i am not able to query results in this query,
i want result based on detail.type (like fetch record where detail.type="one") and fetch only first 10 records in detail.numbers array
{
"_id" : ObjectId("5a27b609e101b6092b4ebf91"),
"city" : "Mumbai",
"detail" : [
{
"type" : "One",
"name" : "Some name",
"_id" : ObjectId("5a27b609e101b6092b4ebf92"),
"numbers" : [
"72598xxx78",
"81301xxx88",
"83302xxx30",
"84309xxx43",
"85309xxx77",
"86309xxx61",
"87270xxx88",
"85272xxx36",
"88272xxx23",
"85276xxx01"
]
},
{
"name" : "Some name",
"type" : "two",
"_id" : ObjectId("5a28e954d4f5a30527d92a32"),
"contact" : [
"72598xxx78",
"81301xxx88",
"83302xxx30",
"84309xxx43",
"85309xxx77",
"86309xxx61",
"87270xxx88",
"85272xxx36",
"88272xxx23",
"85276xxx01"
]
},
]
}
MongoDB facilitates querying over array elements using $elemMatch operator.
According to description as mentioned into above question as a solution to it please try executing following MongoDB query to fetch required data from MongoDB collection.
db.collection.find({
detail: {
$elemMatch: {
type: 'One'
}
}
}, {
_id: 1,
city: 1,
'detail.$': 1
})
db.collection.aggregate([
{
$project:{
detail:{
$map:{
input:{$filter:{input:"$detail",as:"d",cond:{$eq:["$$d.type","One"]}}},
as:"d",
in:{
"type" : "$$d.type",
"name" : "$$d.name",
"numbers":{$slice:["$$d.numbers",10]}
}
}
}
}
}
])
Related
For the given structure I need to find out the count of the likes array based on the unique slug value
{
"_id" : ObjectId("4e8ae86d08101908e1000001"),
"name" : ["Name"],
"likes" : ["emp1"],
"slug": 'slugabcd'
}
{
"_id" : ObjectId("4e8ae86d08101908e1000002"),
"name" : ["Another ", "Name"],
"likes" : ["emp1","emp2","emp4"],
"slug": 'slugxyz'
}
{
"_id" : ObjectId("4e8ae86d08101908e1000002"),
"name" : ["Another ", "Name"],
"slug": 'slugpqr'
}
Here is my code but not working
db.blog.aggregate({slug:"slugxyz"},{$project:{NumberOfItemsInArray:{$size:"likes"}}}).count();
How can we achieve this?
Without using any query stage:
db.blog.aggregate({$project:{slug : "$slug", numberOfLikes:{$size:"$likes"}}})
Try the following:
const pipeline = [
{
$group: {
_id: "$slug",
likesCount: {$sum: {$size: "$likes"}}
}
]
Here we are grouping by the unique "slug" value and counting the size of "likes" array field.
Here is my organization collection.
[{
"_id" : ObjectId("5fd5fc1b9f117029b5233b2e"),
"name" : "ClassA",
"orgMembers" : [
{
"_id" : ObjectId("5fd5fc1b9f117029b5233b2f"),
"userId" : "Ben",
},
{
"_id" : ObjectId("5fd5fc1b9f117029b5233b2f"),
"userId" : "Anton",
}
],
},
{
"_id" : ObjectId("5fd5fc1b9f117029b5233b2e"),
"name" : "ClassA",
"orgMembers" : [
{
"_id" : ObjectId("5fd5fc1b9f117029b5233b2f"),
"userId" : "Ben",
}
],
}]
Each document has properties like _id, name, orgMembers which represent document information.
And orgMembers is the Array of Members (_id, userId) who belongs to organization.
In this collection, I want to fetch the organizations which includes orgMember with Anton as userId and as well orgMembers of fetched organization document should only contain Anton as a orgMember.
Expected Result is likewise
[{
"_id" : ObjectId("5fd5fc1b9f117029b5233b2e"),
"name" : "ClassA",
"orgMembers" : [
{
"_id" : ObjectId("5fd5fc1b9f117029b5233b2f"),
"userId" : "Anton",
}
],
}]
Here ClassA organization has two orgMembers but need to be filtered matching with userId.
I have tried with
documentModel.find({ 'orgMembers.userId': 'Anton' })
But within this query, I get the result like this.
[{
"_id" : ObjectId("5fd5fc1b9f117029b5233b2e"),
"name" : "ClassA",
"orgMembers" : [
// should be omitted
{
"_id" : ObjectId("5fd5fc1b9f117029b5233b2f"),
"userId" : "Ben",
},
// should be contained
{
"_id" : ObjectId("5fd5fc1b9f117029b5233b2f"),
"userId" : "Anton",
}
],
}]
For expected result, orgMember with userId: Ben should be omitted.
How can I get my expected result with mongo query?
