{
"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"
}
1. Write a MongoDB query to display all the documents in the collection restaurants.
db.restaurants.find().pretty();
2. 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});
3. 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});
4. 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,"address.zipcode" :1,"_id":0});
5. Write a MongoDB query to display all the restaurant which is in the borough Bronx.
db.restaurants.find({"borough": "Bronx"});
6. Write a MongoDB query to display the first 5 restaurant which is in the borough Bronx.
db.restaurants.find({"borough": "Bronx"}).limit(5);
7.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);
8. Write a MongoDB query to find the restaurants who achieved a score more than 90.
db.restaurants.find({grades : { $elemMatch:{"score":{$gt : 90}}}});
9. Write a MongoDB query to find the restaurants that achieved a score, more than 80 but less than 100.
db.restaurants.find({grades : { $elemMatch:{"score":{$gt : 80 , $lt :100}}}});
10. Write a MongoDB query to find the restaurants which locate in latitude value less than -95.754168.
db.restaurants.find({"address.coord" : {$lt : -95.754168}});
11. 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}}
]
}
);
12. 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.
db.restaurants.find(
{$query:
{
"cuisine" : {$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 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"
},
$orderby : {"cuisine":-1}
}
);
14. Write a MongoDB query to find the restaurant Id, name, borough and cuisine for those restaurants which contain 'Wil' as first three letters for its name.
db.restaurants.find(
{name: /^Wil/},
{
"restaurant_id" : 1,
"name":1,"borough":1,
"cuisine" :1
}
);
15. Write a MongoDB query to find the restaurant Id, name, borough and cuisine for those restaurants which contain 'ces' as last three letters for its name.
db.restaurants.find(
{name: /ces$/},
{
"restaurant_id" : 1,
"name":1,"borough":1,
"cuisine" :1
}
);
16. 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
}
);
17. 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" ,
$or : [
{ "cuisine" : "American " },
{ "cuisine" : "Chinese" }
]
}
);
18. Write a MongoDB query to find the restaurant Id, name, borough and cuisine for those restaurants which belong to the borough Staten Island or Queens or Bronxor Brooklyn.
db.restaurants.find(
{"borough" :{$in :["Staten Island","Queens","Bronx","Brooklyn"]}},
{
"restaurant_id" : 1,
"name":1,"borough":1,
"cuisine" :1
}
);
19. 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","Bronx","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 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
}
);
21. 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}
);
22. 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": ISODate("2014-08-11T00:00:00Z"),
"grades.grade":"A" ,
"grades.score" : 11
},
{"restaurant_id" : 1,"name":1,"grades":1}
);
23. 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".
db.restaurants.find(
{ "grades.1.date": ISODate("2014-08-11T00:00:00Z"),
"grades.1.grade":"A" ,
"grades.1.score" : 9
},
{"restaurant_id" : 1,"name":1,"grades":1}
);
24. 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..
db.restaurants.find(
{
"address.coord.1": {$gt : 42, $lte : 52}
},
{"restaurant_id" : 1,"name":1,"address":1,"coord":1}
);
25. 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});
26. Write a MongoDB query to arrange the name of the restaurants in descending along with all the columns.
db.restaurants.find().sort(
{"name":-1}
);
27. 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,}
);
28. Write a MongoDB query to know whether all the addresses contains the street or not.
db.restaurants.find(
{"address.street" :
{ $exists : true }
}
);
29. Write a MongoDB query which will select all documents in the restaurants collection where the coord field value is Double.
db.restaurants.find(
{"address.coord" :
{$type : 1}
}
);
30. 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}
);
31. 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 :
{ $regex : "mon.*", $options: "i" }
},
{
"name":1,
"borough":1,
"address.coord":1,
"cuisine" :1
}
);
32. Write a MongoDB query to find the restaurant name, borough, longitude and latitude and cuisine for those restaurants which contain 'Mad' as first three letters of its name.
db.restaurants.find(
{ name :
{ $regex : /^Mad/i, }
},
{
"name":1,
"borough":1,
"address.coord":1,
"cuisine" :1
}
);
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