I have 2 collections, collection A has some documents like {'id':1,'field':'name'},{'id':1,'field':'age'},and collection B has some documents like
{'_id':1,'name':'alice','age':18,'phone':123},{'_id':2,'name':'bob','age':30,'phone':321}
and I want to find all the document whose '_id' is in collectionA, and just project the corresponding field.
for example:
collection A
{'id':1,'field':'name'},
{'id':1,'field':'age'}
collection B
{'_id':1,'name':'alice','age':18,'phone':123},
{'_id':2,'name':'bob','age':30,'phone':321}
the result is:
{'name':'alice','age':18},
I don't know if there is an easy way to do that?
You can use $lookup to join two collection
db.col1.aggregate([
{
$match: {
id: 1
}
},
{
"$lookup": {
"from": "col2",
"localField": "id",
"foreignField": "_id",
"as": "listNames"
}
},
{
$project: {
listNames: {
$first: "$listNames"
}
}
},
{
$project: {
_id: 0,
name: "$listNames.name",
age: "$listNames.age"
}
}
])
Mongo Playground: https://mongoplayground.net/p/E-0WvK_SUS_
So the idea is:
Convert the documents in to key, value pair for both the collections using $objectToArray.
Then perform a join operation based on key k and (id <-> _id) using $lookup.
Replace the result as root element using $replaceRoot.
Convert array to object using $arrayToObject and again $replaceRoot.
Query:
db.colB.aggregate([
{
$project: {
temp: { $objectToArray: "$$ROOT" }
}
},
{
$lookup: {
from: "colA",
let: { temp: "$temp", colB_id: "$_id" },
pipeline: [
{
$addFields: {
temp: { k: "$field", v: "$id" }
}
},
{
$match: {
$expr: {
$and: [
{ $in: ["$temp.k", "$$temp.k"] },
{ $eq: ["$temp.v", "$$colB_id"] }
]
}
}
},
{
$replaceRoot: {
newRoot: {
$first: {
$filter: {
input: "$$temp",
as: "item",
cond: { $eq: ["$field", "$$item.k"] }
}
}
}
}
}
],
as: "array"
}
},
{
$replaceRoot: {
newRoot: { $arrayToObject: "$array" }
}
}
]);
Output:
{
"name" : "alice",
"age" : 18
}
Related
I have the following data:
{
_id: "1"
transitions: [
{
"_id" : "11"
"name" : "Tr1"
"checkLists" : [
{ _id: "111", name: "N1"},
{ _id: "112", name: "N2"}
]
}
]
}
I used the following code to get the name N2 by query of _id:112
db.collection.findOne({ 'transitions.checkLists._id: new ObjectId("112") } }}, { 'transitions.checkLists.$': 1 })
but the result returns back both of them:
{ _id: ObjectId("1"),
transitions:
[ { checkLists:
[ { name: 'N1', _id: ObjectId("111") },
{ name: 'N2', _id: ObjectId("112") } ] } ] }
I would like to find and get only the name N2 by query of _id:112
Expected Result:
{ _id: ObjectId("1"),
transitions:
[ { checkLists:
[ { name: 'N2', _id: ObjectId("112") } ] } ] }
You can do it via the aggregation framework as follow:
db.collection.aggregate([
{
$match: {
"transitions.checkLists._id": "111"
}
},
{
"$addFields": {
"transitions": {
"$map": {
"input": "$transitions",
"as": "t",
"in": {
"$mergeObjects": [
"$$t",
{
"checkLists": {
"$filter": {
"input": "$$t.checkLists",
"as": "c",
"cond": {
$eq: [
"$$c._id",
"111"
]
}
}
}
}
]
}
}
}
}
},
{
"$addFields": {
transitions: {
$filter: {
input: "$transitions",
as: "elem",
cond: {
"$ne": [
"$$elem.checkLists",
[]
]
}
}
}
}
}
])
Explained:
Match the transitions.checkLists._id element in first stage.
