db={
comments: [
{
"_id": ObjectId("5f364189f412c01fd01abab3"),
"content": "Comment 1",
"parent_comment_id": "",
"date": 1592461538923
},
{
"_id": ObjectId("5f364642f412c01fd01abeu4"),
"content": "Replied",
"parent_comment_id": "5f364189f412c01fd01abab3",
"date": 1592461538926
},
{
"_id": ObjectId("5f364642f412c01fd01abtx5"),
"content": "fresh comment",
"parent_comment_id": "",
"date": 1592461538929
}
]
}
How can I achieve self join in mongodb based on parent_comment_id.
is it possible in mongodb as like mysql ?
Using aggregation aggregate(),
$addFields for convert parent_comment_id to object if not empty, if its already an object id then skip this pipeline
db.comments.aggregate([
{
$addFields: {
parent_comment_id: {
$cond: {
if: { $eq: ["$parent_comment_id", ""] },
then: "$parent_comment_id",
else: { $toObjectId: "$parent_comment_id" }
}
}
}
},
$lookup to join with self collection, and use lookup with pipeline to match condition
$match parent_comment_id to _id
{
"$lookup": {
from: "comments",
le": { pid: "$parent_comment_id" },
as: "parentComment",
pipeline: [
{
$match: {
$expr: { $eq: ["$$pid", "$_id" ] }
}
}
]
}
},
$unwind to deconstruct parentComment because its an array and we need an object
preserveNullAndEmptyArrays to ignore empty parentComment array
{
$unwind: {
path: "$parentComment",
preserveNullAndEmptyArrays: true
}
}
])
Playground
Related
I have a structure where I want to match the value of a field on root level with the value of a field inside another object in the same document, I got to his structure by unwinding on the nested field. So I have a structure like this:
{
"name": "somename",
"level": "123",
"nested":[
{
"somefield": "test",
"file": {
level:"123"
}
},
{
"somefield": "test2",
"file": {
level:"124"
}
}
]
}
After unwinding I got the structure like:
{
"name": "somename",
"level": "123",
"nested": {
"somefield": "test",
"file": {
level:"123"
}
}
}
So I want to match on level = nested.file.level and return only documents which satisfy this condition.
I tried using
$match: {
"nested.file.level": '$level'
}
also
$project: {
nested: {
$cond: [{
$eq: [
'nested.file.level',
'$level'
]
},
'$nested',
null
]
}
}
Nothing seems to work. Any idea on how I can match based on the mentioned criteria?
Solution 1: With $unwind stage
After $unwind stage, in the $match stage you need to use the $expr operator.
{
$match: {
$expr: {
$eq: [
"$nested.file.level",
"$level"
]
}
}
}
Demo Solution 1 # Mongo Playground
Solution 2: Without $unwind stage
Without $unwind stage, you may work with $filter operator.
db.collection.aggregate([
{
$match: {
$expr: {
$in: [
"$level",
"$nested.file.level"
]
}
}
},
{
$project: {
nested: {
$filter: {
input: "$nested",
cond: {
$eq: [
"$$this.file.level",
"$level"
]
}
}
}
}
}
])
Demo Solution 2 # Mongo Playground
I have this simplified MongoDB document and would like to change something because there is quite a lot of redundant data. This field "activeUsersLookup" is the result of aggregation which returns data I'd like to put inside the first users array.
First id:
"_id": "80b1565a-faf4-4e68-9bd6-8344060e8d3a" matches
id from activeUsersLookup the same story is with user IDs.
[{
"_id": "80b1565a-faf4-4e68-9bd6-8344060e8d3a",
"users": [
{
"_id": "eaa946da-2708-443e-ab4c-b6db357050ca",
"lastactive": {
"$date": {
"$numberLong": "1637922656000"
}
}
},
{
"_id": "4972ba13-6f4e-4943-be07-15802e22e0dd",
"lastactive": {
"$date": {
"$numberLong": "1653286066000"
}
}
},
{
"_id": "6c4a62ce-c6c6-430f-a0cd-d348ec77dbb2",
"lastactive": {
"$date": {
"$numberLong": "1558623982000"
}
}
}
],
"activeUsersLookup": [
{
"_id": "80b1565a-faf4-4e68-9bd6-8344060e8d3a",
"users": [
{
"_id": "eaa946da-2708-443e-ab4c-b6db357050ca",
"activities": 2
},
{
"_id": "6c4a62ce-c6c6-430f-a0cd-d348ec77dbb2",
"activities": 1
}
],
"sumOfActivities": 3
}
]
}]
So more or less the final document should look like this:
[{
"_id": "80b1565a-faf4-4e68-9bd6-8344060e8d3a",
"users": [
{
"_id": "eaa946da-2708-443e-ab4c-b6db357050ca",
"lastactive": {
"$date": {
"$numberLong": "1637922656000"
}
},
"activities": 2
},
{
"_id": "4972ba13-6f4e-4943-be07-15802e22e0dd",
"lastactive": {
"$date": {
"$numberLong": "1653286066000"
}
},
"activities": 0
},
{
"_id": "6c4a62ce-c6c6-430f-a0cd-d348ec77dbb2",
"lastactive": {
"$date": {
"$numberLong": "1558623982000"
}
},
"activities": 1
},
"sumOfActivities": 3
]
}]
I've tried with:
{
$addFields: {
'licenses.activities': '$activeUsersLookup.users.activities'
}
}
But this gives me an empty array so I must be doing something wrong.
