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MongoDB
[
{ "_id": 1, "name": "Park", "location": { "type": "Point", "coordinates": [ -73.97, 40.77 ] } },
{ "_id": 2, "name": "Restaurant", "location": { "type": "Point", "coordinates": [ -73.98, 40.75 ] } },
{ "_id": 3, "name": "Museum", "location": { "type": "Point", "coordinates": [ -73.96, 40.78 ] } }
]
To find the locations near a specific point, you can use the $near command:
db.locations.find({
location: {
$near: {
$geometry: {
type: "Point",
coordinates: [ -73.97, 40.76 ]
},
$maxDistance: 1000 // in meters
}
}
})
This query returns the locations within 1000 meters of the specified point.
You can also use the $geoWithin command to find locations within a specific shape, such as a polygon:
db.locations.find({
location: {
$geoWithin: {
$geometry: {
type: "Polygon",
coordinates: [
[
[ -73.98, 40.76 ],
[ -73.96, 40.76 ],
[ -73.96, 40.78 ],
[ -73.98, 40.78 ],
[ -73.98, 40.76 ]
]
]
}
}
}
})
This query returns the locations that are completely within the specified polygon.
Geospatial commands and features in MongoDB enable you to perform powerful geospatial queries and operations on your data, making it easier to work with location-based information in your applications.
[
{ "_id": 1, "name": "Park", "location": { "type": "Point", "coordinates": [ -73.97, 40.77 ] } },
{ "_id": 2, "name": "Restaurant", "location": { "type": "Point", "coordinates": [ -73.98, 40.75 ] } },
{ "_id": 3, "name": "Museum", "location": { "type": "Point", "coordinates": [ -73.96, 40.78 ] } }
]
To find the locations near a specific point using the $geoNear stage:
db.locations.aggregate([
{
$geoNear: {
near: {
type: "Point",
coordinates: [ -73.97, 40.76 ]
},
distanceField: "distance",
spherical: true
}
}
])
In this example, the $geoNear stage takes the following parameters:
near: Specifies the point from which to calculate distances.distanceField: Specifies the name of the field where the calculated distances will be stored.spherical: Specifies whether to perform calculations on a sphere (true) or a flat surface (false).
The output of the aggregation will include the documents sorted by their proximity to the specified point, along with the calculated distance for each document.
It’s important to note that the $geoNear stage requires a geospatial index on the field used for the geospatial query. Before using the $geoNear stage, make sure to create a geospatial index on the relevant field using the createIndex() method.
While the $geoNear stage in the aggregation framework provides powerful geospatial capabilities, it’s worth mentioning that other geospatial operators and commands, such as $near and $geoWithin, may be more suitable for certain use cases.
[
{ "_id": 1, "name": "Park", "location": { "type": "Point", "coordinates": [ -73.97, 40.77 ] } },
{ "_id": 2, "name": "Restaurant", "location": { "type": "Point", "coordinates": [ -73.98, 40.75 ] } },
{ "_id": 3, "name": "Museum", "location": { "type": "Point", "coordinates": [ -73.96, 40.78 ] } }
]
To find locations within a specific shape, such as a polygon, you can use the $geoWithin operator in a find() query:
db.locations.find({
location: {
$geoWithin: {
$geometry: {
type: "Polygon",
coordinates: [
[
[ -73.98, 40.76 ],
[ -73.96, 40.76 ],
[ -73.96, 40.78 ],
[ -73.98, 40.78 ],
[ -73.98, 40.76 ]
]
]
}
}
}
})
In this example, the location field is specified with the $geoWithin operator, which takes the $geometry parameter. The $geometry parameter defines the shape or geometry for the query. In this case, it represents a polygon with the specified coordinates.
The query will return the documents from the “locations” collection that are completely within the specified polygon.
The $geoWithin operator can also be used within the aggregation framework, enabling you to perform more complex geospatial operations and calculations using the $match stage.
The purpose of the $geoWithin operator is to query for documents that are entirely contained within a specified area. It is useful for scenarios where you need to find locations within a specific shape, such as finding points within a polygon or finding areas within a larger region.