Map/mergeobjects with filtered checklists to filter only the needed object from the transitions.checkLists array.
Remove the transitions elements where no checkList exists.
( this need to be done to remove elements for same document where there is no matching _id's )
Playground
I have a products collection with a schema as follows:
{
brand: String,
category: String,
title: String,
description: String,
product_variants: [...],
tags: [{label:String},{value:String}],
}
I am performing a lookup in the same collection to add a field consisting of related products for each product. I need to get related products by matching documents that have similar elements in the tags array. So far I have the got the following lookup pipeline:
{
$lookup: {
from: 'products',
let: { "tags": "$tags.label" },
pipeline: [{
$match: {'product_variants.status': {$eq: 'Active'}}
},
{
'$match': {
'$expr': {
'$in': ['$tags.label', '$$tags']
}
},
},
{
$match: { 'product_variants': {
$elemMatch: {
'variant_details': {
$elemMatch: {
'inventory': {
$elemMatch: {
quantity: {$gt:0},
}
}
}
}
}
}}
}, {
$project: {
product_variants: {
"$filter": {
"input": {
"$map": {
"input": "$product_variants",
"as": "variants",
"in": {
"variant_code": "$$variants.variant_code",
"images": {$slice: ["$$variants.images", 1]},
"slug": "$$variants.slug"
}
}
},
"as": "related_products",
"cond":{$gt: [{$size: "$$related_products.images"}, 0]}
}
}
}
}, { $limit: 3 } ],
"as": "related_products"
}
},
I have tried using $all operator but it is not working either.
I want to make an upsert call to update as well as insert my data in nested array of mongo db.
This is my mongo document.
{
"_id" : "575",
"_class" : "com.spyne.sharing.SpyneShareUserProject",
"spyneSharePhotoList" : [
{
"_id" : "fxLO68XyMR",
"spyneShareUsers" : [
{
"_id" : "chittaranjan#eventila.com",
"selectedByClient" : false
},
{
"_id" : "chittaranjan#gmail.com",
"selectedByClient" : false
}
]
},
{
"_id" : "nVpD0KoQAI",
"spyneShareUsers" : [
{
"_id" : "chittaranjan#eventila.com",
"selectedByClient" : true
}
]
},
{
"_id" : "Pm0B3Q9Igv",
"spyneShareUsers" : [
{
"_id" : "chittaranjan#gmail.com",
"selectedByClient" : true
}
]
}
]
}
Here my requirement is,
lets say i have an ID i.e. 575 (_id)
Then i will have the nested array ID i.e. fxLO68XyMR (spyneSharePhotoList._id)
Then i will have nested email id as ID i.e. chittaranjan#eventila.com (spyneSharePhotoList.spyneShareUsers._id) and selectedByClient (boolean)
Now i want is to check if this ID (spyneSharePhotoList.spyneShareUsers._id) is already present in the desired location i want to update the boolean value i.e. selectedByClient (true / false) according to that email id.
If the id is not present in the array, the it will make a new entry. as
{
"_id" : "chittaranjan#gmail.com",
"selectedByClient" : false
}
in spyneShareUsers list.