The next stage would be to sum all those activities as sumOfActivities and the last stage would be unset activeUsersLookup.
What magic tricks must I do to have the needed result? :)
I don't think the expected result you posted for the "sumOfActivities": 3 in the users array is valid.
Assume that you are trying to achieve the result as below:
[{
"_id": "80b1565a-faf4-4e68-9bd6-8344060e8d3a",
"users": [...],
"sumOfActivities": 3
}]
The query is a bit long:
$set - Set activeUsersLookup field as object.
1.1. $first - Get the first document from 1.2.
1.2. $filter - Filter document(s) from activeUsersLookup by matching _id for the document in activeUsersLookup with _id (root document).
$set
2.1. - Set users array.
2.1.1. $map - Iterate the documents in users array and return a new array.
2.1.2. $mergeObjects - Merge current documents with the documents with activities field.
2.1.3. $ifNull - Set activities as 0 if no result returned from 2.1.4.
2.1.4. $getField - Get the activities field from the result 2.1.5.
2.1.5. $first - Get the first document from the result 2.1.6.
2.1.6. $filter - Filter the activeUsersLookup.users documents by matching _id for the document (users array) with _id for the current document.
2.2. Set sumOfActivities field.
$unset - Remove activeUsersLookup field.
db.collection.aggregate([
{
$set: {
activeUsersLookup: {
$first: {
$filter: {
input: "$activeUsersLookup",
cond: {
$eq: [
"$$this._id",
"$_id"
]
}
}
}
}
}
},
{
$set: {
users: {
$map: {
input: "$users",
as: "user",
in: {
$mergeObjects: [
"$$user",
{
activities: {
"$ifNull": [
{
"$getField": {
"field": "activities",
"input": {
$first: {
$filter: {
input: "$activeUsersLookup.users",
cond: {
$eq: [
"$$this._id",
"$$user._id"
]
}
}
}
}
}
},
0
]
}
}
]
}
}
},
sumOfActivities: "$activeUsersLookup.sumOfActivities"
}
},
{
$unset: "activeUsersLookup"
}
])
Sample Mongo Playground
I have two collections in MongoDB, items and categories.
items is
{
_id: "some_id",
category_A: "foo",
category_B: "bar",
}
and categories is
{
_id: "foo_id",
name: "foo",
type: "A"
},
{
_id: "bar_id",
name: "bar",
type: "B"
}
I'm trying to use a pipeline to get foo_id and bar_id by using $lookup, but I don't understand why the category_A_out array always returns empty.
Here is the relevant step of the pipeline for category_A:
{
from: 'categories',
"let": {
"category": "$name",
"type": "$type"
},
"pipeline": [{
"$match": {
$expr: {
$and: [
{ $eq: ["$category_A", "$$category"] },
{ $eq: ["$$type", "A"] }
]
}
}
}],
as: 'category_A_out'
}
I am sure that foo and bar exist in the categories collection.
What am I doing wrong?
let should use for declaring the variable for LEFT collection which is items.
If category_A holds the categories' name, you need match with name.
Else match with _id.
