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MongoDB how to use geographic information index, many novices are not very clear about this, in order to help you solve this problem, the following editor will explain for you in detail, people with this need can come to learn, I hope you can gain something.

Geographic information indexes are divided into two categories: 2D plane index and 2DSphere spherical index.

Basically, the information can be saved in the 2D index, that is, the coordinates of longitude and latitude.

Example: define a collection of stores

Db.shop.insert ({loc: [10jue 10]})

Db.shop.insert ({loc: [20jue 10]})

Db.shop.insert ({loc: [10pm 20]})

Db.shop.insert ({loc: [200.20]})

Db.shop.insert ({loc: [100100]})

Db.shop.insert ({loc: [80pr 30]})

Db.shop.insert ({loc: [30pm 50]})

Example: s > db.shop.createIndex ({"loc": "2d"})

{

"createdCollectionAutomatically": false

"numIndexesBefore": 1

"numIndexesAfter": 2

"ok": 1

} hop collection definition 2D index

At this point, the shop collection can query the coordinate location. There are two ways to query:

● "$near" query: query the coordinate point closest to a point.

● "$geoWithin" query: queries for points within a shape.

Example: suppose that the current coordinates are: [30 ~ 30]

> db.shop.find ({"loc": {"$near": [300.30]}})

{"_ id": ObjectId ("599396cd0184ff511bf02bc6"), "loc": [20,20]}

{"_ id": ObjectId ("599396ce0184ff511bf02bc9"), "loc": [30,50]}

{"_ id": ObjectId ("599396cd0184ff511bf02bc4"), "loc": [20,10]}

{"_ id": ObjectId ("599396cd0184ff511bf02bc5"), "loc": [10,20]}

{"_ id": ObjectId ("599396cd0184ff511bf02bc3"), "loc": [10,10]}

{"_ id": ObjectId ("599396cd0184ff511bf02bc8"), "loc": [80,30]}

{"_ id": ObjectId ("599396cd0184ff511bf02bc7"), "loc": [100,100]}

If the above query is executed, the information of the first 100 points in the data set will actually be returned, and the distance range can be set.

Example: set the distance range of a query

> db.shop.find ({"loc": {"$near": [30 near 30], "$maxDistance": 20}})

{"_ id": ObjectId ("599396cd0184ff511bf02bc6"), "loc": [20,20]}

{"_ id": ObjectId ("599396ce0184ff511bf02bc9"), "loc": [30,50]}

However, it should be noted that although the maximum distance is supported in the 2D index, the minimum distance is not supported.

But you can also set the scope of a query, using the "$geoWithin" query, which can be set as follows:

Rectangular range ($box): {"$box": [[x1jiny1], [x2jiny2]]}

Circular range ($center): {"$center": [[x1jiny1], r]}

Polygon ($polygon): {"$polygon": [[x1rect y1], [x2rect y2], [x3jue y3],...]}

Example: query rectangle range

> db.shop.find ({"loc": {"$geoWithin": {$box: [[30Jing 30], [80Jing 80]})

{"_ id": ObjectId ("599396ce0184ff511bf02bc9"), "loc": [30,50]}

{"_ id": ObjectId ("599396cd0184ff511bf02bc8"), "loc": [80,30]}

Example: query circle range

> db.shop.find ({"loc": {"$geoWithin": {$center: [[30 geoWithin 30], 20]})

{"_ id": ObjectId ("599396cd0184ff511bf02bc6"), "loc": [20,20]}

{"_ id": ObjectId ("599396ce0184ff511bf02bc9"), "loc": [30,50]}

In addition to some supported operation functions in the MongoDB database, there is another important command: runCommand (), which executes specific MongoDB commands.

Example: using runCommand () to realize information query

> db.runCommand ({"geoNear": "shop", "near": [30 dint 30], "maxDistance": 20 minus 2})

{

"results": [

{

"dis": 14.142135623730951

"obj": {

"_ id": ObjectId ("599396cd0184ff511bf02bc6")

"loc": [

twenty,

twenty

]

}

}

{

"dis": 20

"obj": {

"_ id": ObjectId ("599396ce0184ff511bf02bc9")

"loc": [

thirty,

fifty

]

}

}

]

"stats": {

"nscanned": 4

"objectsLoaded": 2

"avgDistance": 17.071067811865476

"maxDistance": 20

"time": 0

}

"ok": 1

}

Such commands can be said to be the most basic commands in MongoDB.

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