Consider a query of:
db.stuff.find({ Location:
{ $geoWithin:
{ $centerSphere: [ [ -73.93414657, 40.82302903 ], 5 / 3963.2 ] } } })
Would it be reasonable to expect a performance boost if the coordinates were less precise? If so, by how much?
db.stuff.find({ Location:
{ $geoWithin:
{ $centerSphere: [ [ -73.93414, 40.82302 ], 5 / 3963.2 ] } } })
Bonus points if you have links to documentation on performance tuning mongo geospatial queries.
Unfortunately no.
And you can test this yourself by looking at $executionStats.
Be aware that you should change the coordinated on every call to avoid metric distortion due to caching.
More info about mongodb's spatial B-tree indexing here.
Related
I want to show nearby places on the map for a given user.
I can do so either by query MongoDB like this:
db.places.find( {
loc: { $geoWithin: { $centerSphere: [ [ -88, 30 ], 10/3963.2 ] } }
} )
and either by query a Reids geospatial set like this:
georadius key longitude latitude 100 m
Any pros and cons?
So I am using Mongodb Compass and trying to test out Geolocation while MongoDB website is very good at terminal coding I need to be able to do the same thing as below in mongoDB atlas - just to make sure the code works.
I plan on using Mongoose as the driver in my react app to fetch the data, however I just thought before I go to far I should see if this is really possible (now I understand Mongodb Compass is different to Mongoose and the query maybe a little different.)
db.campaign.find({ location:
{ $geoWithin:
{ $centerSphere: [ [ 115.880321, 31.9256201], 5 / 3963.2 ] } } })
The collection looks like this
{"_id":{"$oid":"55cba2476c522cafdb053add"},"location":{"coordinates":[115.880321,-31.9256201],"type":"Point"},"name":"DRN1"}
It currently throws an error an does not let me even attempt to search this.
Query
{ location: { $nearSphere: { $geometry: { type: "Point", coordinates: [ 115.880321, -31.9256201 ] }, $maxDistance: 5 * 1609.34 } } }
In my application I would like to query items that are close by (e.g. within 5km) to a coordinate and I tried to use $near to achieve that. With a quick look I thought it worked but after I tested it further it seems the query is somewhat inaccurate. Here is my setup:
I selected 2 coordinates that are a bit less than 5km apart from each other:
61.4644750214197, 23.8426943813556
61.497133399999996, 23.778528100000003
(At least according to tools like this, this or this the distance between those coordinates should be about ~4,99km)
I added one of the coordinates into empty "items" collection:
db.items.insert({
"geo" : {
"type" : "Point",
"coordinates" : [
61.4644750214197,
23.8426943813556
]
}
});
I added "2dsphere" index to the collection make geospatial queries possible:
db.items.createIndex( { geo : "2dsphere" } )
Finally, I used the other coordinate with $near query:
db.items.find({geo: {
$near: {
$geometry: {
type: "Point" ,
coordinates: [ 61.497133399999996, 23.778528100000003 ]
},
$maxDistance: 5000 // according to docs with '2dsphere' index and GeoJSON this is is meters
}
}}).count()
I expected the result to be 1 but instead it is 0. Even if I set $maxDistance to 7000 the result is still 0, but if I set it to 8000 the result will be 1.
Am I doing something wrong or are MongoDB geospatial queries (or just $near query?) that inaccurate? If so, is there a better way to get accurate results for this kind of query? This is my first time dealing with geospatial queries in MongoDB so there is probably a trivial explanation for my problem.
EDIT:
Basically I was dreaming of a functionality to show all items in map within X kilometres from users current location and X could be determined by user. It would be awkward if an item within 5km would not be visible even when the user wants to filter items within 7km.
