Use $project aggregation to edit documents schema - MongoDB - mongodb

I have this MongoDB document:
{
"_id" : 1,
title: "abc123",
isbn: "0001122223334",
author: { last: "zzz", first: "aaa" },
copies: 5
}
Using $project (aggregation operator) I have to reshape the previous schema to get:
{
"_id" : 1,
field: {key:"title", value:"abc123"},
isbn: "0001122223334",
author: { last: "zzz", first: "aaa" },
copies: 5
}
To reach my target I used the following aggregation:
db.book.aggregate([{$project: {"field": {"key":"title", "value":"$title"}}}])
but I got an error:
{
"ok" : 0,
"errmsg" : "FieldPath 'isbn' doesn't start with $",
"code" : 16873
} : aggregate failed
I don't understand why that aggregation does not work, since if I want to reshape the previous schema to get:
{
"_id" : 1,
"author" : {
"last" : "zzz",
"first" : "aaa"
},
"copies" : 5,
"fieldTitle" : {
"key" : "abc123"
}
}
I can use this aggregation (and it works):
db.book.aggregate([{$project: {_id:1, fieldTitle:{key:"$title"}, author:1, copies:1}}])

Use the $literal operator to return a value without parsing. It's used for values that the aggregation pipeline may interpret as an expression, like the error you are presently getting:
db.book.aggregate([
{
$project: {
"field.key": { "$literal": "title" },
"field.value": "$title",
"author": 1, "copies": 1
}
}
])
Sample Output
{
"result" : [
{
"_id" : 1,
"author" : {
"last" : "zzz",
"first" : "aaa"
},
"copies" : 5,
"field" : {
"key" : "title",
"value" : "abc123"
}
}
],
"ok" : 1
}

Related

Whats the alternative to $replaceRoot on mongoDB? $replaceRoot is incompatible with documentDB

The problem: I'm trying to make a query on MongoDB, but I'm using the DocumentDb from amazon, where some operations are no supported. I wanted to find an alternative to get the same result, if possible. Basically I want to change the root of the result, instead of being the first entity, I need it to be some merging of some values in different levels of the document.
So, I have the following structure in my collection:
{
"_id" : ObjectId("5e598bf4d98f7c70f9aa3b58"),
"status" : "active",
"invoices" : [
{
"_id" : ObjectId("5e598bf13b24713f50600375"),
"value" : 1157.52,
"receivables" : [
{
"situation" : {
"status" : "active",
"reason" : []
},
"rec_code" : "001",
"_id" : ObjectId("5e598bf13b24713f50600374"),
"expiration_date" : ISODate("2020-03-25T00:00:00.000Z"),
"value" : 1157.52
}
],
"invoice_code" : 9773,
"buyer" : {
"legal_name" : "test name",
"buyer_code" : "223132165498797"
}
},
],
"seller" : {
"code" : "321654897986",
"name" : "test name 2"
}
}
What I want to achieve is to list all "receivables" like this, where the _id is the _id of the receivable:
[{
"_id" : ObjectId("5e598bf13b24713f50600374"),
"situation" : {
"status" : "active",
"reason" : []
},
"rec_code" : "001",
"expiration_date" : ISODate("2020-03-25T00:00:00.000Z"),
"value" : 1157.52,
"status" : "active",
"seller" : {
"cnpj" : "321654897986",
"name" : "test name 2"
},
"invoice_code" : 9773.0,
"buyer" : {
"legal_name" : "test name",
"cnpj" : "223132165498797"
}
}]
This I can do with $replaceRoot in with the query below on MongoDB, but using documentDB I can't use $replaceRoot or $mergeObjects. Do you know how can I get the same result with other operators?:
db.testCollection.aggregate([
{ $unwind: "$invoices" },
{ $replaceRoot: {
newRoot: {
$mergeObjects: ["$$ROOT","$invoices"]}
}
},
{$project: {"_id": 0, "value": 0, "created_at": 0, "situation": 0}},
{ $unwind: "$receivables" },
{ $replaceRoot: {
newRoot: {
$mergeObjects: ["$receivables", "$$ROOT"]
}
}
},
{$project:{"created_at": 0, "receivables": 0, "invoices": 0}}
])
After going through mongodb operations, I could get a similar result fro what I wanted with the following query without $replaceRoot. It turns out it was a better query, I think:
db.testCollection.aggregate([
{$unwind: "$invoices"},
{$project : {
created_at: 1,
seller: "$seller",
buyer: "$invoices.buyer",
nnf: "$invoices.nnf",
receivable: '$invoices.receivables'
}
},
{$unwind: "$receivable"},
{$project : {
_id: '$receivable._id',
seller: 1,
buyer: 1,
invoice_code: 1,
receivable: 1,
created_at: 1,
}
},
{$sort: {"created_at": -1}},
])
This query resulted in the following structure list:
[{
"created_at" : ISODate("2020-03-06T09:47:26.161Z"),
"seller" : {
"name" : "Test name",
"cnpj" : "21231232131232"
},
"buyer" : {
"cnpj" : "21322132164654",
"legal_name" : "Test name 2"
},
"invoice_code" : 66119,
"receivable" : {
"rec_code" : "001",
"_id" : ObjectId("5e601bb5efff82b92935bad4"),
"expiration_date" : ISODate("2020-03-17T00:00:00.000Z"),
"value" : 6540.7,
"situation" : {
"status" : "active",
"reason" : []
}
},
"_id" : ObjectId("5e601bb5efff82b92935bad4")
}]
Support for $replaceRoot was added to Amazon DocumentDB in January 2021.

