How do I find the documents with with average score greater than 5. The collection looks like this:
Collection restaurants:
{"grades": [{"grade": "A", "score": 2}, {"grade": "A", "score": 6}], "name": "Morris Park Bake Shop", "restaurant_id": "30075445"}
{"grades": [{"grade": "A", "score": 8}, {"grade": "B", "score": 23}], "name": "Wendy'S", "restaurant_id": "30112340"}
{"grades": [{"grade": "A", "score": 2}, {"grade": "A", "score": 11}], "name": "Dj Reynolds Pub And Restaurant", "restaurant_id": "30191841"}
I tried
db.restaurants.find({average_socre: {$gt: 5}}, {average_socre:{$avg: "$grades.score"}})
but it doesn't work.
Using this query:
db.collection.find({
$expr: {
$gt: [
{
"$avg": "$grades.score"
},
5
]
}
},
{
average_score: {
$avg: "$grades.score"
}
})
Live
Related
I want to query a match between records in my db based on certain tags. The match would be calculated based on a formula and the intersection of the tags. Now, even querying the intersection doesn't work...always. Sometimes it does, sometimes it doesn't. In my example, if I change the displayName attribute to something else (add or remove one character, the query works. In its current state (for demo purposes) it doesn't as it does not deliver the one intersection match for the last doc with id 3.
https://mongoplayground.net/p/KAYPoV29RFO
That's my query:
db.collection.aggregate([
{
$match: {
"_id": "1"
}
},
{
"$lookup": {
from: "collection",
let: {
"criteria": "$tags"
},
pipeline: [
{
$project: {
"match": {
$setIntersection: [
"$tags",
"$$criteria"
]
},
}
}
],
as: "result"
}
},
{
$project: {
"tags": 0
}
},
])
Here is the example data (simplified):
[
{ "_id": "1", "tags": [{ "_id": "a", "displayName": "a", "level": 1}, {"_id": "b", "displayName": "b", "level": 2}, {"_id": "c", "displayName": "c", "level": 3}]},
{"_id": "2", "tags": [{"_id": "a", "displayName": "a", "level": 1}, {"_id": "b", "displayName": "b", "level": 2}]},
{"_id": "3", "tags": [{"_id": "a", "displayName": "a", "level": 1}, {"_id": "d", "displayName": "d", "level": 4}]}
]
and the result as it is: (expected is three matches for id 1, 2 matches for id 2 and one for the last id. However, the last result has 0 elements in the intersection result. Again, when i change "displayName" to "displayNam" or "displayNames" (obviously in all docs), it give the correct result...
[{
"_id": "1", "result": [
{"_id": "1", "match": [{"_id": "a", "displayName": "a", "level": 1}, {"_id": "b", "displayName": "b", "level": 2},{"_id": "c","displayName": "c","level": 3}]},
{"_id": "2", "match": [{"_id": "a", "displayName": "a", "level": 1}, {"_id": "b", "displayName": "b", "level": 2}]},
{"_id": "3","match": [*here should be the match to _id: "a", but it's not (always) there*]}
]
}]
Does anyone have an idea what I am missing here?
I would like to independently group the results of an or clause, including overlap. The data set is rather large so running 2 queries sequentially will result in an undesirable wait time. I am hoping I can somehow project which clause returned the corresponding data. Given this data set:
[
{
"_id": 1,
"item": "abc",
"name": "Michael",
"price": NumberDecimal("10"),
"quantity": NumberInt("2"),
"date": ISODate("2014-03-01T08:00:00Z")
},
{
"_id": 2,
"item": "jkl",
"name": "Toby",
"price": NumberDecimal("20"),
"quantity": NumberInt("1"),
"date": ISODate("2014-03-01T09:00:00Z")
},
{
"_id": 3,
"item": "xyz",
"name": "Keith",
"price": NumberDecimal("5"),
"quantity": NumberInt("10"),
"date": ISODate("2014-03-15T09:00:00Z")
},
{
"_id": 4,
"item": "abc",
"name": "Dwight",
"price": NumberDecimal("5"),
"quantity": NumberInt("20"),
"date": ISODate("2014-04-04T11:21:39.736Z")
},
{
"_id": 5,
"item": "abc",
"name": "Ryan",
"price": NumberDecimal("10"),
"quantity": NumberInt("10"),
"date": ISODate("2014-04-04T21:23:13.331Z")
},
{
"_id": 6,
"item": "def",
"name": "Jim",
"price": NumberDecimal("7.5"),
"quantity": NumberInt("5"),
"date": ISODate("2015-06-04T05:08:13Z")
},
{
"_id": 7,
"item": "abc",
"name": "Keith",
"price": NumberDecimal("7.5"),
"quantity": NumberInt("10"),
"date": ISODate("2015-09-10T08:43:00Z")
},
{
"_id": 8,
"item": "abc",
"name": "Michael",
"price": NumberDecimal("10"),
"quantity": NumberInt("5"),
"date": ISODate("2016-02-06T20:20:13Z")
},
]
I would like to receive this result:
[{
"_id": {
"name": "Keith"
},
"count": 2
},
{
"_id": {
"item": "abc",
},
"count": 5
}]
Here is what I have tried so far:
db.collection.aggregate([
{
$match: {
$or: [
{
item: "abc"
},
{
name: "Keith"
}
]
}
},
{
$group: {
_id: {
item: "$item",
name: "$name"
},
count: {
$sum: 1
}
}
}
])
You can use $facet to get multiple aggregation pipelines into the same stage in this way:
Using $facet there are two "outputs" one group by name and other by item.
In each one there are multiple stages:
First $match to process only documents you want.
