:[
...
]
}
Here is what I tried :
db.userSpots.findOne(
{ user: 'Kevin',
spots: {
$elemMatch: {
location:{ $nearSphere: [lng,lat], $maxDistance: d},
type: 'pub'
}
}
},
},
function(err){...}
)
I get a strange error. Mongo tells me there is no index :2d in the location field. But when I check with db.userSpots.getIndexes(), the 2d index is there. Why doesn't mongodb see the index ? Is there something I am doing wrong ?
MongoError: can't find special index: 2d for : { spots: { $elemMatch: { type:'pub',location:{ $nearSphere: [lng,lat], $maxDistance: d}}}, user:'Kevin'}
db.userSpots.getIndexes() output :
{
"0" : {
"v" : 1,
"key" : {
"_id" : 1
},
"ns" : "mydb.userSpots",
"name" : "_id_"
},
"1" : {
"v" : 1,
"key" : {
"spots.location" : "2d"
},
"ns" : "mydb.usersBoxes",
"name" : "spots.location_2d",
"background" : true,
"safe" : null
}
}
For a similar geospatial app, I transformed the location into GeoJSON:
{
"_id" : ObjectId("5252cbdd9520b8b18ee4b1c3"),
"name" : "Seattle - Downtown",
"location" : {
"type" : "Point",
"coordinates" : [
-122.33145,
47.60789
]
}
}
(the coordinates are in longitude / latitude format. Mongo's use of GeoJSON is described here.).
The index is created using:
db.userSpots.ensureIndex({"location": "2dsphere"})
In my aggregation pipeline, I find matches using:
{"$match":{"location":{"$geoWithin": {"$centerSphere":[[location.coordinates[0], location.coordinates[1]], radius/3959]}}}}
(where radius is measured in miles - the magic number is used to convert to radians).
To index documents containing array of geo data MongoDB uses multi-key index. Multi-key index unwinds document to some documents with single value instead of array before indexing. So the index consider that key field as single value field not array.
Try query it without $elemMatch operator.