count based on nested key mongodb - mongodb

How can i count based on xTag key is on doc
I tried this but it does not provide me actual count
db.collection.find({
"products.xTag": {
$exists: false
}
}).count();
when you run with $exist:true i would expect result 1
When you run with $exist:false i would expect result 3
Playground: https://mongoplayground.net/p/_gf7RzGc8oB
Structure:
[
{
"item": 1,
"products": [
{
"name": "xyz",
"xTag": 32423
},
{
"name": "abc"
}
]
},
{
"item": 2,
"products": [
{
"name": "bob",
},
{
"name": "foo"
}
]
}
]

It is not possible with find(), You can use aggregate(),
$unwind deconstruct products array
$match your condition
$count total documents
db.collection.aggregate([
{ $unwind: "$products" },
{ $match: { "products.xTag": { $exists: false } } },
{ $count: "count" }
])
Playground

Related

MongoDB Aggregate Query to find the documents with missing values

I am having a huge collection of objects where the data is stored for different employees.
{
"employee": "Joe",
"areAllAttributesMatched": false,
"characteristics": [
{
"step": "A",
"name": "house",
"score": "1"
},
{
"step": "B",
"name": "car"
},
{
"step": "C",
"name": "job",
"score": "3"
}
]
}
There are cases where the score for an object is completely missing and I want to find out all these details from the database.
In order to do this, I have written the following query, but seems I am going wrong somewhere due to which it is not displaying the output.
I want the data in the following format for this query, so that it is easy to find out which employee is missing the score for which step and which name.
db.collection.aggregate([
{
"$unwind": "$characteristics"
},
{
"$match": {
"characteristics.score": {
"$exists": false
}
}
},
{
"$project": {
"employee": 1,
"name": "$characteristics.name",
"step": "$characteristics.step",
_id: 0
}
}
])
You need to use $exists to check the existence
playground
You can use $ifNull to handle both cases of 1. the score field is missing 2. score is null.
db.collection.aggregate([
{
"$unwind": "$characteristics"
},
{
"$match": {
$expr: {
$eq: [
{
"$ifNull": [
"$characteristics.score",
null
]
},
null
]
}
}
},
{
"$group": {
_id: null,
documents: {
$push: {
"employee": "$employee",
"name": "$characteristics.name",
"step": "$characteristics.step",
}
}
}
},
{
$project: {
_id: false
}
}
])
Here is the Mongo playground for your reference.

How to count embedded array object elements in mongoDB

{
"orderNo": "123",
"bags": [{
"type": "small",
"products": [{
"id": "1",
"name": "ABC",
"returnable": true
}, {
"id": "2",
"name": "XYZ"
}
]
},{
"type": "big",
"products": [{
"id": "3",
"name": "PQR",
"returnable": true
}, {
"id": "4",
"name": "UVW"
}
]
}
]
}
I have orders collection where documents are in this format. I want to get a total count of products which has the returnable flag. e.g: for the above order the count should be 2. I am very new to MongoDB wanted to know how to write a query to find this out, I have tried few things but did not help:
this is what I tried but not worked:
db.orders.aggregate([
{ "$unwind": "$bags" },
{ "$unwind": "$bags.products" },
{ "$unwind": "$bags.products.returnable" },
{ "$group": {
"_id": "$bags.products.returnable",
"count": { "$sum": 1 }
}}
])
For inner array you can use $filter to check returnable flag and $size to get number of such items. For the outer one you can take advantage of $reduce to sum the values from inner arrays:
db.collection.aggregate([
{
$project: {
totalReturnable: {
$reduce: {
input: "$bags",
initialValue: 0,
in: {
$add: [
"$$value",
{
$size: {
$filter: {
input: "$$this.products",
as: "prod",
cond: {
$eq: [ "$$prod.returnable", true ]
}
}
}
]
}
}
}
}
}
}
])
Mongo Playground

mongodb update multiple Array elements using db.update()

I compiled 2 update queries by referring to related stackoverflow answers, however, it doesn't seem to work, query updates all elements while only elements matching the criteria are expected to update.
Document:
[
{
"_id": 259,
"members": [
{
"email": "test1#gmail.com",
"added_by": "javapedia.net",
"status": "pending"
},
{
"email": "test2#gmail.com",
"added_by": "javapedia.net",
"status": "pending"
},
{
"email": "test3#gmail.com",
"status": "pending"
}
]
}
]
Query1: Using elemMatch operator, mongodb playground: https://mongoplayground.net/p/4cNgWJse86W
db.collection.update({
_id: 259,
"members": {
"$elemMatch": {
"email": {
"$in": [
"test3#gmail.com",
"test4#gmail.com"
]
}
}
}
},
{
"$set": {
"members.$[].status": "active"
}
},
{
"multi": true
})
Query2: using $in, mongodb playground : https://mongoplayground.net/p/tNu395B2RFx
db.collection.update({
_id: 259,
"members.email": {
"$in": [
"test3#gmail.com",
"test4#gmail.com"
]
}
},
{
"$set": {
"members.$[].status": "active"
}
},
{
"multi": true
})
Expected result: only one element with test3#gmail.com status should be updated to active.
Actual result: both queries update all records.
Is this what you're looking for?
db.collection.update({
_id: 259,
},
{
"$set": {
"members.$[el].status": "active"
}
},
{
arrayFilters: [
{
"el.email": {
$in: [
"test3#gmail.com",
"test4#gmail.com"
]
}
}
]
})
You can put the initial conditions back if needed, I just keep this short (and to me they make no sense).
multi:true isn't needed for one document
Maybe better semantically to use updateOne()