Note that for geospatial queries, you should have a geospatial index on the relevant field for efficient query performance. You can create a geospatial index using the createIndex() method in MongoDB.
Overall, the $geoWithin operator allows you to perform powerful geospatial queries in MongoDB to find documents that fall within a specified shape or geometry.
[
{ "_id": 1, "name": "Area A", "boundary": { "type": "Polygon", "coordinates": [[[0, 0], [0, 10], [10, 10], [10, 0], [0, 0]]] } },
{ "_id": 2, "name": "Area B", "boundary": { "type": "Polygon", "coordinates": [[[5, 5], [5, 15], [15, 15], [15, 5], [5, 5]]] } },
{ "_id": 3, "name": "Area C", "boundary": { "type": "Polygon", "coordinates": [[[12, 12], [12, 20], [20, 20], [20, 12], [12, 12]]] } }
]
To find the areas that intersect with a specific shape, such as a polygon, you can use the $geoIntersects operator in a find() query:
db.areas.find({
boundary: {
$geoIntersects: {
$geometry: {
type: "Polygon",
coordinates: [
[
[ 3, 3 ],
[ 3, 8 ],
[ 8, 8 ],
[ 8, 3 ],
[ 3, 3 ]
]
]
}
}
}
})
In this example, the boundary field is specified with the $geoIntersects operator, which takes the $geometry parameter. The $geometry parameter defines the shape or geometry for the query. In this case, it represents a polygon with the specified coordinates.
The query will return the documents from the “areas” collection that intersect with the specified polygon.
The $geoIntersects operator can also be used within the aggregation framework, enabling you to perform more complex geospatial operations and calculations using the $match stage.
The purpose of the $geoIntersects operator is to query for documents that have a spatial relationship with a specified area. It is useful for scenarios where you need to find documents that intersect or have any spatial relationship with a given shape, such as finding areas that overlap with a region or determining boundaries that touch a line.
Note that for geospatial queries, you should have a geospatial index on the relevant field for efficient query performance. You can create a geospatial index using the createIndex() method in MongoDB.
Overall, the $geoIntersects operator allows you to perform powerful geospatial queries in MongoDB to find documents that intersect with a specified shape or geometry.
[
{ "_id": 1, "name": "Park", "location": { "type": "Point", "coordinates": [ -73.97, 40.77 ] } },
{ "_id": 2, "name": "Restaurant", "location": { "type": "Point", "coordinates": [ -73.98, 40.75 ] } },
{ "_id": 3, "name": "Museum", "location": { "type": "Point", "coordinates": [ -73.96, 40.78 ] } }
]
To find locations near a specific point on the sphere using the $nearSphere operator:
db.locations.find({
location: {
$nearSphere: {
$geometry: {
type: "Point",
coordinates: [ -73.97, 40.76 ]
},
$maxDistance: 1000 // Optional: Specifies the maximum distance in meters
}
}
})
In this example, the location field is specified with the $nearSphere operator, which takes the $geometry parameter. The $geometry parameter represents the point on the sphere to which you want to find nearby locations. The coordinates property specifies the longitude and latitude of the point.
You can also include the optional $maxDistance parameter, which specifies the maximum distance from the specified point. The distance is measured in meters. This parameter is useful for limiting the search to a specific radius or proximity.
The query will return the documents from the “locations” collection that are near the specified point on the sphere, sorted by their distance.
The $nearSphere operator can also be used within the aggregation framework, allowing you to perform more complex geospatial operations and calculations using the $match stage.
The purpose of the $nearSphere operator is to query for documents based on their proximity to a specified point on the Earth’s surface, taking into account the curvature of the sphere. It is particularly useful for location-based services, mapping applications, and any scenario where you need to find nearby locations on a global scale.
Note that for geospatial queries, you should have a geospatial index on the relevant field for efficient query performance. You can create a geospatial index using the createIndex() method in MongoDB.
Overall, the $nearSphere operator allows you to perform geospatial queries in MongoDB to find documents near a specified point on the sphere, considering the Earth’s curvature.
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