Then $group with _id name or item, and $count to get the total.
db.collection.aggregate([
{
"$facet": {
"groupByName": [
{
"$match": {"name": "Keith"}
},
{
"$group": {"_id": "$name","count": {"$sum": 1}}
}
],
"groupByItem": [
{
"$match": {"item": "abc"}
},
{
"$group": {"_id": "$item","count": {"$sum": 1}}
}
]
}
}
])
Example here
The output is:
{
"groupByItem": [
{
"_id": "abc",
"count": 5
}
],
"groupByName": [
{
"_id": "Keith",
"count": 2
}
]
}
Here it is:
mongos> db.n.aggregate([ { $facet:{ names:[ {$match:{name:"Keith"}} , {$group:{_id:{name:"$name"}, count:{$sum:1}}} ] , items:[ {$match:{item:"abc"}},{ $group:{_id:{item:"$item"}, count:{$sum:1}} } ] } } , {$project:{ "namesANDitems":{$concatArrays:[ "$names","$items" ]} }} ,{$unwind:"$namesANDitems"} ,{$replaceRoot:{newRoot:"$namesANDitems"} } ]).pretty()
{ "_id" : { "name" : "Keith" }, "count" : 2 }
{ "_id" : { "item" : "abc" }, "count" : 5 }
mongos>
explained:
You create two pipes via $facet
Match in every facet pipe what you need to group pipe1=names , pipe2=items
Join the arrays from the two pipes in single array named "namesANDitems"
Convert the array to object with $unwind
Remove the temporary object name namesANDitems so you have only the two objects as requested
I have a collection with this schema:
{
"fields":
{
"field1": [
{"name": "abc", "value": 2},
{"name": "bcd", "value": 4},
{"name": "cde", "value": 6}
],
"field2": [
{"name": "dec", "value": 3},
{"name": "das", "value": 8},
{"name": "pam", "value": 10}
]
}
},
{
"fields":
{
"field1": [
{"name": "abc", "value": 7},
{"name": "cde", "value": 12}
],
"field2": [
{"name": "dec", "value": 3},
{"name": "das", "value": 8},
{"name": "pam", "value": 10}
]
}
}
What I'm trying to obtain is e.g. the average values of all members of 'field1', evaluating 0 if a member exist in a document but not in another (like 'bcd').
So in this example I should get:
{
'_id': 'abc',
'avg': 4.5
},
{
'_id': 'bcd',
'avg': 2
},
{
'_id': 'cde',
'avg': 9
}
I wrote this aggregation query but I'm pretty sure there is something wrong with it:
db.statuses.aggregate([
{
$unwind: '$fields.field1'
},
{
$group: {
_id: '$fields.field1.name',
avg: {
$avg: '$fields.field1.value'
}
}
},
{
$sort: {
avg: -1
}
}
])
I think I should add a step before the average calculation in which I have to build an array of all values for each name (0 if the name does not exist in a document), and then evaluate the average on these arrays. Am I right?
How could I do this?
I have the following document:
{
"address": {
"building": "1007",
"coord": [ -73.856077, 40.848447 ],
"street": "Morris Park Ave",
"zipcode": "10462"
},
"borough": "Bronx",
"cuisine": "Bakery",
"grades": [
{ "date": { "$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"
}
I want a query that looks at the grades.grade and grades.score and doesn't return a this document if a grades object has grade == "A" AND score == 2. However, I want it to return a document if for example one grades object has grade == "A" and another grades object has score == 2.
This might also illustrate what I'm trying to do (although it doesn't work):
db.restaurants.find({
grades : {
$and: [
{"grade": {'$ne':"A"}},
{"score": {'$ne':2}}
]
}
});
You can try below query.
You basically require $anding $or and $nand. MongoDB doesn't have $nand operator, so I replaced it with the equivalent experession.
db.restaurants.find({
$and: [{
$or: [{
"grades.grade": "A"
}, {
"grades.score": 2
}]
}, {
$nor: [{
$and: [{
"grades.grade": "A"
}, {
"grades.score": 2
}]
}]
}]
});
$or operation will match all documents where any of the grade embedded document has either grade A or score is 2.
{ "grade": "A", "score": 3 } --- Just grade A
{ "grade": "A", "score": 2 } --- Both grade A and score 2
{ "grade": "B", "score": 2 } --- Just score 2
$nand operation will match all the documents where none of the grade embedded documents has both grade as A and score is 2
{ "grade": "A", "score": 3 } --- Just grade A
{ "grade": "B", "score": 2 } --- Just score 2
{ "grade": "C", "score": 4 } --- None
$and of above operations is the intersection.
{ "grade": "A", "score": 3 } --- Just grade A
{ "grade": "B", "score": 2 } --- Just score 2
Question: Write a MongoDB query to find the restaurants which locates in latitude value less than -95.754168.
Structure of 'restaurants' collection
{
"address": {
"building": "1007",
"coord": [ -73.856077, 40.848447 ],
"street": "Morris Park Ave",
"zipcode": "10462"
},
"borough": "Bronx",
"cuisine": "Bakery",
"grades": [
{ "date": { "$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"
}
Author's Answer is : db.restaurants.find({"address.coord" : {$lt : -95.754168}});
Is this the correct answer?
If no then what is the correct answer?
Resource: http://www.w3resource.com/mongodb-exercises/#PracticeOnline
You can go into your coord index like this
db.restaurants.find({"address.coord.0" : {$lt: -95.754168}});
According to the documentation here,
MongoDB uses the dot notation to access the elements of an array and to access the fields of an embedded document.
E.g. <array>.<index>
Note that the index is 0-based.