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 }] }
)
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 defined a model like this.
const ShotcountSchema = new Schema({
shotCountId : {
type : ObjectId,
required : true,
ref : 'member-info'
},
userId : {
type : String,
required : true,
unique : true
},
shot : [{
shotId : {
type : String,
required : true,
unique : true
},
clubType : {
type : String,
required : true
}
createdAt : {
type : Date,
default : Date.now
}
}]
});
If you perform a query to find subdocuments based on clubType as follows, only the results of the entire document are output.
For example, if I write the following code and check the result, I get the full result.
const shotCount = await ShotcountSchema.aggregate([
{
$match : { shotCountId : user[0]._id }
},
{
$match : { 'shot.clubType' : 'driver' }
}
]);
console.log(shotCount[0]); // Full result output
I would like to filter the subdocuments via clubType or createdAt to explore. So, I want these results to be printed.
{
_id: new ObjectId("61d67f0a74ec8620f34c57ed"),
shot: [
{
shotId: 'undefinedMKSf*Tf#!qHxWpz1hPzUBTz%',
clubType: 'driver',
shotCount: 20,
_id: new ObjectId("61d67f0a74ec8620f34c57ef"),
createdAt: 2022-01-06T05:32:58.391Z
}
]
}
How should I write the code?
db.collection.aggregate([
{
"$match": {
_id: ObjectId("61d67f0a74ec8620f34c57ed"),
"shot.clubType": "driver",
shot: {
$elemMatch: {
$and: [
{
"createdAt": {
$gte: ISODate("2022-01-07T05:32:58.391Z")
}
},
{
"createdAt": {
$lte: ISODate("2022-01-09T05:32:58.391Z")
}
}
]
}
}
}
},
{
"$set": {
shot: {
"$filter": {
"input": "$shot",
"as": "s",
"cond": {
$and: [
{
"$eq": [
"$$s.clubType",
"driver"
]
},
{
"$gte": [
"$$s.createdAt",
ISODate("2022-01-07T05:32:58.391Z")
]
},
{
"$lte": [
"$$s.createdAt",
ISODate("2022-01-09T05:32:58.391Z")
]
}
]
}
}
}
}
}
])
mongoplayground
I have 2 collections, collection A has some documents like {'id':1,'field':'name'},{'id':1,'field':'age'},and collection B has some documents like
{'_id':1,'name':'alice','age':18,'phone':123},{'_id':2,'name':'bob','age':30,'phone':321}
and I want to find all the document whose '_id' is in collectionA, and just project the corresponding field.
for example:
collection A
{'id':1,'field':'name'},
{'id':1,'field':'age'}
collection B
{'_id':1,'name':'alice','age':18,'phone':123},
{'_id':2,'name':'bob','age':30,'phone':321}
the result is:
{'name':'alice','age':18},
I don't know if there is an easy way to do that?
You can use $lookup to join two collection
db.col1.aggregate([
{
$match: {
id: 1
}
},
{
"$lookup": {
"from": "col2",
"localField": "id",
"foreignField": "_id",
"as": "listNames"
}
},
{
$project: {
listNames: {
$first: "$listNames"
}
}
},
{
$project: {
_id: 0,
name: "$listNames.name",
age: "$listNames.age"
}
}
])
Mongo Playground: https://mongoplayground.net/p/E-0WvK_SUS_
So the idea is:
Convert the documents in to key, value pair for both the collections using $objectToArray.
Then perform a join operation based on key k and (id <-> _id) using $lookup.
Replace the result as root element using $replaceRoot.
Convert array to object using $arrayToObject and again $replaceRoot.
Query:
db.colB.aggregate([
{
$project: {
temp: { $objectToArray: "$$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
}
Here is my Json in Mongo DB Compass. I am just querying greater than rating products from each collection.
Note: if I am doing with pageCount it is working fine because that is not inside a collection.
{PageCount:{gte:2}} -- works.
Problem with inner arrays collection of collection if anyone matches it displays all.
When we are doing the below query if anyone of the index have greater than 99 it shows all the values.
{"ProductField.ProductDetailFields.ProductDetailInfo.ProductScore.Rating": {$exists:true, $ne: null , $gte: 99}}
----- if I perform above query, I am getting this output.
How to iterate like foreach kind of things and check the condition in MongoDB querying
{
"_id":{
"$oid":"5fc73a7b3fb52d00166554b9"
},
"ProductField":{
"PageCount":2,
"ProductDetailFields":[
{
"PageNumber":1,
"ProductDetailInfo":[
{
"RowIndex":0,
"ProductScore":{
"Name":"Samsung",
"Rating":99
},
},
{
"RowIndex":1,
"ProductScore":{
"Name":"Nokia",
"Rating":96
},
},
{
"RowIndex":2,
"ProductScore":{
"Name":"Apple",
"Rating":80
},
}
]
}
]
}
},
{
"_id":{
"$oid":"5fc73a7b3fb52d0016655450"
},
"ProductField":{
"PageCount":2,
"ProductDetailFields":[
{
"PageNumber":1,
"ProductDetailInfo":[
{
"RowIndex":0,
"ProductScore":{
"Name":"Sony",
"Rating":93
}
},
{
"RowIndex":1,
"ProductScore":{
"Name":"OnePlus",
"Rating":93
}
},
{
"RowIndex":2,
"ProductScore":{
"Name":"BlackBerry",
"Rating":20
}
}
]
}
]
}
}
#Misky How to run this query execute:
While run this query in Mongo Shell - no sql client throws below error. we are using 3.4.9 https://www.nosqlclient.com/demo/
Is this somewhat close to your idea
db.collection.aggregate({
$addFields: {
"ProductField.ProductDetailFields": {
$map: {
"input": "$ProductField.ProductDetailFields",
as: "pdf",
in: {
$filter: {
input: {
$map: {
"input": "$$pdf.ProductDetailInfo",
as: "e",
in: {
$cond: [
{
$gte: [
"$$e.ProductScore.Rating",
99
]
},
{
$mergeObjects: [
"$$e",
{
PageNumber: "$$pdf.PageNumber"
}
]
},
null
]
}
}
},
as: "i",
cond: {
$ne: [
"$$i",
null
]
}
}
}
}
}
}
},
{
$addFields: {
"ProductField.ProductDetailFields": {
"$arrayElemAt": [
"$ProductField.ProductDetailFields",
0
]
}
}
})
LIVE VERSION
I have changed one of the fields of my collection in mongoDB from an array of strings to an array of object containing 2 strings. New documents get inserted without any problem, but when a get method is called to get , querying all the documents I get this error:
Failed to decode 'Students'. Decoding 'photoAddresses' errored
with: readStartDocument can only be called when CurrentBSONType is
DOCUMENT, not when CurrentBSONType is STRING.
photoAddresses is the field that was changed in Students.
I was wondering is there any way to update all the records so they all have the same data type, without losing any data.
The old version of photoAdresses:
"photoAddresses" : ["something","something else"]
This should be updated to the new version like this:
"photoAddresses" : [{photoAddresses:"something"},{photoAddresses:"something else"}]
The following aggregation queries update the string array to object array, only if the array has string elements. The aggregation operator $map is used to map the string array elements to objects. You can use any of the two queries.
db.test.aggregate( [
{
$match: {
$expr: { $and: [ { $isArray: "$photo" },
{ $gt: [ { $size: "$photo" }, 0 ] }
]
},
"photo.0": { $type: "string" }
}
},
{
$project: {
photo: {
$map: {
input: "$photo",
as: "ph",
in: { addr: "$$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 } } ) )