I'm working in MongoDB and getting stuck at one aggregation case. Let me show you my collection.
First collection (data):
[
{
"_id": "8e7b3fa0-4230-448c-8f70-1d7300632834",
"data": [
{
"animal" : "7d44251a-b308-4deb-875a-33ef0a69fe2b",
"place": "Chennai"
},
{
"animal" : "fcfdd527-5885-48b0-a91f-03f72f78528f",
"place": "Kolkata"
}
]
}
]
Second collection (Animal):
[
{
"_id": "7d44251a-b308-4deb-875a-33ef0a69fe2b",
"name": "Dog"
},
{
"_id": "7d44251a-b308-4deb-875a-33ef0a69fe2b",
"name": "Cat"
}
]
I'm using this query:
db.data.aggregate([
{
"$lookup": {
"from": "animal",
"localField": "data.animal",
"foreignField": "_id",
"as": "doc"
}
},
{
"$unwind": "$doc"
},
{
"$project": {
"_id": 1,
"data.animal": "$doc.name",
"data.place": 1
}
}
])
and it result me this
[
{
"_id": "8e7b3fa0-4230-448c-8f70-1d7300632834",
"data": [
{
"animal": "Dog",
"place": "Chennai"
},
{
"animal": "Dog",
"place": "Kolkata"
}
]
},
{
"_id": "8e7b3fa0-4230-448c-8f70-1d7300632834",
"data": [
{
"animal": "Cat",
"place": "Chennai"
},
{
"animal": "Cat",
"place": "Kolkata"
}
]
}
]
Where I'm expecting like this
[
{
"_id": "8e7b3fa0-4230-448c-8f70-1d7300632834",
"data": [
{
"animal": "Dog",
"place": "Chennai"
},
{
"animal": "Cat",
"place": "Kolkata"
}
]
}
]
Mongo Playground
Also sharing this question in Mongo playgroud. Thanks in advance!!
Solution 1
$unset - Deconstruct the data array into multiple documents.
$lookup - Perform join with animal collection.
$project - Decorate the output document. For data.animal field, get the first value via $first.
$group - Group by _id. Push the data document into the data array.
db.data.aggregate([
{
"$unwind": "$data"
},
{
"$lookup": {
"from": "animal",
"localField": "data.animal",
"foreignField": "_id",
"as": "doc"
}
},
{
"$project": {
"_id": 1,
"data.animal": {
$first: "$doc.name"
},
"data.place": 1
}
},
{
$group: {
_id: "$_id",
data: {
$push: "$data"
}
}
}
])
Demo Solution 1 # Mongo Playground
Solution 2
$lookup
$set - Set data field.
2.1. $map - Iterate the data array and returns a new array.
2.1.1. $mergeObjects - Merge current iterated document with place field and the document from 2.1.1.1.
2.1.1.1. $first - Get the first document from the filtered doc arrays by matching the ids via $filter.
$unset - Remove _id and animals._id fields.
db.data.aggregate([
{
"$lookup": {
"from": "animal",
"localField": "data.animal",
"foreignField": "_id",
"as": "doc"
}
},
{
$set: {
data: {
$map: {
input: "$data",
as: "data",
in: {
$mergeObjects: [
{
place: "$$data.place"
},
{
$first: {
$filter: {
input: "$doc",
cond: {
$eq: [
"$$this._id",
"$$data.animal"
]
}
}
}
}
]
}
}
}
}
},
{
$unset: [
"doc",
"data._id"
]
}
])
Demo Solution 2 # Mongo Playground
Related
I have a collection of vehicles with the following car structure:
{
"_id": {}
brand : ""
model : ""
year : ""
suppliers : [
"name": "",
"contact": ""
"supplierId":"",
"orders":[], <-- Specific to the vehicles collection
"info":"" <-- Specific to the vehicles collection
]
}
And a Suppliers collection with a structure like:
{
"name":"",
"contact":"",
"_id":{}
"internalId":"",
"address":"",
...
}
I need to add a new field in the suppliers array within each document in the vehicles collection with the internalId field from the supplier in the suppliers collection that has the same _id.
if the supplier array has a document with the id 123, i should go to the suppliers collection and look for the supplier with the id 123 and retrieve the internalId. afterwards should create the field in the supplier array with that value.
