C:\Elod\2017-2018\IF\3IF\DW\TD2_MongoDB

mongoimport --db mongoLab --collection velov_geo --file "C:\Elod\2024-2025\centrale\BsC_EM_EC\MongoDBLab\velov_geo.json"

./mongoimport --db mongoLab --collection velov_geo --file "/Users/elodegyed/2024-2025/INSA/IF/3IF/DW/MongoDB/velov_geo.json"




1. db.velov_geo.find({"properties.commune":"VILLEURBANNE"});
  
  ou
  
  db.velov_geo.find({"properties.commune":{$eq:"VILLEURBANNE"}});

// avec projection
   db.velov_geo.find({"properties.commune":"VILLEURBANNE"},
                     {"properties.commune":1, "properties.name":1, _id:0});

2. 
db.velov_geo.find({"properties.commune":{$ne:"VILLEURBANNE"}});
db.velov_geo.find({"properties.commune":{$ne:"VILLEURBANNE"}},
                     {"properties.commune":1, "properties.name":1});

db.velov_geo.find({"properties.commune":{$ne:"VILLEURBANNE"}}).count();

3.
Liste des stations qui n’ont pas de seconde adresse (adress2 vide)

db.velov_geo.find({"properties.address2":""},
                  {"properties.commune":1, "properties.name":1,"properties.address2":1});

4.
Nombre de stations dont la seconde adresse a une valeur
db.velov_geo.find({"properties.address2":{$ne:""}}).count();


5.
db.velov_geo.find({"properties.available_bikes":{$gt:2}});

db.velov_geo.find({"properties.available_bikes":{$gt:2}},
                  {"properties.available_bikes":1, "properties.name":1, _id:0});

6.
db.velov_geo.distinct("properties.commune");

db.velov_geo.aggregate(
[
{$group:{_id:"$properties.commune"}}
]
);

7.
db.velov_geo.aggregate(
[
{$group:{_id:"$properties.commune"}},
{$sort:{"_id":-1}}
]
);


db.velov_geo.distinct("properties.commune").sort();
db.velov_geo.distinct("properties.commune").sort().reverse();

8.
db.velov_geo.find({"properties.commune":"Lyon 9 ème"},
                   {"properties.available_bikes":1})
 		    .sort({"properties.available_bikes":1});


10.
db.velov_geo.aggregate(
[
{$group:{_id:"$properties.commune", nb_stations : {$sum:1}}}
]
);

11.
db.velov_geo.aggregate(
[
{$group:{_id:"$properties.commune", nb_stations : {$sum:1}}},
{$sort:{"_id":1}}
]
);

12.
db.velov_geo.aggregate(
[
{$group:{_id:"$properties.commune", total : {$sum:1}}},
{$sort:{"total":-1}}
]
);

13.
db.velov_geo.aggregate(
[
{$match:{"properties.commune":"VILLEURBANNE"}},
{$group:{_id:"$properties.available_bikes", 
  	     nb_stations : {$sum:1}}},
{$sort:{"nb_stations":-1}}
]
);

14.
db.velov_geo.aggregate(
[
{$match:{"properties.commune":"VILLEURBANNE"}},
{$group:{_id:"$properties.available_bikes", 
         noms : {$push:"$properties.name"}}}
]
);



15.	Calculer le nombre moyen de vélos disponibles par commune

db.velov_geo.aggregate(
	[
		{
			$group: {
			_id:{commune:"$properties.commune"}, moyenne : { $avg : "$properties.available_bikes"}
			}
		},
	]
);

19.	Chercher les stations Vélo’V qui sont à moins de 500m du point : $geometry: { type: "Point",  coordinates: [ 4.863132722360224, 45.77022676914935 ] }

db.velov_geo.find({
"geometry.coordinates":{
$near: {
            $geometry: { type: "Point",  coordinates: [ 4.863132722360224, 45.77022676914935 ] },
            $minDistance: 0,
            $maxDistance: 500
          }}
});





20.	Listez les 5 stations les plus proches des coordonnées type : "Point",  coordinates: [ 4.863132722360224, 45.77022676914935 ] } (utilisez : geoNear)
db.runCommand(
   {
     geoNear: "velov_geo",
     near: { type: "Point",  coordinates: [ 4.863132722360224, 45.77022676914935 ]},
     spherical: true,
     num: 5
 
   }
)

Ou
db.velov_geo.aggregate(
	[
		{
			$geoNear: {
			        near: { type: "Point",  coordinates: [ 4.863132722360224, 45.77022676914935 ]},
			        distanceField: "geometry",
			        num: 5,
			        spherical: true
			}
		},

	]
);

Index text

18.	Cherchez les stations dont le pole répond à la requête  « quartiers »

Find velov stations with the adress containing: "Château".

First solution with a regexp:

db.velov_geo.find({
  "properties.address": { "$regex": "Europe", "$options": "i" }
});

or a shorter form : 
db.velov_geo.find({ "properties.address": /Chateau/i });

This 

db.velov_geo.find( { $text: { $search: "quartiers" } } )


19.
{
    "type" : "Feature",
    "properties" : {
        "number" : 10013,
        "name" : "Ecole Centrale",
        "address" : "Av. Guy de Collongue",
        "address2" : "",
        "commune" : "Ecully",
        "nmarrond" : 14,
        "bonus" : "Oui",
        "pole" : "Campus Ecully",  
        "lat" : 45.783226793334435,
        "lng" : 4.766414069315745,
        "bike_stands" : 20,
        "status" : "OPEN",
        "available_bike_stands" : 7,
        "available_bikes" : 13,
        "availabilitycode" : 1,
        "availability" : "Vert",
        "banking" : 0,
        "gid" : 1065,
        "last_update" : "2022/01/25 10:49:23",
        "last_update_fme" : "2022/01/25 10:49:23"
    },
    "geometry" : {
        "type" : "Point",
        "coordinates" : [ 
            4.766414069315745, 
            45.783226793334435
        ]
    }
}

17.