{
"address": {
"building": "1007",
"coord": [ -73.856077, 40.848447 ],
"street": "Morris Park Ave",
"zipcode": "10462"
},
"borough": "Bronx",
"cuisine": "Bakery",
"grades": [
{ "date": { "$date": 1393804800000 }, "grade": "A", "score": 2 },
{ "date": { "$date": 1378857600000 }, "grade": "A", "score": 6 },
{ "date": { "$date": 1358985600000 }, "grade": "A", "score": 10 },
{ "date": { "$date": 1322006400000 }, "grade": "A", "score": 9 },
{ "date": { "$date": 1299715200000 }, "grade": "B", "score": 14 }
],
"name": "Morris Park Bake Shop",
"restaurant_id": "30075445"
}Use Robot 3T to create and import the collection restaurants into the database ny or use the mongo shell.
With mongo Shell:
Create and import your collection into a new database called ny:
$ mongoimport --db ny --collection restaurants --file restaurants.json- 1 Write a MongoDB query to display all the documents in the collection restaurants
db.restaurants.find()
- 2 Write a MongoDB query to display only one document
db.restaurants.findOne()
- 3 Write a MongoDB query to display the fields restaurant_id, name, borough and cuisine for all the documents in the collection restaurant
db.restaurants.find({}, {restaurant_id: 1, name: 1, borough: 1, cuisine: 1})
- 4 Write a MongoDB query to display the fields restaurant_id, name, borough and cuisine, but exclude the field _id for all the documents in the collection restaurant
db.restaurants.find({}, {restaurant_id: 1, name: 1, borough: 1, cuisine: 1, _id: 0})
- 5 Write a MongoDB query to display the fields restaurant_id, name, borough and zip code, but exclude the field _id for all the documents in the collection restaurant
db.restaurants.find({}, {restaurant_id: 1, name: 1, borough: 1, cuisine: 1, "address.zipcode": 1, _id: 0})
- 6 Write a MongoDB query to display all the restaurant which is in the borough Bronx
db.restaurants.find({borough: "Bronx"})
- 7 Write a MongoDB query to display the first 5 restaurant which is in the borough Bronx
db.restaurants.find({borough: "Bronx"}).limit(5)
- 8 Write a MongoDB query to display the next 5 restaurants after skipping first 5 which are in the borough Bronx
db.restaurants.find({borough: "Bronx"}).skip(5).limit(5)
- 9 Write a MongoDB query to find the restaurants who achieved a score more than 90
db.restaurants.find({"grades.score": {$gt: 90}})
- 10 Write a MongoDB query to find the restaurants that achieved a score, more than 80 but less than 100
db.restaurants.find({"grades.score": {$gt: 80, $lt: 100}})
- 11 Write a MongoDB query to find the restaurants which locate in latitude value less than -95.754168
db.restaurants.find({"address.coord": {$lt: -95.754168}})
- 12 Write a MongoDB query to find the restaurants that do not prepare any cuisine of 'American' and their grade score more than 70 and latitude less than -65.754168
db.restaurants.find({$and: [{cuisine: {$ne: "American"}}, {"grades.score": {$gt: 70}}, {"address.coord": {$lt: -65.754168}}]})
- 13 Write a MongoDB query to find the restaurants which do not prepare any cuisine of 'American' and achieved a score more than 70 and located in the longitude less than -65.754168
Note: Do this query without using $and operator
db.restaurants.find({$query: {cuisine: {$ne: "American"}, "grades.score": {$gt: 70}, "address.coord": {$lt: -65.754168}}})
- 14 Write a MongoDB query to find the restaurants which do not prepare any cuisine of 'American ' and achieved a grade point 'A' not belongs to the borough Brooklyn. The document must be displayed according to the cuisine in descending order
db.restaurants.find({$query: {cuisine: {$ne: "American"}, "grades.grade": "A", borough: "Brooklyn"}, $orderby: {cuisine: -1}})
- 15 Write a MongoDB query to find the restaurant Id, name, borough and cuisine for those restaurants which contain 'Wil' as first three letters for its name
db.restaurants.find({name: "/^Wil/"}, {restaurant_id: 1, name: 1, borough: 1, cuisine: 1})
- 16 Write a MongoDB query to find the restaurant Id, name, borough and cuisine for those restaurants which contain 'ces' as last three letters for its name
