let data = [
{
"_id": '101',
"name": 'category_1',
"subcategory": [
{
"_id": '201',
"name": 'subCategory_1'
},
{
"_id": '202',
"name": 'subCategory_2',
"subsubcategory": [
{
"_id": '301',
"name": 'subsubcategory_1'
},
{
"_id": '302',
"name": 'subsubcategory_2'
}
]
}
]
}
]
How can I change subsubcategory name ?
Related
I want to add value in array of the following json structure in mongo db collection "Scdtls".
I need to add value only where "Type": "Fees" and "IsCurrentVersion": true.
{
"_id": ObjectId("60e71243b484cf3ec22a6845"),
"Item": "School",
"Text": "School Details",
"Types": [
{
"Type": "Library",
"Values": [
{
"IsCurrentVersion": false,
"KeyWords": [
{
"_id": ObjectId("611a4f113800d6af3fc4814f"),
"Value": "Physics"
}
]
}
]
},
{
"Type": "Fees",
"Values": [
{
"IsCurrentVersion": false,
"KeyWords": [
{
"_id": ObjectId("611a4f113800d6af3fc4814f"),
"Value": "Admission"
},
{
"_id": ObjectId("611a4f113800d6af3fc4814k"),
"Value": "Canteen"
}
]
},
{
"IsCurrentVersion": true,
"KeyWords": [
{
"_id": ObjectId("611a4f113800d6af3fc4814g"),
"Value": "Tution"
}
]
}
]
}
]
}
This is how I am trying
db.Scdtls.update({
"Item": "School",
"Types.Type": "Fees",
"Types.Values.IsCurrentVersion": true
},
{
"$push": {
"Types.1.Values.$[].KeyWords": {
"_id": ObjectId(),
"Value": "Sports"
}
}
})
But it is also adding "Value": "Sports" in "Type" : "Fees" where "IsCurrentVersion": false.
Not able to understand the reason.
If I understand correctly, you can do the update you want using "arrayFilters", like this:
db.Scdtls.update({
"Item": "School",
"Types.Type": "Fees",
"Types.Values.IsCurrentVersion": true
},
{
"$push": {
"Types.$[x].Values.$[y].KeyWords": {
"_id": ObjectId("deadbeafcafebabec0deface"),
"Value": "Sports"
}
}
},
{
"arrayFilters": [
{ "x.Type": "Fees" },
{ "y.IsCurrentVersion": true }
]
})
Try it on mongoplayground.net.
I need to run a query that joins documents from two collections, I wrote an aggregation query but it takes too much time when running in the production database with many documents. Is there any way to write this query in a more efficient way?
Query in Mongo playground: https://mongoplayground.net/p/dLb3hsJHNYt
There are two collections users and activities. I need to run a query to get some users (from users collection), and also their last activity (from activities collection).
Database:
db={
"users": [
{
"_id": 1,
"email": "user1#gmail.com",
"username": "user1",
"country": "BR",
"creation_date": 1646873628
},
{
"_id": 2,
"email": "user2#gmail.com",
"username": "user2",
"country": "US",
"creation_date": 1646006402
}
],
"activities": [
{
"_id": 1,
"email": "user1#gmail.com",
"activity": "like",
"timestamp": 1647564787
},
{
"_id": 2,
"email": "user1#gmail.com",
"activity": "comment",
"timestamp": 1647564834
},
{
"_id": 3,
"email": "user2#gmail.com",
"activity": "like",
"timestamp": 1647564831
}
]
}
Inefficient Query:
db.users.aggregate([
{
// Get users using some filters
"$match": {
"$expr": {
"$and": [
{ "$not": { "$in": [ "$country", [ "AR", "CA" ] ] } },
{ "$gte": [ "$creation_date", 1646006400 ] },
{ "$lte": [ "$creation_date", 1648684800 ] }
]
}
}
},
{
// Get the last activity within the time range
"$lookup": {
"from": "activities",
"as": "last_activity",
"let": { "cur_email": "$email" },
"pipeline": [
{
"$match": {
"$expr": {
"$and": [
{ "$eq": [ "$email", "$$cur_email" ] },
{ "$gte": [ "$timestamp", 1647564787 ] },
{ "$lte": [ "$timestamp", 1647564834 ] }
]
}
}
},
{ "$sort": { "timestamp": -1 } },
{ "$limit": 1 }
]
}
},
{
// Remove users with no activity
"$match": {
"$expr": {
"$gt": [ { "$size": "$last_activity" }, 0 ] }
}
}
])
Result:
[
{
"_id": 1,
"country": "BR",
"creation_date": 1.646873628e+09,
"email": "user1#gmail.com",
"last_activity": [
{
"_id": 2,
"activity": "comment",
"email": "user1#gmail.com",
"timestamp": 1.647564788e+09
}
],
"username": "user1"
},
{
"_id": 2,
"country": "US",
"creation_date": 1.646006402e+09,
"email": "user2#gmail.com",
"last_activity": [
{
"_id": 3,
"activity": "like",
"email": "user2#gmail.com",
"timestamp": 1.647564831e+09
}
],
"username": "user2"
}
]
I'm more familiar with relational databases, so I'm struggling a little to run this query efficiently.
Thanks!
Let's say I have a Customer document like the following
db.collection.insertOne( {
"customerName": "John Doe",
"orders": [
{
"type": "regular",
"items": [
{
"name": "itemA",
"price": 11.1
},
{
"name": "itemB",
"price": 22.2
}
]
},
{
"type": "express",
"items": [
{
"name": "itemC",
"price": 33.3
},
{
"name": "itemD",
"price": 44.4
}
]
}
]
})
How can I calculate the total price of all orders (111 in this example)?