So that i end up with the vehicles collection as:
{
"_id": {}
brand : ""
model : ""
year : ""
suppliers : [
"name": "",
"contact": ""
"supplierId":""
"internalId":"" <-- the new field
]
}
Tried:
db.vehicles.aggregate([
{
"$unwind": { "path": "$suppliers", "preserveNullAndEmptyArrays": false }
},
{
"$project": { "supplierObjId": { "$toObjectId": "$suppliers.supplierId" } }
},
{
"$lookup":
{
"from": "suppliers",
"localField": "supplierObjId",
"foreignField": "_id",
"as": "supplierInfo"
}
},{
"$set": {
"suppliers.internalId": "$supplierInfo.internalid"
}}
])
But it is adding the new field, to the returned values instead to the array item at the collection.
How can i achieve this?
But it is adding the new field, to the returned values instead to the array item at the collection.
The .aggregate method does not update documents, but it will just format the result documents,
You have to use 2 queries, first aggregate and second update,
I am not sure i guess you want to execute this query for one time, so i am suggesting a query you can execute in mongo shell,
Aggregation query:
$lookup with pipeline, pass suppliers.supplierId in let
$toString to convert object id to string type
$match the $in condition
$project to show required fields
$map to iterate loop of suppliers array
$reduce to iterate loop of suppliers_data array and find the matching record by supplierId
$mergeObjects to merge current object properties with new property internalId
Loop the result from aggregate query using forEach
Update Query to update suppliers array
db.vehicles.aggregate([
{
$lookup: {
from: "suppliers",
let: { supplierId: "$suppliers.supplierId" },
pipeline: [
{
$match: {
$expr: {
$in: [{ $toString: "$_id" }, "$$supplierId"]
}
}
},
{
$project: {
_id: 0,
supplierId: { $toString: "$_id" },
internalId: 1
}
}
],
as: "suppliers_data"
}
},
{
$project: {
suppliers: {
$map: {
input: "$suppliers",
as: "s",
in: {
$mergeObjects: [
"$$s",
{
internalId: {
$reduce: {
input: "$suppliers_data",
initialValue: "",
in: {
$cond: [
{ $eq: ["$$this.supplierId", "$$s.supplierId"] },
"$$this.internalId",
"$$value"
]
}
}
}
}
]
}
}
}
}
}
])
.forEach(function(doc) {
db.vehicles.updateOne({ _id: doc._id }, { $set: { suppliers: doc.suppliers } });
});
Playground for aggregation query, and Playground for update query.
It looks like one way to solve this is by using $addFields and $lookup. We first flatten any matching suppliers, then add the property, then regroup.
You can find a live demo here via Mongo Playground.
Database
Consider the following database structure:
[{
// Collection
"vehicles": [
{
"_id": "1",
brand: "ford",
model: "explorer",
year: "1999",
suppliers: [
{
name: "supplier1",
contact: "john doe",
supplierId: "001"
},
{
name: "supplier2",
contact: "jane doez",
supplierId: "002"
}
]
},
{
"_id": "2",
brand: "honda",
model: "accord",
year: "2002",
suppliers: [
{
name: "supplier1",
contact: "john doe",
supplierId: "001"
},
]
}
],
// Collection
"suppliers": [
{
"name": "supplier1",
"contact": "john doe",
"_id": "001",
"internalId": "999-001",
"address": "111 main street"
},
{
"name": "supplier2",
"contact": "jane doez",
"_id": "002",
"internalId": "999-002",
"address": "222 north street"
},
{
"name": "ignored_supplier",
"contact": "doesnt matter",
"_id": "xxxxxxx",
"internalId": "xxxxxxx",
"address": "0987 midtown"
}
]
}]
Query
This is the query that I was able to get working. I'm not sure how efficient it is, or if it can be improved, but this seemed to do the trick:
db.vehicles.aggregate([
{
$unwind: "$suppliers"
},
{
$lookup: {
from: "suppliers",
localField: "suppliers.supplierId",
foreignField: "_id", // <---- OR MATCH WHATEVER FIELD YOU WANT
as: "vehicle_suppliers"
}
},
{
$unwind: "$vehicle_suppliers"
},
{
$addFields: {
"suppliers.internalId": "$vehicle_suppliers.internalId"
}
},
{
$group: {
_id: "$_id",