db.restaurants.find({name: "/ces$/"}, {restaurant_id: 1, name: 1, borough: 1, cuisine: 1})
- 17 Write a MongoDB query to find the restaurant Id, name, borough and cuisine for those restaurants which contain 'Reg' as three letters somewhere in its name
db.restaurants.find({name: "/.*Reg.*/"}, {restaurant_id: 1, name: 1, borough: 1, cuisine: 1})
- 18 Write a MongoDB query to find the restaurants which belong to the borough Bronx and prepared either American or Chinese dish
db.restaurants.find({borough: "Bronx", $or: [{cuisine: "American "}, {cuisine: "Chinese"}]});
- 19 Write a MongoDB query to find the restaurant Id, name, borough and cuisine for those restaurants which belong to the borough Staten Island or Queens or Bronxor Brooklyn
db.restaurants.find({borough: {$in: ["Staten Island", "Queens", "Brooklyn"]}}, {restaurant_id: 1, name: 1, borough: 1, cuisine: 1});
- 20 Write a MongoDB query to find the restaurant Id, name, borough and cuisine for those restaurants which are not belonging to the borough Staten Island or Queens or Bronxor Brooklyn
db.restaurants.find({borough: {$nin: ["Staten Island", "Queens", "Brooklyn"]}}, {restaurant_id: 1, name: 1, borough: 1, cuisine: 1});
- 21 Write a MongoDB query to find the restaurant Id, name, borough and cuisine for those restaurants which achieved a score which is not more than 10
db.restaurants.find({"grades.score": {$not: {$gt: 10}}}, {restaurant_id: 1, name: 1, borough: 1, cuisine: 1});
- 22 Write a MongoDB query to find the restaurant Id, name, borough and cuisine for those restaurants which prepared dish except 'American' and 'Chinees' or restaurant's name begins with letter 'Wil'
db.restaurants.find({$or: [{name: "Wil"}, {$and: [{cuisine: {$ne: "American"}}, {cuisine: {$ne: "Chinees"}}]}]}, {restaurant_id: 1, name: 1, borough: 1, cuisine: 1});
- 23 Write a MongoDB query to find the restaurant Id, name, and grades for those restaurants which achieved a grade of "A" and scored 11 on an ISODate "2014-08-11T00:00:00Z" among many of survey dates
db.restaurants.find({"grades.date": "2014-08-11T00:00:00Z", "grades.grade": "A", "grades.score": 11}, {restaurant_id: 1, name: 1, grades: 1});
- 24 Write a MongoDB query to find the restaurant Id, name and grades for those restaurants where the 2nd element of grades array contains a grade of "A" and score 9 on an ISODate "2014-08-11T00:00:00Z"
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- 25 Write a MongoDB query to find the restaurant Id, name, address and geographical location for those restaurants where 2nd element of coord array contains a value which is more than 42 and upto 52
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- 26 Write a MongoDB query to arrange the name of the restaurants in ascending order along with all the columns
db.restaurants.find().sort({name: 1});
- 27 Write a MongoDB query to arrange the name of the restaurants in descending along with all the columns
db.restaurants.find().sort({name: -1});
- 28 Write a MongoDB query to arranged the name of the cuisine in ascending order and for that same cuisine borough should be in descending order
db.restaurants.find().sort({cuisine: 1, borough: -1});
- 29 Write a MongoDB query to know whether all the addresses contains the street or not
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- 30 Write a MongoDB query which will select all documents in the restaurants collection where the coord field value is Double
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- 31 Write a MongoDB query which will select the restaurant Id, name and grades for those restaurants which returns 0 as a remainder after dividing the score by 7
db.restaurants.find({"grades.score": {$mod : [7,0]}}, {restaurant_id: 1, name: 1, grades: 1});
- 32 Write a MongoDB query to find the restaurant name, borough, longitude and attitude and cuisine for those restaurants which contains 'mon' as three letters somewhere in its name
db.restaurants.find({name: "mon",}, {name: 1, borough: 1, address: 1, cuisine: 1});