How can I do match after second level unwind in mongodb?

I am working on a software that uses MongoDB as a database. I have a collection like this (this is just one document)
{
"_id" : ObjectId("5aef51e0af42ea1b70d0c4dc"),
"EndpointId" : "89799bcc-e86f-4c8a-b340-8b5ed53caf83",
"DateTime" : ISODate("2018-05-06T19:05:04.574Z"),
"Url" : "test",
"Tags" : [
{
"Uid" : "E2:02:00:18:DA:40",
"Type" : 1,
"DateTime" : ISODate("2018-05-06T19:05:04.574Z"),
"Sensors" : [
{
"Type" : 1,
"Value" : NumberDecimal("-98")
},
{
"Type" : 2,
"Value" : NumberDecimal("-65")
}
]
},
{
"Uid" : "12:3B:6A:1A:B7:F9",
"Type" : 1,
"DateTime" : ISODate("2018-05-06T19:05:04.574Z"),
"Sensors" : [
{
"Type" : 1,
"Value" : NumberDecimal("-95")
},
{
"Type" : 2,
"Value" : NumberDecimal("-59")
},
{
"Type" : 3,
"Value" : NumberDecimal("12.939770381907275")
}
]
}
]
}
and I want to run this query on it.
db.myCollection.aggregate([
{ $unwind: "$Tags" },
{
$match: {
$and: [
{
"Tags.DateTime": {
$gte: ISODate("2018-05-06T19:05:02Z"),
$lte: ISODate("2018-05-06T19:05:09Z"),
},
},
{ "Tags.Uid": { $in: ["C1:3D:CA:D4:45:11"] } },
],
},
},
{ $unwind: "$Tags.Sensors" },
{ $match: { "$Tags.Sensors.Type": { $in: [1, 2] } } },
{
$project: {
_id: 0,
EndpointId: "$EndpointId",
TagId: "$Tags.Uid",
Url: "$Url",
TagType: "$Tags.Type",
Date: "$Tags.DateTime",
SensorType: "$Tags.Sensors.Type",
Value: "$Tags.Sensors.Value",
},
},
])
the problem is, the second match (that checks $Tags.Sensors.Type) doesn't work and doesn't affect the result of the query.
How can I solve that?
If this is not the right way, what is the right way to run these conditions?
The $match stage accepts field names without a leading $ sign. You've done that correctly in your first $match stage but in the second one you write $Tags.Sensors.Type. Simply removing the leading $ sign should make your query work.
Mind you, the whole thing can be a bit simplified (and some beautification doesn't hurt, either):
You don't need to use $and in your example since it's assumed by default if you specify more than one criterion in a filter.
The $in that you use for the Tags.Sensors.Type filter can be a simple : kind of equality operator unless you have more than one element in the list of acceptable values.
In the $project stage, instead of (kind of) duplicating identical field names you can use the <field>: 1 syntax unless the order of the fields matters.
So the final query would be something like this.
db.myCollection.aggregate([
{
"$unwind" : "$Tags"
},
{
"$match" : {
"Tags.DateTime" : { "$gte" : ISODate("2018-05-06T19:05:02Z"), "$lte" : ISODate("2018-05-06T19:05:09Z") },
"Tags.Uid" : { "$in" : ["C1:3D:CA:D4:45:11"] }
}
}, {
"$unwind" : "$Tags.Sensors"
}, {
"$match" : {
"Tags.Sensors.Type" : { "$in" : [1,2] }
}
},
{
"$project" : {
"_id" : 0,
"EndpointId" : 1,
"TagId" : "$Tags.Uid",
"Url" : 1,
"TagType" : "$Tags.Type",
"Date" : "$Tags.DateTime",
"SensorType" : "$Tags.Sensors.Type",
"Value" : "$Tags.Sensors.Value"
}
}])

