Geospatial Indexing with the 'location' collection

		How to create a GeoJSON with Geospatial Indexing

1. Create a JSON file called collection.json with a specific format for collecting the coordinates for each location under the GeoJSON Specification Format.

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2. Import the JSON in the database you want with collection name (Here database = dbms_team_project and collection = location).
Format of the command:-mongoimport --db <database name> --collection <colection name> --type json <JSON File name>

mongoimport --db dbms_team_project --collection location --type json location.json

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3. Start the mongo shell after running the mongod server (through the 'mongod' command) in another command prompt. Then switch from the default database to the 'project' database.

C:\Users\Aditya Gogoi>mongo
MongoDB shell version: 3.2.10
connecting to: test
> use dbms_team_project
switched to db dbms_team_project

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4. Check out a few of the documents in the collection.

Format of the command:-db.<collection_name>.find().pretty()

> db.location.find().pretty()
{
        "_id" : "GA01",
        "name" : "Georgia Aquarium",
        "address" : "225 Baker St NW, Atlanta, GA 30313",
        "state" : "Georgia",
        "coordinates" : {
                "type" : "Point",
                "coordinates" : [
                        -84.394891,
                        33.763424
                ]
        }
}
{
        "_id" : "GA04",
        "name" : "Centennial Olympic Park",
        "address" : "265 Park Avenue West, Atlanta, GA 30313",
        "state" : "Georgia",
        "coordinates" : {
                "type" : "Point",
                "coordinates" : [
                        -84.39451,
                        33.761837
                ]
        }
}
{
        "_id" : "GA06",
        "name" : "Forsyth Park",
        "address" : "Drayton St, Savannah, GA 31401",
        "state" : "Georgia",
        "coordinates" : {
                "type" : "Point",
                "coordinates" : [
                        -81.095388,
                        32.066572
                ]
        }
}

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You will notice that the 'coordinates' field has a Document embedded as its value. This is a GeoJSON document. But to make it effective, we need to include the Geospatial '2dsphere' index to this collection of GeoJSON documents. 

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4. Apply the geospatial '2dsphere' index in the following format:-
Format of the command:-db.<collection name>.ensureIndex({'coordinates':'2dsphere'})

>db.location.ensureIndex({'coordinates':'2dsphere'})
connecting to: localhost:27017/dbms_team_project
{
	"createdCollectionAutomatically" : false,
	"numIndexesBefore" : 2,
	"numIndexesAfter" : 2,
	"note" : "all indexes already exist",
	"ok" : 1
}
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5. Check that there are 2 indexes (a default index and a geospatial index).
Format of the command:-db.<collection name>.getIndexes()

> db.location.getIndexes()
[
        {
                "v" : 1,
                "key" : {
                        "_id" : 1
                },
                "name" : "_id_",
                "ns" : "dbms_team_project.location"
        },
        {
                "v" : 1,
                "key" : {
                        "coordinates" : "2dsphere"
                },
                "name" : "coordinates_2dsphere",
                "ns" : "dbms_team_project.location",
                "2dsphereIndexVersion" : 3
        }
]
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5. We can use the index to see how many locations are close to a given coordinate within a specific maximum distance (Proximity Search Operation).

Format of the command:-db.<collection_name>.find({<field_with_GeoJSON_doc>:{$near:{$geometry:{type:"Point",coordinates:[<Longitude>,<Latitude>]}, $maxdistance:<Max Distance in meters>}}}).pretty()

> db.location.find({coordinates:{$near:{$geometry:{type:"Point",coordinates:[-84,33]}, $maxDistance:80000}}}).pretty()
{
        "_id" : "GA24",
        "name" : "Museum of Aviation",
        "address" : "1942 Heritage Blvd, Robins AFB, GA 31098",
        "state" : "Georgia",
        "coordinates" : {
                "type" : "Point",
                "coordinates" : [
                        -83.587858,
                        32.59214
                ]
        }
}

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6. Increasing the Maximum distance to include more GeoJSON documents form nearest to farthest with reference to the entered coordinate.

> db.location.find({coordinates:{$near:{$geometry:{type:"Point",coordinates:[-84,33]}, $maxDistance:85000}}}).pretty()
{
        "_id" : "GA24",
        "name" : "Museum of Aviation",
        "address" : "1942 Heritage Blvd, Robins AFB, GA 31098",
        "state" : "Georgia",
        "coordinates" : {
                "type" : "Point",
                "coordinates" : [
                        -83.587858,
                        32.59214
                ]
        }
}
{
        "_id" : "GA20",
        "name" : "Callaway Gardens",
        "address" : "Columbus, GA 30304",
        "state" : "Georgia",
        "coordinates" : {
                "type" : "Point",
                "coordinates" : [
                        -84.848313,
                        32.854943
                ]
        }
}