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"location": { + "type": "Point", + "coordinates": [ + -111.5495777, + 33.4150485 + ] + }, + "name": "Apache Junction", + "state_abbrev": "AK" +} +{ + "_id": { + "$oid": "6572f42bd061423be246a3ee" + }, + "growth_from_2000_to_2013": "2.9%", + "population": "36888", + "rank": "999", + "state": "Wisconsin", + "location": { + "type": "Point", + "coordinates": [ + -89.03177649999999, + 42.5083482 + ] + }, + "name": "Beloit", + "state_abbrev": "WI" +} +{ + "_id": { + "$oid": "6572f42bd061423be246a3ec" + }, + "growth_from_2000_to_2013": "14.4%", + "population": "37064", + "rank": "997", + "state": "Oregon", + "location": { + "type": "Point", + "coordinates": [ + -123.0262077, + 44.9901194 + ] + }, + "name": "Keizer", + "state_abbrev": "OR" +} +{ + "_id": { + "$oid": "6572f42bd061423be246a3ef" + }, + "growth_from_2000_to_2013": "0.1%", + "population": "36877", + "rank": "1000", + "state": "Florida", + "location": { + "type": "Point", + "coordinates": [ + -85.6602058, + 30.1588129 + ] + }, + "name": "Panama City", + "state_abbrev": "FL" +} +{ + "_id": { + "$oid": "6572f42bd061423be246a3eb" + }, + "growth_from_2000_to_2013": "28.8%", + "population": "37093", + "rank": "996", + "state": "Texas", + "location": { + "type": "Point", + "coordinates": [ + -97.9908366, + 26.1595194 + ] + }, + "name": "Weslaco", + "state_abbrev": "TX" +} +{ + "_id": { + "$oid": "6572f42bd061423be246a3ed" + }, + "growth_from_2000_to_2013": "78.1%", + "population": "36956", + "rank": "998", + "state": "Utah", + "location": { + "type": "Point", + "coordinates": [ + -111.654923, + 40.114955 + ] + }, + "name": "Spanish Fork", + "state_abbrev": "UT" +} diff --git a/2A/BDD/tp/s2/noSQL/3_tp/responses.sql b/2A/BDD/tp/s2/noSQL/3_tp/responses.sql new file mode 100644 index 0000000..3a51983 --- /dev/null +++ b/2A/BDD/tp/s2/noSQL/3_tp/responses.sql @@ -0,0 +1,120 @@ + +-- Q1). Lister les noms, villes et nombres d’étoiles des adresses répertoriées en Californie (CA) ayant +-- obtenu 5 étoiles, triées par nom par ordre alphabétique. + +db.yelp.find({state: 'CA', stars: 5}, ["name", "city", "stars"]).sort({"name": 1}) + +-- Q2). Faire la même chose sous forme de pipeline d’agrégation. + +db.yelp.aggregate({ $match : {"state": 'CA','stars': 5}}, {$project : {"name": 1,"city": 1,"stars": 1}},{ $sort : {"name": 1}}) + +-- Q3). Faire la même chose via l’interface graphique de Compass en utilisant l’onglet . +-- En rajoutant l’option .explain("executionStats") entre le nom de la collection et le .aggregate, +-- il est possible d’obtenir des informations sur l’exécution de votre pipeline d’agrégation comme par +-- exemple : +-- ... +-- executionStats: { +-- executionSuccess: true, /*Est-ce que l’exécution s’est bien passée ?*/ +-- nReturned: 2416, /*Le nombre de documents retournés*/ +-- executionTimeMillis: 250, /*Le temps d’exécution en ms*/ +-- ... + + + +-- Q4). Utiliser cette option pour obtenir le temps d’exécution du pipeline d’agrégation réalisé pour +-- la question 2. + +db.yelp.explain("executionStats").aggregate({ $match : {"state": 'CA','stars': 5}}, {$project : {"name": 1,"city": 1,"stars": 1}},{ $sort : {"name": 1}}) + + +-- Q5). Inverser l’ordre de vos opérateurs dans le pipeline et comparer le temps d’exécution de cette +-- nouvelle version avec l’ancienne. Pourquoi ce résultat ? + +db.yelp.explain("executionStats").aggregate({$project : {"name": 1,"city": 1,"stars": 1}}, { $match : {"state": 'CA','stars': 5}},{ $sort : {"name": 1}}) +db.yelp.explain("executionStats").aggregate({$project : {"name": 1,"city": 1,"stars": 1}}, { $match : {"state": 'CA','stars': 5}},{ $sort : {"name": 1}}) +db.yelp.explain("executionStats").aggregate({$project : {"name": 1,"city": 1,"stars": 1}}, { $sort : {"name": 1}}, { $match : {"state": 'CA','stars': 5}}) +db.yelp.explain("executionStats").aggregate({ $sort : {"name": 1}}, {$project : {"name": 1,"city": 1,"stars": 1}}, { $match : {"state": 'CA','stars': 5}}) +db.yelp.explain("executionStats").aggregate({ $sort : {"name": 1}}, { $match : {"state": 'CA','stars': 5}}, {$project : {"name": 1,"city": 1,"stars": 1}}) + + + +-- Q6). Utiliser un pipeline pour lister les états représentés dans cette base de données. + +db.yelp.aggregate({$project : {state : 1}}) + +-- Q7). Utiliser un pipeline pour lister les villes du Texas (TX) représentées dans cette base de données. + +db.yelp.aggregate({$match : {"state" : "TX"}},{$project : {city: 1, _id : 0}}) + +-- Q8). Compter le nombre d’adresses connues à Santa Barbara. + +db.yelp.aggregate({$match : {"city" : "Santa Barbara"}},{$count : "name"}) +db.yelp.aggregate({$match : {"city" : "Santa Barbara"}},{$count : "*"}) + +-- Q9). Combien y a t’il d’adresses référencées qui sont définitivement fermées ? + +db.yelp.aggregate({$match : {"is_open" : 0}},{$count : "*"}) + +-- Q10). Compter le nombre d’adresses référencées pour chaque état, les états en ayant le plus en +-- premier. + +db.yelp.aggregate({$group : {_id : "$state", "nombre" : {$count : {}}}}, {$sort : {"nombre" : -1}}) + +-- Q11). Compter le nombre total de commentaires laissés pour des restaurants dans chaque ville de +-- Californie (CA). + +db.yelp.aggregate({$match : {state : "CA", "categories": ["Restaurants"]}}, {$group : {_id : "$city", "nombre" : { $count : {} } } }) + + +-- Q12). Quel est le nombre maximum de commentaires laissés pour des chefs à domicile (Personal +-- Chefs) pour chaque état ? + + + +-- Q13). Quel est le nombre moyen d’étoiles reçues par les bars de chaque ville du Missouri (MO) ? + + + +-- Q14). Récupérer le fichier cities.json sur Moodle. Ce fichier contient des informations sur les +-- 1000 plus grandes villes américaines. + + + +-- Q15). Importer les documents du fichier cities.json dans une nouvelle collection nommée cities. +-- Vous pouvez utiliser la commande mongoimport ou importer via Compass. + + + +-- Q16). Les champs "rank" et "population" sont sous forme de chaîne de caractères. Pour faciliter +-- l’analyse ultérieure de ses données nous allons les transformer en entier. Faire un pipeline d’agrégation +-- faisant la conversion en entier pour ces deux champs et enregistrant le résultat dans une nouvelle +-- collection cities2. + + + +-- Q17). Vérifier que la collection cities2 a bien été créée et afficher quelques documents pour vérifier +-- que la conversion en entier a bien été réalisée. + + + +-- Q18). Quelle est la population moyenne de ces villes ? + + + +-- Q19). Faire une jointure entre la collection yelp et la collection cities2. Le champ servant à stocker +-- le résultat devra s’appeler "city_details". + + + +-- Q20). Plusieurs villes américaines situées dans des états différents portent le même nom. Par +-- exemple, il existe une ville se nommant Madison dans l’Alabama, dans le Tennessee et dans le Wis- +-- consin. +-- Modifier votre pipeline d’agrégation pour que le champ "city_details" ne soit plus un tableau mais +-- un objet unique, et que les informations contenues dans "city_details" correspondent bien à la ville +-- en question. Vous en profiterez pour éliminer les adresses pour lesquelles nous n’avons pas d’information +-- sur la ville. + + + +-- Q21). Lister les glaciers (Gelato) pour lesquels au moins un habitant sur 1000 de sa ville a laissé un +-- commentai \ No newline at end of file diff --git a/2A/BDD/tp/s2/noSQL/3_tp/tp05_mongo.pdf b/2A/BDD/tp/s2/noSQL/3_tp/tp05_mongo.pdf new file mode 100644 index 0000000..010e149 Binary files /dev/null and b/2A/BDD/tp/s2/noSQL/3_tp/tp05_mongo.pdf differ