Retrieve a specific field Mongoose - node.js

I want retrieve the account array if the query find role "elite"
i try with
db.users.aggregate(
{ $match : { "account.role" : "Elite" } }
);
But i have all object...
{
"_id" : ObjectId("7623902143981943"),
"account" : [
{
"role" : "Elite",
"action" : [
"create",
"read",
"update",
"delete"
],
"extra" : {
account:[1,2,3,4]
}
},
{
"role" : "User",
"action" : [
"create",
"read",
"update",
"delete"
],
"extra" : {
account:[10]
}
}
],
}
Can i retrieve only extra Array ( account:[1,2,3,4] ),if it is a positive result from the query? or I have to parse the received object?
(the schema is very simplified, but I have many roles)

You must use $project and $unwind:
//Order of $unwind and $match matters
db.users.aggregate(
{$unwind: "$account"},
{$match : { "account.role" : "Elite" }},
{$project : { "extra.account" : 1}}
);
explanation
$unwind splits the array into different elements. See the effect of
db.users.aggregate({$unwind: "$account"})
then you match the elements with {"account.role": "Elite"}. See the effect of:
db.users.aggregate(
{$unwind: "$account"},
{$match : { "account.role" : "Elite" }}
);
And then you finally project just the desired fields
db.users.aggregate(
{$unwind: "$account"},
{$match : { "account.role" : "Elite" }},
{$project : { "extra.account" : 1}}
);
//You can also remove the _id filed (included by default with:
db.users.aggregate(
{$unwind: "$account"},
{$match : { "account.role" : "Elite" }},
{$project : { _id: 0, "extra.account" : 1}}
);
OLD ANSWER
You must use projection:
db.users.aggregate(
{$match : { "account.role" : "Elite" }},
{$project : { "extra.account" : 1}}
);
Besides, if you are just matching documents, there's no need to use the aggregation framewrok and you can just use:
// No projection here
db.users.find({"account.role" : "Elite"})
or
// Only returns the _id field + "extra.account" field if exists. By default the _id field is included
db.users.find({"account.role" : "Elite"}, { "extra.account" : 1})
// Only returns the "extra.account" field if exists
db.users.find({"account.role" : "Elite"}, { _id: 0, "extra.account" : 1})
Mongodb documentation can be found here and here

Related

How to fetch document with filtered nested document using Mongo query?

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

How to get arrays on output from MongoDB aggregate

I have documents in MongoDB, like so:
{
"_id" : ObjectId("5a748c8b178227d602ec9ce8"),
"dateHour" : ISODate("2018-02-02T16:00:00.000Z"),
"data" : [
{
"date" : ISODate("2018-02-02T16:06:35.033Z"),
"cap" : 437105726836.0
},
{
"date" : ISODate("2018-02-02T16:09:25.127Z"),
"cap" : 437316498502.0
},
...
]
}
Using aggregate method (in NodeJS):
db.getCollection('hourly').aggregate([
{$match: {}},
{$unwind: "$data"},
{$project: {_id: 0, date: "$data.date", cap: "$data.cap" } }
])
I get output like:
[
{
"date" : ISODate("2018-02-02T16:06:35.033Z"),
"cap" : 437105726836.0
},
{
"date" : ISODate("2018-02-02T16:09:25.127Z"),
"cap" : 437316498502.0
}
]
QUESTION: What is the most effective way to get output like so:
[
[ISODate("2018-02-02T16:06:35.033Z"), 437105726836.0],
[ISODate("2018-02-02T16:09:25.127Z"), 437316498502.0]
]
?
I can simply add .map(function(item) {return [item.date, item.cap]}) but is this most effective way when working with huge amount of data?
try $project with $map or $reduce
$map
db.col.aggregate(
[
{$project : {
_id : 0,
data : {$map : {input : "$data", as : "d", in : ["$$d.date", "$$d.cap"]}}
}
}
]
)
$reduce
db.col.aggregate(
[
{$project : {
_id : 0,
data : {$reduce : {input : "$data", initialValue : [], in : {$concatArrays : ["$$value", [["$$this.date", "$$this.cap"]]]}}}
}
}
]
).pretty()
output
{
"data" : [
[
ISODate("2018-02-02T16:06:35.033Z"),
437105726836
],
[
ISODate("2018-02-02T16:09:25.127Z"),
437316498502
]
]
}
The root has to be a document, proof:
db.test.aggregate([
{$unwind: "$data"},
{ $replaceRoot: { newRoot: ["$data.date", "$data.cap"] } }
]);
assert: command failed: {
"ok" : 0,
"errmsg" : "'newRoot' expression must evaluate to an object, but resulting value was: [null, null]. Type of resulting value: 'array'. Input document: {date: 2018-02-02T16:06:35.033Z, cap: 4.37106e+11}",
"code" : 40228,
"codeName" : "Location40228"
} : aggregate failed
You could, however, project it into an array within a document:
> db.test.aggregate([
... {$unwind: "$data"},
... { $replaceRoot: { newRoot: {a:["$data.date", "$data.cap"] } }}
... ])
{ "a" : [ ISODate("2018-02-02T16:06:35.033Z"), 437105726836 ] }
{ "a" : [ ISODate("2018-02-02T16:09:25.127Z"), 437316498502 ] }
It's in the projection. Try this:
db.getCollection('hourly').aggregate([
{$match: {}},
{$unwind: "$data"},
{$project: {_id: 0, date: ["$data.date", "$data.cap"] } }
]);
Just in case my syntax is a little off, here is MongoDb documentation to project a new array.
I don't see why you need aggregate.
Why not:
db.getCollection('hourly').find({}, {data: 1}, (err, results) => {
// manage results here.
});

Searching value in 2 different fields mongodb + node.js

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"}}
])

customize aggregate $group outpout in node.js

I am using aggregate in node.js as follows
collection.aggregate(
{
$group : {
_id : "$id_page",
"count" : {$sum : 1}
}
},
{$sort : {"count" : -1}},
{$limit : 1}
).limit(1).toArray(function (err, r) { ................. })
this runs correctly but I am getting this result
{ id: '346593403645', _id: 57a868497e07fcf75f27009c, __v: 0 }
because of the _id key, the object cannot be exploited.
Is it possible to use aggregate such a way it does not return the _id key?
use $project and choose which field is display
collection.aggregate(
{
$group : {
_id : "$id_page",
"count" : {$sum : 1}
}
},
{$sort : {"count" : -1}},
{$limit : 1} ,
{$project:{count:1,_id:0}}
)

Find sub-documents using $in with MongoDB

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.

Resources