Sort a match group by id in aggregate

(Mongo newbie here, sorry) I have a mongodb collection, result of a mapreduce with this schema :
{
"_id" : "John Snow",
"value" : {
"countTot" : 500,
"countCall" : 30,
"comment" : [
{
"text" : "this is a text",
"date" : 2016-11-17 00:00:00.000Z,
"type" : "call"
},
{
"text" : "this is a text",
"date" : 2016-11-12 00:00:00.000Z,
"type" : "visit"
},
...
]
}
}
My goal is to have a document containing all the comments of a certain type. For example, a document John snow with all the calls.
I manage to have all the comments for a certain type using this :
db.general_stats.aggregate(
{ $unwind: '$value.comment' },
{ $match: {
'value.comment.type': 'call'
}}
)
However, I can't find a way to group the data received by the ID (for example john snow) even using the $group property. Any idea ?
Thanks for reading.
Here is the solution for your query.
db.getCollection('calls').aggregate([
{ $unwind: '$value.comment' },
{ $match: {
'value.comment.type': 'call'
}},
{
$group : {
_id : "$_id",
comment : { $push : "$value.comment"},
countTot : {$first : "$value.countTot"},
countCall : {$first : "$value.countCall"},
}
},
{
$project : {
_id : 1,
value : {"countTot":"$countTot","countCall":"$countCall","comment":"$comment"}
}
}
])
or either you can go with $project with $filter option
db.getCollection('calls').aggregate([
{
$project: {
"value.comment": {
$filter: {
input: "$value.comment",
as: "comment",
cond: { $eq: [ "$$comment.type", 'call' ] }
}
},
"value.countTot":"$value.countTot",
"value.countCall":"$value.countCall",
}
}
])
In both case below is my output.
{
"_id" : "John Snow",
"value" : {
"countTot" : 500,
"countCall" : 30,
"comment" : [
{
"text" : "this is a text",
"date" : "2016-11-17 00:00:00.000Z",
"type" : "call"
},
{
"text" : "this is a text 2",
"date" : "2016-11-17 00:00:00.000Z",
"type" : "call"
}
]
}
}
Here is the query which is the extension of the one present in OP.
db.general_stats.aggregate(
{ $unwind: '$value.comment' },
{ $match: {
'value.comment.type': 'call'
}},
{$group : {_id : "$_id", allValues : {"$push" : "$$ROOT"}}},
{$project : {"allValues" : 1, _id : 0} },
{$unwind : "$allValues" }
);
Output:-
{
"allValues" : {
"_id" : "John Snow",
"value" : {
"countTot" : 500,
"countCall" : 30,
"comment" : {
"text" : "this is a text",
"date" : ISODate("2016-11-25T10:46:49.258Z"),
"type" : "call"
}
}
}
}
Got my answer looking at this :
How to retrieve all matching elements present inside array in Mongo DB?
using the $addToSet property in the $group one.