I have tried most of the options for doing this query, like $centerSphere, $nearSphere and geoNear with similar results. They all seem to claim that the distance between my earlier mentioned coordinates is somewhere between 7-8km. I'm starting to think either 1. I'm missing some key peace of information about how distances work in general or 2. it simply is not possible to solve my problem with mongodb. Below are my queries for the other options:
$centerSphere (0 results with 5, 6 and 7km but 1 result with 8km):
db.items.find( { geo: {
$geoWithin: { $centerSphere: [ [ 61.497133399999996, 23.778528100000003 ], 5/6378.1 ]
}
}}).count()
geoNear (0 results with maxDistance 5000, 6000 and 7000 but 1 result with 8000):
db.runCommand(
{
geoNear: "items",
near: { type: "Point", coordinates: [ 61.497133399999996, 23.778528100000003 ] },
spherical: true,
maxDistance: 5000
}
)
I understand I am late to the party, but for all those who are facing similar issue
The problem here is that when you store that data into "coordinates", it must be in the [longitude, latitude] order because this is how mongodb works. https://docs.mongodb.com/manual/geospatial-queries/#spherical I just ran your example with reversed order of coordinates and it worked as expected.
db.items.insert({
"geo" : {
"type" : "Point",
"coordinates" : [
23.8426943813556,
61.4644750214197
]
}
});
And then i ran
db.items.find({geo: {
$near: {
$geometry: {
type: "Point" ,
coordinates: [ 23.778528100000003 , 61.497133399999996]
},
$maxDistance: 5000
}
}}).count()
The count here is 1:
Hope it helps
I have two collections in my database: Post and Gallery. A Post has a single GeoJSON Point location, and a gallery is a collection of posts. The gallery's location is a GeoJSON Polygon bounding the gallery's posts (using quickhull algorithm). I now need to query for all galleries within x miles of a certain point, however I'm not getting any results even if I query from right next to my polygon.
I would like the behavior to be exactly the same as the following:
db.posts.find({
'location': {
$geoWithin: {
$centerSphere: [[-70, 30], 1000/3959]
}
}
});
Here, all posts within a the radius are returned. However, when I run the same type of function in this way, I am returned nothing, which is not correct:
db.galleries.find({
'location': {
$geoWithin: {
$centerSphere: [[-70, 30], 1000/3959]
}
}
});
One of my galleries has the following location (is 2dsphere index with 2dsphereIndexVersion = 2):
"location": {
"type": "Polygon",
"coordinates": [
[
[
-73.986882,
40.682829
],
[
-73.971089,
40.6672045
],
[
-73.955296,
40.65158
],
[
-73.986882,
40.682829
]
]
]
}
How do I query for location polygons that at least intersect with my radius?
I had the same problem and tried the exact same query that you initially tried. I'm not sure why it didn't work, but I was eventually able to get $near to do the job. Keep in mind that $near uses meters when calculating $maxDistance, so I had to convert my 10 mile desired distance to meters by multiplying by 1609.34. Here's the query that I ended up using:
db.maTowns.find(
{
'geometry': {
$near: {
$geometry: {
'type': "Point",
'coordinates': [ -71, 42 ]
},
$maxDistance: 10 * 1609.34
}
}
}
)
Select all polygons within the radius of a point
With the recent release of MongoDB version 3.6.0-rc0, you can now query GeoJSON LineStrings and Polygons with $geoWithin geospatial operator $centerSphere.
See also SERVER-27968 for more information about the change. Note that this change is pending to be backported.
Also maybe related for $geoIntersects and $centerSphere is ticket SERVER-30390
I am writing a nodejs app involving geocodes ( ~50million places) stored in mongodb (using mongo native driver). For development I am testing with sample data (airports of the world ~45k locations http://www.ourairports.com/data/airports.csv ). I am following GeoJSON format and building 2dsphere index on location field(named "geometry"). Then I am doing a $geowithin query to find locations.
Evrything works as expected. The issue is that when I am querying for a polygon containing US, the query is taking around 4-6sec for returning 22845 locations.
db. airports.ensureIndex({ geometry: '2dsphere' })
db.airports.find({ geometry: { '$geoWithin': { '$geometry': { type: 'Polygon', coordinates: [ [ [ -127.32917843921399, 75.11297289119061 ], [ -71.32126356078601, 75.11297289119061 ], [ -71.32126356078601, 12.305525108809391 ], [ -127.32917843921399, 12.305525108809391 ], [ -127.32917843921399, 75.11297289119061 ] ] ] } } } })
I am sure that this cant be correct. This way I cant imagine response times with 50million points.
Would appreciate if someone can point me in direction to improve the performance of this.