db.items.aggregate([
{
$lookup: {
from: "categories",
"let": {
"category_A": "$category_A"
},
"pipeline": [
{
"$match": {
$expr: {
$and: [
{
$eq: [
"$name", // Or Match with $_id if category_A holds id
"$$category_A"
]
},
{
$eq: [
"$type",
"A"
]
}
]
}
}
}
],
as: "category_A_out"
}
}
])
Sample Mongo Playground
Let's say I have these two collections:
// Members:
{
"_id":{
"$oid":"60dca71f0394f430c8ca296d"
},
"church":"60dbb265a75a610d90b45c6b",
"name":"Julio Verne Cerqueira"
},
{
"_id":{
"$oid":"60dca71f0394f430c8ca29a8"
},
"nome":"Ryan Steel Oliveira",
"church":"60dbb265a75a610d90b45c6c"
}
And
// Churches
{
"_id": {
"$oid": "60dbb265a75a610d90b45c6c"
},
"name": "Saint Antoine Hill",
"active": true
},
{
"_id": {
"$oid": "60dbb265a75a610d90b45c6b"
},
"name": "Jackeline Hill",
"active": true
}
And I want to query it and have a result like this:
// Member with Church names
{
"_id":{
"$oid":"60dca71f0394f430c8ca296d"
},
"church":"Jackeline Hill",
"name":"Julio Verne Cerqueira"
},
{
"_id":{
"$oid":"60dca71f0394f430c8ca29a8"
},
"church":"Saint Antoine Hill",
"nome":"Ryan Steel Oliveira"
}
If I try a Lookup, I have the following Result: (It is getting the entire churches collection).
How would I do the query, so it gives me only the one church that member is related to?
And, if possible, how to Sort the result in alphabetical order by church then by name?
Obs.: MongoDB Version: 4.4.10
There is matching error in the $lookup --> $pipeline --> $match.
It should be:
$match: {
$expr: {
$eq: [
"$_id",
"$$searchId"
]
}
}
From the provided documents, members to churchies relationship will be 1 to many. Hence, when you join members with churchies via $lookup, the output church will be an array with only one churchies document.
Aggregation pipelines:
$lookup - Join members collection (by $$searchId) with churchies (by _id).
$unwind - Deconstruct church array field to multiple documents.
$project - Decorate output document.
$sort - Sort by church and name ascending.
db.members.aggregate([
{
"$lookup": {
"from": "churchies",
"let": {
searchId: {
"$toObjectId": "$church"
}
},
"pipeline": [
{
$match: {
$expr: {
$eq: [
"$_id",
"$$searchId"
]
}
}
},
{
$project: {
name: 1
}
}
],
"as": "church"
}
},
{
"$unwind": "$church"
},
{
$project: {
_id: 1,
church: "$church.name",
name: 1
}
},
{
"$sort": {
"church": 1,
"name": 1
}
}
])
Sample Mongo Playground
I'm having hard time getting $lookup with a pipeline to work in MongoDB Compass.
I have the following collections:
Toys
Data
[
{
"_id": {
"$oid": "5d233c3bb173a546386c59bb"
},
"type": "multiple",
"tags": [
""
],
"searchFields": [
"Jungle Stampers - Two",
""
],
"items": [
{
"$oid": "5d233c3cb173a546386c59bd"
},
{
"$oid": "5d233c3cb173a546386c59be"
},
{
"$oid": "5d233c3cb173a546386c59bf"
},
{
"$oid": "5d233c3cb173a546386c59c0"
},
{
"$oid": "5d233c3cb173a546386c59c1"
},
{
"$oid": "5d233c3cb173a546386c59c2"
},
{
"$oid": "5d233c3cb173a546386c59c3"
},
{
"$oid": "5d233c3cb173a546386c59c4"
}
],
"name": "Jungle Stampers - Two",
"description": "",
"status": "active",
"category": {
"$oid": "5cfe727cac920000086b880e"
},
"subCategory": "Stamp Sets",
"make": "",
"defaultCharge": null,
"defaultOverdue": null,
"sizeCategory": {
"$oid": "5d0cfde57561e107c88fbde3"
},
"ageFrom": {
"$numberInt": "24"
},
"ageTo": {
"$numberInt": "120"
},
"images": [
{
"_id": {
"$oid": "5d233c3bb173a546386c59bc"
},
"id": {
"$oid": "5d233c39b173a546386c59ba"
},
"url": "/toyimages/5d233c39b173a546386c59ba.jpg",
"thumbUrl": "/toyimages/thumbs/tn_5d233c39b173a546386c59ba.jpg"
}
],
"__v": {
"$numberInt": "2"
}
}
]
Loans
Data
[
{
"_id": {
"$oid": "5e1f1661b712215978c746d9"
},
"tags": [],
"member": {
"$oid": "5e17495e4f81ab3f900dbb63"
},
"source": "admin portal - potter1#gmail.com",
"items": [
{
"id": {
"$oid": "5e1f160eb712215978c746d5"
},
"status": "new",
"_id": {
"$oid": "5e1f1661b712215978c746db"
},
"toy": {
"$oid": "5d233c3bb173a546386c59bb"
},
"cost": {
"$numberInt": "0"
}
},
{
"id": {
"$oid": "5e1f160eb712215978c746d5"
},
"status": "new",
"_id": {
"$oid": "5e1f1661b712215978c746da"
},
"toy": {
"$oid": "5d233b1ab173a546386c59b5"
},
"cost": {
"$numberInt": "0"
}
}
],
"dateEntered": {
"$date": {
"$numberLong": "1579095632870"
}
},
"dateDue": {
"$date": {
"$numberLong": "1579651200000"
}
},
"__v": {
"$numberInt": "0"
}
}
]
I am trying to return a list of toys and their associated loans that have a status of 'new' or 'out'.