brand: {
$first: "$brand"
},
model: {
$first: "$model"
},
year: {
$first: "$year"
},
suppliers: {
$push: "$suppliers"
}
}
}
])
Results
Which returns:
[
{
"_id": "2",
"brand": "honda",
"model": "accord",
"suppliers": [
{
"contact": "john doe",
"internalId": "999-001",
"name": "supplier1",
"supplierId": "001"
}
],
"year": "2002"
},
{
"_id": "1",
"brand": "ford",
"model": "explorer",
"suppliers": [
{
"contact": "john doe",
"internalId": "999-001",
"name": "supplier1",
"supplierId": "001"
},
{
"contact": "jane doez",
"internalId": "999-002",
"name": "supplier2",
"supplierId": "002"
}
],
"year": "1999"
}
]
I have an object like this:
{
"_id": {
"$oid": "5f0047f02fd3fc048aab9ee9"
},
"array": [
{
"_id": {
"$oid": "5f00dcc23e12b8721e4f3672"
},
"name": "NAME",
"sub_array": [
{
"sub_array2": [
{
"$oid": "5f00e367f7b8747beddc6d31"
},
{
"$oid": "5f00f26c1facd18c5158d1d3"
}
],
"_id": {
"$oid": "5f00de99a8802e767885e72b"
},
"week_day": 1
},
{
"sub_array2": [
{
"$oid": "5f00e367f7b8747beddc6d31"
}
],
"_id": {
"$oid": "5f00f2501facd18c5158d1d2"
},
"week_day": 3
}
]
},
{
"_id": {
"$oid": "5f00f2401facd18c5158d1d1"
},
"name": "NAME1",
"sub_array": []
}
]
}
I want to replace sub_array ids with objects from another collection but that results converting array and sub_array to objects and losing all of the data like week_day.
Lookup:
'$lookup': {
'from': 'sati',
'localField': 'array.sub_array.sub_array2',
'foreignField': '_id',
'as': 'array.sub_array.sub_array2'
}
Result:
{
"_id": {
"$oid": "5f0047f02fd3fc048aab9ee9"
},
"array": {
"sub_array": {
"sub_array2": [
{
"_id": {
"$oid": "5f00e367f7b8747beddc6d31"
},
"endTime": "2020-07-03T12:06:50+0000",
"startTime": "2020-07-03T12:05:50+0000",
"data1": {
"$oid": "5f005e63ab1cbf2374d5163f"
}
},
{
"_id": {
"$oid": "5f00e367f7b8747beddc6d31"
},
"endTime": "2020-07-03T12:06:50+0000",
"startTime": "2020-07-03T12:05:50+0000",
"data1": {
"$oid": "5f005e63ab1cbf2374d5163f"
}
},
{
"_id": {
"$oid": "5f00e367f7b8747beddc6d31"
},
"endTime": "2020-07-03T12:06:50+0000",
"startTime": "2020-07-03T12:05:50+0000",
"data1": {
"$oid": "5f005e63ab1cbf2374d5163f"
}
}
]
}
}
}
Is there a way to "replace" the individual ids without converting entire arrays to objects and removing other fields. I know mongoose can do that but I'm not permitted to use it. None of the other questions helped (example).
It will override entire object key:value with $lookup result. Instead, store the lookup result in the sati variable and add an extra stage like shown below.
$map allows use iterate over an array and transform each item.
db.collection.aggregate([
{
"$lookup": {
"from": "sati",
"localField": "array.sub_array.sub_array2",
"foreignField": "_id",
"as": "sati"
}
},
{
$project: {
array: {
$map: {
input: "$array",
as: "array",
in: {
_id: "$$array._id",
name: "$$array.name",
sub_array: {
$map: {
input: "$$array.sub_array",
as: "sub_array",
in: {
_id: "$$sub_array._id",
week_day: "$$sub_array.week_day",
sub_array2: {
$filter: {
input: "$sati",
as: "sati_item",
cond: {
$in: [
"$$sati_item._id",
"$$sub_array.sub_array2"
]
}
}
}
}
}
}
}
}
}
}
}
])
MongoPlayground | Altenative with $mergeObjects
I have two collections in the following format -
collection 1
{
"_id": "col1id1",
"name": "col1doc1",
"properties": [ "<_id1>", "<_id2>", "<_id3>"]
}
collection 2
{
"_id": "<_id1>",
"name": "doc1",
"boolean_field": false
}
{
"_id": "<_id2>",
"name": "doc2",
"boolean_field": true
}
{
"_id": "<_id3>",
"name": "doc3",
"boolean_field" : false
}
the desired output is -
{
"_id": "col1id1",
"name": "col1doc1",
"property_names": ["doc1", "doc3"]
}
The field proerties of document in collection1 has three IDs of documents in collection2 but the output after join operation should contain only those which have the boolean_field value as false. How can I perform this filter with join operation in MongoDB?