MongoDB: Assign document objects to field in '$project' stage

I have a user collection:
[
{"_id": 1,"name": "John", "age": 25, "valid_user": true}
{"_id": 2, "name": "Bob", "age": 40, "valid_user": false}
{"_id": 3, "name": "Jacob","age": 27,"valid_user": null}
{"_id": 4, "name": "Amelia","age": 29,"valid_user": true}
]
I run a '$facet' stage on this collection. Checkout this MongoPlayground.
I want to talk about the first output from the facet stage. The following is the response currently:
{
"user_by_valid_status": [
{
"_id": false,
"count": 1
},
{
"_id": true,
"count": 2
},
{
"_id": null,
"count": 1
}
]
}
However, I want to restructure the output in this way:
"analytics": {
"invalid_user": {
"_id": false
"count": 1
},
"valid_user": {
"_id": true
"count": 2
},
"user_with_unknown_status": {
"_id": null
"count": 1
}
}
The problem with using a '$project' stage along with 'arrayElemAt' is that the order may not be definite for me to associate an index with an attribute like 'valid_users' or others. Also, it gets further complicated because unlike the sample documents that I have shared, my collection may not always contain all the three categories of users.
Is there some way I can do this?
You can use $switch conditional operator,
$project to show value part in v with _id and count field as object, k to put $switch condition
db.collection.aggregate([
{
"$facet": {
"user_by_valid_status": [
{
"$group": {
"_id": "$valid_user",
"count": { "$sum": 1 }
}
},
{
$project: {
_id: 0,
v: { _id: "$_id", count: "$count" },
k: {
$switch: {
branches: [
{ case: { $eq: ["$_id", null] }, then: "user_with_unknown_status" },
{ case: { $eq: ["$_id", false] }, then: "invalid_user" },
{ case: { $eq: ["$_id", true] }, then: "valid_user" }
]
}
}
}
}
],
"users_above_30": [{ "$match": { "age": { "$gt": 30 } } }]
}
},
$project stage in root, convert user_by_valid_status array to object using $arrayToObject
{
$project: {
analytics: { $arrayToObject: "$user_by_valid_status" },
users_above_30: 1
}
}
])
Playground

Mongo db not in query by having two subset of documents from same collection

I am new to mongodb. Assume the following. There are 3 types of documents in one collection x, y and z.
docs = [{
"item_id": 1
"type": "x"
},
{
"item_id": 2
"type": "x"
},{
"item_id": 3
"type": "y",
"relavent_item_ids": [1, 2]
},
{
"item_id": 3
"type": "y",
"relavent_item_ids": [1, 2, 3]
},{
"item_id": 4
"type": "z",
}]
I want to get the following.
Ignore the documents with type z
Get all the documents of type x where it's item_id is not in relavent_item_ids of type y documents.
The result should have item_id field.
I tried doing match $in but this returns me all the records, I am unable to figure out how to have in condition with subset of documents of type y.
You can use below query
const item_ids = (await db.collection.find({ "type": "y" })).map(({ relavent_item_ids }) => relavent_item_ids)
const result = db.collection.find({
"item_id": { "$exists": true },
"type": { "$ne": "z", "$eq": "x" },
"relavent_item_ids": { "$nin": item_ids }
})
console.log({ result })
Ignore the documents with type z --> Use $ne not equal to query operator to filter out z types.
Get all the documents of type x where it's item_id is not in relavent_item_ids of type y documents --> Use $expr to match the same documents fields.
The result should have item_id field --> Use $exists query operator.
The solution:
db.test.aggregate( [
{
$facet: {
firstQuery: [
{
$match: { type: { $eq: "x", $ne: "z" } }
},
{
$project: {
item_id : 1, _id: 0
}
}
],
secondQuery: [
{
$match: { type: "y" }
},
{
$group: {
_id: null,
relavent: { $push: "$relavent_item_ids" }
}
},
{
$project: {
relavent: {
$reduce: {
input: "$relavent",
initialValue: [ ],
in: { $setUnion: [ "$$value", "$$this" ] }
}
}
}
}
]
}
},
{
$addFields: { secondQuery: { $arrayElemAt: [ "$secondQuery", 0 ] } }
},
{
$project: {
result: {
$filter: {
input: "$firstQuery" ,
as: "e",
cond: { $not: [ { $in: [ "$$e.item_id", "$secondQuery.relavent" ] } ] }
}
}
}
},
] )
Using the input documents in the question post and adding one more following document to the collection:
{
"item_id": 11,
"type": "x",
}
: only this document's item_id (value 11) will show in the output.
The aggregation uses a $facet to make two individual queries with a single pass. The first query gets all the "x" types (and ignores type "z") as an array. The second query gets an array of relavent_item_ids with unique values (from the documents of type "y"). The final, $project stage filters the first query result array with the condition:
Get all the documents of type x where it's item_id is not in
relavent_item_ids of type y documents
I am not sure if its an elegant solution.
db.getCollection('test').aggregate([
{
"$unwind": {
"path": "$relavent_item_ids",
"preserveNullAndEmptyArrays": true
}
},
{
"$group": {
"_id":null,
"relavent_item_ids": {"$addToSet":"$relavent_item_ids"},
"other_ids": {
"$addToSet":{
"$cond":[
{"$eq":["$type", "x"]},
"$item_id",
null
]
}
}
}
},
{
"$project":{
"includeIds": {"$setDifference":["$other_ids", "$relavent_item_ids"]}
}
},
{
"$unwind": "$includeIds"
},
{
"$match": {"includeIds":{"$ne":null}}
},
{
"$lookup":{
"from": "test",
"let": { "includeIds": "$includeIds"},
"pipeline": [
{ "$match":
{ "$expr":
{ "$and":
[
{ "$eq": [ "$item_id", "$$includeIds" ] },
{ "$eq": [ "$type", "x" ] }
]
}
}
}
],
"as": "result"
}
},
{
"$unwind": "$result"
},
])