I believe this will be worked on your side
db.collection.find({
"orgMembers.userId": "Anton"
},
{
orgMembers: {
"$elemMatch": {
userId: "Anton"
}
}
})
not sure if i quite got your requirement:
but try this if it works
db.collection.find({
"orgMembers.userId": {
$regex: "Anton",
$options: "i"
}
},
{
name: 1,
"orgMembers.$": 1
})
this is to return only the userId you are looking for in orgMembers.if there are more orgmembers they will not be part of output
I have a schema in which it has some fields..
i am not able to find query for this, i tried $group but was not able to find results
collection: tasks
{
"_id" : ObjectId("5a475ee4b342fa03e71192bd"),
"title" : "Some Title",
"assignedUsers" : [
{
"_id" : ObjectId("5a47386ee4788102e530f60d"),
"name" : "Sam",
"status" : "Unconfirmed"
},
{
"_id" : ObjectId("5a473878e4788102e530f60f"),
"name" : "Ricky",
"status" : "Rejected"
}
{
"_id" : ObjectId("5a47388be4788102e530f611"),
"name" : "Niel",
"status" : "Unconfirmed"
},
{
"_id" : ObjectId("5a47388be4788102e530f611"),
"name" : "ABC",
"status" : "Unconfirmed"
},
{
"_id" : ObjectId("5a473892e4788102e530f612"),
"name" : "Rocky",
"status" : "Rejected"
}
]
}
Result should contain
Unconfirmed=3
Rejected=2
Thanks
Use below query,
db.coll3.aggregate([{
$unwind: '$assignedUsers'
}, {
$group: {
_id: '$assignedUsers.status',
'count': {
$sum: 1
}
}
}
])
If you want to query against a particular document make sure, you use a $match as first stage and then use the other 2 $unwind and $group.
You would get result as
{ "_id" : "Rejected", "count" : 2 }
{ "_id" : "Unconfirmed", "count" : 3 }
Hope this helps.
I am newbie. But I try to learn the most logical ways to write the queries.
Assume I have collection which is as;
{
"id" : NumberInt(1),
"school" : [
{
"name" : "george",
"code" : "01"
},
{
"name" : "michelangelo",
"code" : "01"
}
],
"enrolledStudents" : [
{
"userName" : "elisabeth",
"code" : NumberInt(21)
}
]
}
{
"id" : NumberInt(2),
"school" : [
{
"name" : "leonarda da vinci",
"code" : "01"
}
],
"enrolledStudents" : [
{
"userName" : "michelangelo",
"code" : NumberInt(25)
}
]
}
I want to list occurence of a key with their corresponding code values.
As an example key : michelangelo
To find the occurence of the key, I wrote two differen aggregation queries as;
db.test.aggregate([
{$unwind: "$school"},
{$match : {"school.name" : "michelangelo"}},
{$project: {_id: "$id", "key" : "$school.name", "code" : "$school.code"}}
])
and
db.test.aggregate([
{$unwind: "$enrolledStudents"},
{$match : {"enrolledStudents.userName" : "michelangelo"}},
{$project: {_id: "$id", "key" : "$enrolledStudents.userName", "code" : "$enrolledStudents.code"}}
])
the result of these 2 queries return what I want as;
{ "_id" : 1, "key" : "michelangelo", "code" : "01" }
{ "_id" : 2, "key" : "michelangelo", "code" : 25 }
One of them to search in enrolledStudents, the other one is searching in school field.
Can these 2 queries reduced into more logical query? Or is this the only way to do it?
ps: I am aware that database structure is not logical, but I tried to simulate.
edit
I try to write a query with find.
db.test.find({$or: [{"enrolledStudents.userName" : "michelangelo"} , {"school.name" : "michelangelo"}]}).pretty()
but this returns the whole documents as;
{
"id" : 1,
"school" : [
{
"name" : "george",
"code" : "01"
},
{
"name" : "michelangelo",
"code" : "01"
}
],
"enrolledStudents" : [
{
"userName" : "elisabeth",
"code" : 21
}
]
}
{
"id" : 2,
"school" : [
{
"name" : "leonarda da vinci",
"code" : "01"
}
],
"enrolledStudents" : [
{
"userName" : "michelangelo",
"code" : 25
}
]
}
Mongo 3.4
$match - This stage will keep all the school array and enrolledStudents where there is atleast one embedded document matching both the query condition
$group - This stage will combine all the school and enrolledStudents array to 2d array for each _id in a group.
$project - This stage will $filter the merge array for matching query condition and $map the array to with new labels values array.
$unwind - This stage will flatten the array.
$addFields & $replaceRoot - This stages will add the id field and promote the values array to the top.
db.collection.aggregate([
{$match : {$or: [{"enrolledStudents.userName" : "michelangelo"} , {"school.name" : "michelangelo"}]}},
{$group: {_id: "$id", merge : {$push:{$setUnion:["$school", "$enrolledStudents"]}}}},
{$project: {
values: {
$map:
{
input: {
$filter: {
input: {"$arrayElemAt":["$merge",0]},
as: "onef",
cond: {
$or: [{
$eq: ["$$onef.userName", "michelangelo"]
}, {
$eq: ["$$onef.name", "michelangelo"]
}]
}
}
},
as: "onem",
in: {
key : { $ifNull: [ "$$onem.userName", "$$onem.name" ] },
code : "$$onem.code"}
}
}
}
},
{$unwind: "$values"},
{$addFields:{"values.id":"$_id"}},
{$replaceRoot: { newRoot:"$values"}}
])
Sample Response
{ "_id" : 2, "key" : "michelangelo", "code" : 25 }
{ "_id" : 1, "key" : "michelangelo", "code" : "01" }
Mongo <= 3.2
Replace last two stages of above aggregation with $project to format the response.