$lookup can be used along with $unwind to achieve this.
db.col1.aggregate([
{
"$unwind": "$properties"
},
{
"$lookup": {
from: "col2",
localField: "properties",
"foreignField": "_id",
"as": "property_names"
}
},
{
"$match": {
"property_names": {
"$elemMatch": {
"bool_field": false
}
}
}
},
{
"$unwind": "$property_names"
},
{
"$group": {
"_id": "$_id",
"properties": {
"$push": "$properties"
},
"property_names": {
"$push": "$property_names"
}
}
},
{
"$project": {
"_id": 1,
"name": 1,
"property_names": {
"name": 1
}
}
}
]);
I want to $lookup for a remote collection like SQL Join but with Mongo. And I don't want all of the keys from the remote document to be pulled to the origin collection - just some specific keys.
This is what I have tried:
[
{
$lookup: {
from: "tables",
localField: "type",
foreignField: "_id",
as: "type"
}
},
{
$unwind: "$type"
},
},
{
$project: {
"type.title": 1
}
}
]
However this prints only "type.title" and ignores all of other keys even from the origin document.
Is there any way to tell MongoDB to pull only specific fields from the remote collection?
You can use below aggregation with mongodb 3.6 and above
[
{ "$lookup": {
"from": "tables",
"let": { "type": "$type" },
"pipeline": [
{ "$addFields": { "owners": { "$cond": { "if": { "$ne": [ { "$type": "$owners" }, "array" ] }, "then": [], "else": "$owners" } } }},
{ "$match": { "$expr": { "$eq": ["$_id", "$$type"] }}},
{ "$project": { "title": 1 }}
],
"as": "type"
}},
{ "$unwind": "$type" }
]
I am trying to aggregate 2 collections in MongoDB based on a student's ID. One collection consists of student personal information, another one consists of the students logs. The issue is that the data is in array which is why I think my aggregation is not working. Any help will be appreciated.
student collection
{
"_id" : ObjectId("(Object ID here"),
"data" : [
{
"name" : "John",
"id" : 1
},
{
"name" : "Sandy",
"id" : 2
}
]
}
logs collection
{
"_id" : ObjectId("(Object ID here"),
"logs" : [
{
"studentId" : 1,
"activity" : "11112,334,123"
},
{
"studentId" : 2,
"activity" : "11112,334,123"
}
]
}
Here is what I have tried:
dbo.collection("student").aggregate([
{ "$lookup": {
"localField": "data.id",
"from": "logs",
"foreignField": "logs.studentId",
"as": "studentInfo"
}
}]).toArray(function(err, results) {
console.log(results);
});
Expected result:
studentinfo: {
id: 1,
name: "John",
activity" : "11112,334,123"
}
You can use below aggregation with mongodb 3.6
So basically your foreign field is an array you need to use $lookup with the pipeline to $unwind the foreign array inside the $lookup pipeline and to match the corresponding ids.
db.students.aggregate([
{ "$lookup": {
"from": "logs",
"let": { "dataId": "$data.id" },
"pipeline": [
{ "$unwind": "$logs" },
{ "$match": { "$expr": { "$in": ["$logs.studentId", "$$dataId"] }}},
{ "$replaceRoot": { "newRoot": "$logs" }}
],
"as": "students"
}}
])
or use this to merge both the arrays
db.students.aggregate([
{ "$lookup": {
"from": "logs",
"let": { "dataId": "$data.id" },
"pipeline": [
{ "$unwind": "$logs" },
{ "$match": { "$expr": { "$in": ["$logs.studentId", "$$dataId"] }}},
{ "$replaceRoot": { "newRoot": "$logs" }}
],
"as": "students"
}},
{ "$project": {
"students": {
"$map": {
"input": "$students",
"in": {
"studentId": "$$this.studentId",
"activity": "$$this.activity",
"name": { "$arrayElemAt": ["$data.name", { "$indexOfArray": ["$data.id", "$$this.studentId"] }]}
}
}
}
}}
])
Output
[
{
"students": [
{
"activity": "11112,334,123",
"name": "John",
"studentId": 1
},
{
"activity": "11112,334,123",
"name": "Sandy",
"studentId": 2
}
]
}
]