Please help me to do this task. Thank you
Most likely this is not the smartest solution, but it should work:
shareUserProject = {
id: "575",
PhotoListId: "fxLO68XyMR",
ShareUserId: "chittaranjan_new#eventila.com"
}
db.collection.aggregate([
{ $match: { _id: shareUserProject.id } },
{
$facet: {
root: [{ $match: {} }],
update: [
{ $unwind: "$spyneSharePhotoList" },
{ $match: { "spyneSharePhotoList._id": shareUserProject.PhotoListId } },
{
$set: {
"spyneSharePhotoList.spyneShareUsers": {
$concatArrays: [
{
$filter: {
input: "$spyneSharePhotoList.spyneShareUsers",
cond: { $ne: ["$$this._id", shareUserProject.ShareUserId] }
}
},
[{
_id: shareUserProject.ShareUserId,
selectedByClient: { $in: [shareUserProject.ShareUserId, "$spyneSharePhotoList.spyneShareUsers._id"] }
}]
]
}
}
}
]
}
},
{ $unwind: "$root" },
{ $unwind: "$update" },
{
$set: {
"root.spyneSharePhotoList": {
$concatArrays: [
["$update.spyneSharePhotoList"],
{
$filter: {
input: "$root.spyneSharePhotoList",
cond: { $ne: ["$$this._id", shareUserProject.PhotoListId] }
}
}
]
}
}
},
{ $replaceRoot: { newRoot: "$root" } }
]).forEach(function (doc) {
db.collection.replaceOne({ _id: doc._id }, doc);
})
I did not check whether all operators are available in MongoDB 3.5
My goal was to process everything in aggregation pipeline and run just a single replaceOne() at the end.
Here another solution based on $map operator:
db.collection.aggregate([
{ $match: { _id: shareUserProject.id } },
{
$set: {
spyneSharePhotoList: {
$map: {
input: "$spyneSharePhotoList",
as: "photoList",
in: {
$cond: {
if: { $eq: [ "$$photoList._id", shareUserProject.PhotoListId ] },
then: {
"_id": "$$photoList._id",
spyneShareUsers: {
$cond: {
if: { $in: [ shareUserProject.ShareUserId, "$$photoList.spyneShareUsers._id" ] },
then: {
$map: {
input: "$$photoList.spyneShareUsers",
as: "shareUsers",
in: {
$cond: {
if: { $eq: [ "$$shareUsers._id", shareUserProject.ShareUserId ] },
then: { _id: shareUserProject.ShareUserId, selectedByClient: true },
else: "$$shareUsers"
}
}
}
},
else: {
$concatArrays: [
"$$photoList.spyneShareUsers",
[ { _id: shareUserProject.ShareUserId, selectedByClient: false } ]
]
}
}
}
},
else: "$$photoList"
}
}
}
}
}
}
]).forEach(function (doc) {
db.collection.replaceOne({ _id: doc._id }, doc);
})
You can achieve the same result also with two updates:
shareUserProject = {
id: "575",
PhotoListId: "fxLO68XyMR_x",
ShareUserId: "chittaranjan_new#gmail.com"
}
ret = db.collection.updateOne(
{ _id: shareUserProject.id },
{ $pull: { "spyneSharePhotoList.$[photoList].spyneShareUsers": { _id: shareUserProject.ShareUserId } } },
{ arrayFilters: [{ "photoList._id": shareUserProject.PhotoListId }] }
)
db.collection.updateOne(
{ _id: shareUserProject.id },
{ $push: { "spyneSharePhotoList.$[photoList].spyneShareUsers": { _id: shareUserProject.ShareUserId, selectedByClient: ret.modifiedCount == 1 } } },
{ arrayFilters: [{ "photoList._id": shareUserProject.PhotoListId }] }
)
I am trying to get first date from inner array in mongodb object and add it to it's parent with aggregation. Example:
car: {
"model": "Astra",
"productions": [
"modelOne": {
"dateOfCreation": "2019-09-30T10:15:25.026+00:00",
"dateOfEstimation": "2017-09-30T10:15:25.026+00:00",
"someOnterInfo": "whatever"
},
"modelTwo": {
"dateOfCreation": "2017-09-30T10:15:25.026+00:00",
"dateOfEstimation": "2019-09-30T10:15:25.026+00:00",
"someOnterInfo": "whatever"
}
]
}
to be turned in
car: {
"model": "Astra",
"earliestDateOfEstimation": "2017-09-30T10:15:25.026+00:00",
"earliestDateOfCreation": "2017-09-30T10:15:25.026+00:00"
}
How can I achieve that?