I can use the following $lookup aggregate to fetch all loans:
{
from: 'loans',
localField: '_id',
foreignField: 'items.toy',
as: 'loansSimple'
}
However I am trying to use a pipeline to load loans that have the two statuses I am interested in, but it always only returns zero documents:
{
from: 'loans',
let: {
'toyid': '$_id'
},
pipeline: [
{
$match: {
$expr: {
$and: [
{$eq: ['$items.toy', '$$toyid']},
{$eq: ['$items.status', 'new']} // changed from $in to $eq for simplicity
]
}
}
}
],
as: 'loans'
}
This always seems to return 0 documents, however I arrange it:
Have I made a mistake somewhere?
I'm using MongoDB Atlas, v4.2.2, MongoDB Compass v 1.20.4
You are trying to search $$toyid inside inner array, but Operator Expression $eq cannot resolve it.
Best solution: $let (returns filtered loans by criteria) + $filter (applies filter for inner array) operator helps us to get desired result.
db.toys.aggregate([
{
$lookup: {
from: "loans",
let: {
"toyid": "$_id",
"toystatus": "new"
},
pipeline: [
{
$match: {
$expr: {
$gt: [
{
$size: {
$let: {
vars: {
item: {
$filter: {
input: "$items",
as: "tmp",
cond: {
$and: [
{
$eq: [
"$$tmp.toy",
"$$toyid"
]
},
{
$eq: [
"$$tmp.status",
"$$toystatus"
]
}
]
}
}
}
},
in: "$$item"
}
}
},
0
]
}
}
}
],
as: "loans"
}
}
])
MongoPlayground
Alternative solution 1. Use $unwind to flatten items attribute. (We create extra field named tmp which stores items value, flatten it with $unwind operator, match as you were doing and then exclude from result)
db.toys.aggregate([
{
$lookup: {
from: "loans",
let: {
"toyid": "$_id"
},
pipeline: [
{
$addFields: {
tmp: "$items"
}
},
{
$unwind: "$tmp"
},
{
$match: {
$expr: {
$and: [
{
$eq: [
"$tmp.toy",
"$$toyid"
]
},
{
$eq: [
"$tmp.status",
"new"
]
}
]
}
}
},
{
$project: {
tmp: 0
}
}
],
as: "loans"
}
}
])
MongoPlayground
Alternative solution 2. We use $reduce to create toy's array and with $in operator we check if toyid exists inside this array.
db.toys.aggregate([
{
$lookup: {
from: "loans",
let: {
"toyid": "$_id"
},
pipeline: [
{
$addFields: {
toys: {
$reduce: {
input: "$items",
initialValue: [],
in: {
$concatArrays: [
"$$value",
[
"$$this.toy"
]
]
}
}
}
}
},
{
$match: {
$expr: {
$in: [
"$$toyid",
"$toys"
]
}
}
},
{
$project: {
toys: 0
}
}
],
as: "loans"
}
}
])
$expr receives aggregation expressions, At that point $$items.toy is parsed for each element in an array as you would expect (however if it would it will still give you "bad" results as you'll get loans that have the required toy id and any other item with status new in their items array).
So you have two options to work around this:
If you don't care about the other items in the lookup'd document you can add an $unwind stage at the start of the lookup pipeline like so:
{
from: 'loans',
let: {
'toyid': '$_id'
},
pipeline: [
{
$unwind: "$items"
},
{
$match: {
$expr: {
$and: [
{$eq: ['$items.toy', '$$toyid']},
{$eq: ['$items.status', 'new']} // changed from $in to $eq for simplicity
]
}
}
}
],
as: 'loans'
}
If you do care about them just iterate the array in one of the possible ways to get a 'correct' match, here is an example using $filter
{
from: 'loads',
let: {
'toyid': '$_id'
},
pipeline: [
{
$addFields: {
temp: {
$filter: {
input: "$items",
as: "item",
cond: {
$and: [
{$eq: ["$$item.toy", "$$toyid"]},
{$eq: ["$$item.status", "new"]}
]
}
}
}
}
}, {$match: {"temp.0": {exists: true}}}
],
as: 'loans'
}