Mongodb aggregate match array item with child array item

I would like to find documents that contains specific values in a child array.
This is an example document:
{
"_id" : ObjectId("52e9658e2a13df5be22cf7dc"),
"desc" : "Something somethingson",
"imageurl" : "http://",
"tags" : [
{
"y" : 29.3,
"brand" : "52d2cecd0bd1bd844d000018",
"brandname" : "Zara",
"type" : "Bow Tie",
"x" : 20,
"color" : "52d50c19f8f8ca8448000001",
"number" : 0,
"season" : 0,
"cloth" : "52d50d57f8f8ca8448000006"
},
{
"y" : 29.3,
"brand" : "52d2cecd0bd1bd844d000018",
"brandname" : "Zara",
"type" : "Bow Tie",
"x" : 20,
"color" : "52d50c19f8f8ca8448000001",
"number" : 0,
"season" : 0,
"cloth" : "52d50d57f8f8ca8448000006"
}
],
"user_id" : "52e953942a13df5be22cf7af",
"username" : "Thompson",
"created" : 1386710259971,
"occasion" : "ID",
"sex" : 0
}
The query I would like to do should look something like this:
db.posts.aggregate([
{$match: {tags.color:"52d50c19f8f8ca8448000001", tags.brand:"52d2cecd0bd1bd844d000018", occasion: "ID"}},
{$sort:{"created":-1}},
{$skip:0},
{$limit:10}
])
my problem is that I dont know how to match anything inside an array in the document like "tags". How can I do this?
You could try to do it without aggregation framework:
db.posts.find(
{
occasion: "ID",
tags: { $elemMatch: { color:"52d50c19f8f8ca8448000001", brand:"52d2cecd0bd1bd844d000018" } }
}
).sort({created: -1}).limit(10)
And if you want to use aggregation:
db.posts.aggregate([
{$match:
{
tags: { $elemMatch: { color:"52d50c19f8f8ca8448000001", brand: "52d2cecd0bd1bd844d000018" } },
occasion: "ID"
}
},
{$sort:{"created":-1}},
{$limit:10}
])

In MongoDb, how to apply sort internal fields present in document?

My document looks like this
{
field1: somevalue,
name:xtz
nested_documents: [ // array of nested document
{ x:"1", y:"2" }, // first nested document
{ x:"2", y:"3" }, // second nested document
{ x:"-1", y:"3" }, // second nested document
// ...many more nested documents
]
}
How one can sort the data present in nested_documents?
Expected answer is shown below:
nested_documents: [ { x:"-1", y:"3" },{ x:"1", y:"2" },{ x:"2", y:"3" }]
To do this you would have to use the aggregation framework
db.test.aggregate([{$unwind:'$nested_documents'},{$sort:{'nested_documents.x':
1}}])
this returns
"result" : [
{
"_id" : ObjectId("5139ba3dcd4e11c83f4cea12"),
"field1" : "somevalue",
"name" : "xtz",
"nested_documents" : {
"x" : "-1",
"y" : "3"
}
},
{
"_id" : ObjectId("5139ba3dcd4e11c83f4cea12"),
"field1" : "somevalue",
"name" : "xtz",
"nested_documents" : {
"x" : "1",
"y" : "2"
}
},
{
"_id" : ObjectId("5139ba3dcd4e11c83f4cea12"),
"field1" : "somevalue",
"name" : "xtz",
"nested_documents" : {
"x" : "2",
"y" : "3"
}
}
],
"ok" : 1
Hope this helps