I'm assuming that modelOne and modelTwo are unknown when you start your aggregation. The key step is to run $map along with $objectToArray in order to get rid of those two values. Then you can just use $min to get "earliest" values:
db.collection.aggregate([
{
$addFields: {
dates: {
$map: {
input: "$car.productions",
in: {
$let: {
vars: { model: { $arrayElemAt: [ { $objectToArray: "$$this" }, 0 ] } },
in: "$$model.v"
}
}
}
}
}
},
{
$project: {
_id: 1,
"car.model": 1,
"car.earliestDateOfEstimation": { $min: "$dates.dateOfEstimation" },
"car.earliestDateOfCreation": { $min: "$dates.dateOfCreation" },
}
}
])
Mongo Playground
EDIT:
First step can be simplified if there's always modelOne, 'modelTwo'... (fixed number)
db.collection.aggregate([
{
$addFields: {
dates: { $concatArrays: [ "$car.productions.modelOne", "$car.productions.modelTwo" ] }
}
},
{
$project: {
_id: 1,
"car.model": 1,
"car.earliestDateOfEstimation": { $min: "$dates.dateOfEstimation" },
"car.earliestDateOfCreation": { $min: "$dates.dateOfCreation" },
}
}
])
Mongo Playground (2)
I have changed one of the fields of my collection in mongoDB from an array of strings to an array of object containing 2 strings. New documents get inserted without any problem, but when a get method is called to get , querying all the documents I get this error:
Failed to decode 'Students'. Decoding 'photoAddresses' errored
with: readStartDocument can only be called when CurrentBSONType is
DOCUMENT, not when CurrentBSONType is STRING.
photoAddresses is the field that was changed in Students.
I was wondering is there any way to update all the records so they all have the same data type, without losing any data.
The old version of photoAdresses:
"photoAddresses" : ["something","something else"]
This should be updated to the new version like this:
"photoAddresses" : [{photoAddresses:"something"},{photoAddresses:"something else"}]
The following aggregation queries update the string array to object array, only if the array has string elements. The aggregation operator $map is used to map the string array elements to objects. You can use any of the two queries.
db.test.aggregate( [
{
$match: {
$expr: { $and: [ { $isArray: "$photo" },
{ $gt: [ { $size: "$photo" }, 0 ] }
]
},
"photo.0": { $type: "string" }
}
},
{
$project: {
photo: {
$map: {
input: "$photo",
as: "ph",
in: { addr: "$$ph" }
}
}
}
},
] ).forEach( doc => db.test.updateOne( { _id: doc._id }, { $set: { photo: doc.photo } } ) )
The following query works with MongoDB version 4.2+ only. Note the update operation is an aggregation instead of an update. See updateMany.
db.test.updateMany(
{
$expr: { $and: [ { $isArray: "$photo" },
{ $gt: [ { $size: "$photo" }, 0 ] }
]
},
"photo.0": { $type: "string" }
},
[
{
$set: {
photo: {
$map: {
input: "$photo",
as: "ph",
in: { addr: "$$ph" }
}
}
}
}
]
)
[EDIT ADD]: The following query works with version MongoDB 3.4:
db.test.aggregate( [
{
$addFields: {
matches: {
$cond: {
if: { $and: [
{ $isArray: "$photoAddresses" },
{ $gt: [ { $size: "$photoAddresses" }, 0 ] },
{ $eq: [ { $type: { $arrayElemAt: [ "$photoAddresses", 0 ] } }, "string" ] }
] },
then: true,
else: false
}
}
}
},
{
$match: { matches: true }
},
{
$project: {
photoAddresses: {
$map: {
input: "$photoAddresses",
as: "ph",
in: { photoAddresses: "$$ph" }
}
}
}
},
] ).forEach( doc => db.test.updateOne( { _id: doc._id }, { $set: { photoAddresses: doc.photoAddresses } } ) )