{$project: {"_id": 0 , id:"$_id", key:"$values.key", code:"$values.code"}}
Sample Response
{ "_id" : 2, "key" : "michelangelo", "code" : 25 }
{ "_id" : 1, "key" : "michelangelo", "code" : "01" }
You can use $redact instead of $group & match and add $project with $map to format the response.
$redact to go through a document level at a time and perform $$DESCEND and $$PRUNE on the matching criteria.
The only thing to note is usage of $ifNull in the first document level for id so that you can $$DESCEND to embedded document level for further processing.
db.collection.aggregate([
{
$redact: {
$cond: [{
$or: [{
$eq: ["$userName", "michelangelo"]
}, {
$eq: ["$name", "michelangelo"]
}, {
$ifNull: ["$id", false]
}]
}, "$$DESCEND", "$$PRUNE"]
}
},
{
$project: {
id:1,
values: {
$map:
{
input: {$setUnion:["$school", "$enrolledStudents"]},
as: "onem",
in: {
key : { $ifNull: [ "$$onem.userName", "$$onem.name" ] },
code : "$$onem.code"}
}
}
}
},
{$unwind: "$values"},
{$project: {_id:0,id:"$id", key:"$values.key", code:"$values.code"}}
])
My task is to find individual authors(comments.user_id) comment on the article (_id)
{
"_id" : ObjectId("56479d9c8510369a4ecea3a9"),
"comments" : [
{
"text" : "222",
"user_id" : ObjectId("563f2db0e2bf6c431b297d45"),
},
{
"text" : "333",
"user_id" : ObjectId("563f2db0e2bf6c431b297d45"),
},
{
"text" : "444",
"user_id" : ObjectId("563f2db0e2bf6c431b297d45"),
},
{
"text" : "55555",
"user_id" : ObjectId("563e3337e2bf6c431b297d41"),
},
{
"text" : "00000",
"user_id" : ObjectId("563f7c0a8db7963420cd5732"),
},
{
"text" : "00001",
"user_id" : ObjectId("563f7c0a8db7963420cd5732"),
}
]
}
My query looks as follows
db.getCollection('messages').find({
'_id': ObjectId("56479d9c8510369a4ecea3a9"),
'comments.user_id': {$in : [
ObjectId("563e3337e2bf6c431b297d41"),
ObjectId("563f7c0a8db7963420cd5732")
]}
})
It returns all comments. Please help to understand why it happens.
Expected Result
{
"_id" : ObjectId("56479d9c8510369a4ecea3a9"),
"comments" : [
{
"text" : "55555",
"user_id" : ObjectId("563e3337e2bf6c431b297d41"),
},
{
"text" : "00000",
"user_id" : ObjectId("563f7c0a8db7963420cd5732"),
},
{
"text" : "00001",
"user_id" : ObjectId("563f7c0a8db7963420cd5732"),
}
]
}
update query (hopelessness)
db.getCollection('messages').find(
{'_id': ObjectId("56479d9c8510369a4ecea3a9")},
{'comments.user_id': {$in: ["563f2db0e2bf6c431b297d45", "563e3337e2bf6c431b297d41"]}},
{'comments.user_id': {$elemMatch: {$in: ["563f2db0e2bf6c431b297d45", "563e3337e2bf6c431b297d41"]}}}
)
db.getCollection('messages').find(
{'_id': ObjectId("56479d9c8510369a4ecea3a9")},
{comments: {$elemMatch: {'user_id': {$in : [ObjectId("563f2db0e2bf6c431b297d45"), ObjectId("563f7c0a8db7963420cd5732")]}}}}
)
I return only 1 record, and I have all the records from these authors
As you've seen, the $ and $elemMatch projection operators only include the first matching element.
To include multiple, filtered array elements in your projection of the comment array, your can use aggregate with the $redact operator instead of find:
db.getCollection('test').aggregate([
{$match: {
'_id': ObjectId("56479d9c8510369a4ecea3a9"),
'comments.user_id': {$in : [
ObjectId("563e3337e2bf6c431b297d41"),
ObjectId("563f7c0a8db7963420cd5732")
]},
}},
{$redact: {
$cond: {
if: {
$or: [
{$eq: ['$user_id', ObjectId("563e3337e2bf6c431b297d41")]},
{$eq: ['$user_id', ObjectId("563f7c0a8db7963420cd5732")]},
{$not: '$user_id'}
]
},
then: '$$DESCEND',
else: '$$PRUNE'
}
}}
])
$redact iterates over each doc like a tree, keeping or trimming the fields of each doc as it's $cond expression dictates.
It gets a bit tricky to wrap your head around $redact, but it's basically saying that if the level's user_id field matches either of the two ObjectIds in your $in, or it's not present (i.e. as it is in the top level of the doc), include the data, otherwise remove it.