You can $unwind twice (because nested array) and group using $sum like this:
db.collection.aggregate([
{
"$unwind": "$orders"
},
{
"$unwind": "$orders.items"
},
{
"$group": {
"_id": "$customerName",
"total": {
"$sum": "$orders.items.price"
}
}
}
])
Example here
I have document as shown
[
{
"Users": [
{
"Name": "Kartikey Vaish",
"_id": "1",
},
{
"Name": "Witcher Proxima",
"_id": "2",
}
],
"_id": "12",
},
{
"Users": [
{
"Name": "Witcher Proxima",
"_id": "2",
},
{
"Name": "Saga",
"_id": "4",
}
],
"_id": "13",
}
]
I want to search for those documents whose Users array has that particular ID
For Example if
ID == 1 // should return
[
{
"Users": [
{
"Name": "Kartikey Vaish",
"_id": "1",
},
{
"Name": "Witcher Proxima",
"_id": "2",
}
],
"_id": "12",
}
]
ID == 2 // should return
[
{
"Users": [
{
"Name": "Kartikey Vaish",
"_id": "1",
},
{
"Name": "Witcher Proxima",
"_id": "2",
}
],
"_id": "12",
},
{
"Users": [
{
"Name": "Witcher Proxima",
"_id": "2",
},
{
"Name": "Saga",
"_id": "4",
}
],
"_id": "13",
}
]
ID == 4 // should return
[
{
"Users": [
{
"Name": "Kartikey Vaish",
"_id": "1",
},
{
"Name": "Saga",
"_id": "4",
}
],
"_id": "13",
}
]
As you can see from above my query should return only those objects whose "Users" array contains an object with given ID. I tried this but it doesn't work.
const chats = await Chats.find({
Users: { $elemMatch: { _id: "1" } },
});
// this returns an empty array
const chats = await Chats.find({
Users: { $elemMatch: { Name: "Kartikey Vaish" } },
});
// this returns
[
{
"Users": [
{
"Name": "Kartikey Vaish",
"_id": "1",
},
{
"Name": "Witcher Proxima",
"_id": "2",
}
],
"_id": "12",
}
]
What am I doing wrong here?
Is it something related to _id paramter?
EDIT:
My Chats Schema looks like this -
const Chats = mongoose.model(
"Chats",
new mongoose.Schema({
Users: {
type: Array,
required: true,
default: [],
},
})
);
Update your schema as shown below
const Chats = mongoose.model(
"Chats",
new mongoose.Schema({
Users: [{
_id: {
type: String,
required: true, // Include only if needed!
unique: true // Include only if needed!
},
Name: {
type: String,
index: true // Include only if needed!
}
}]
})
);
If you do not explicitly mention _id MongoDB will create _id field as ObjectId.
I have users indexed with categories as follows
{
id: 1
name: John
categories: [
{
id: 1
name: Category 1
},
{
id: 2
name: Category 2
}
]
},
{
id: 2
name: Mark
categories: [
{
id: 1
name: Category 1
}
]
}
And I'm trying to get all the documents with Category 1 or Category 2 with
{
filter:
{
bool: {
must: [
{
terms: {user.categories.id: [1, 2]}
}
]
}
}
}
But It only returns the first document that has the two categories, what I am doing wrong?
As I understood, terms search that one of the values is contained in the field, so for user 1
user.categories.id: [1, 2]
user 2
user.categories.id: [1]
Categoy id 1 is contained in both documents
The best way to handle this is probably with a nested filter. You'll have to specify the "nested" type in your mapping, though.
I can set up an index like this:
PUT /test_index
{
"settings": {
"number_of_shards": 1,
"number_of_replicas": 0
},
"mappings": {
"doc": {
"properties": {
"categories": {
"type": "nested",
"properties": {
"id": {
"type": "long"
},
"name": {
"type": "string"
}
}
},
"id": {
"type": "long"
},
"name": {
"type": "string"
}
}
}
}
}
then add some docs:
PUT /test_index/doc/1
{
"id": 1,
"name": "John",
"categories": [
{ "id": 1, "name": "Category 1" },
{ "id": 2, "name": "Category 2" }
]
}
PUT /test_index/doc/2
{
"id": 2,
"name": "Mark",
"categories": [
{ "id": 1, "name": "Category 1" }
]
}
PUT /test_index/doc/3
{
"id": 3,
"name": "Bill",
"categories": [
{ "id": 3, "name": "Category 3" },
{ "id": 4, "name": "Category 4" }
]
}
Now I can use a nested terms filter like this:
POST /test_index/doc/_search
{
"query": {
"constant_score": {
"filter": {
"nested": {
"path": "categories",
"filter": {
"terms": {
"categories.id": [1, 2]
}
}
}
},
"boost": 1.2
}
}
}
...
{
"took": 3,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"failed": 0
},
"hits": {
"total": 2,
"max_score": 1,
"hits": [
{
"_index": "test_index",
"_type": "doc",
"_id": "1",
"_score": 1,
"_source": {
"id": 1,
"name": "John",
"categories": [
{
"id": 1,
"name": "Category 1"
},
{
"id": 2,
"name": "Category 2"
}
]
}
},
{
"_index": "test_index",
"_type": "doc",
"_id": "2",
"_score": 1,
"_source": {
"id": 2,
"name": "Mark",
"categories": [
{
"id": 1,
"name": "Category 1"
}
]
}
}
]
}
}
Here is the code I used:
http://sense.qbox.io/gist/668aefe910643b52a3a10d40aca67104491668fc