I need to rename the key "street" to "block" in every object of the "address" array in a mongo document. The structure of the document is as follows,
{
"_id": 1234,
"name": "Jack",
"address": [
{
"no": 1,
"street": "streetx",
"country": "countryx"
},
{
"no": 1,
"street": "streety",
"country": "countryy"
}
]
}
Note : The mongoDB version is '4.0.0'
You can use $map to assign the new field to the address objects. For MongoDB v4.0, use javascript to iterate and update back to the collection.
db.collection.aggregate([
{
"$addFields": {
"address": {
"$map": {
"input": "$address",
"as": "a",
"in": {
"$mergeObjects": [
"$$a",
{
"no": "$$a.no",
"country": "$$a.country",
"block": "$$a.street"
}
]
}
}
}
}
}
]).forEach(function(doc){
db.collection.save(doc);
})
Here is the Mongo playground for your reference.
Related
I have the following Mongo collection
{
"_id": ObjectId("5524d12d2702a21830bdb8e5"),
"code": "Apple",
"name": "iPhone",
"parameters": [
{
"code": "xxx",
"name": "Andrew",
"value": "9",
},
{
"code": "yyy",
"name": "Joy",
"value": "7",
},
]
}
I am using the following query to push into the parameters array object
db.coll.update({
"parameters.name": "Andrew"
},
{
$push: {
"parameters": {
"code": "$code",
"name": "bar",
"value": "10",
}
}
},
{
multi: true
})
However, for the value of code, I want to use the value of the object that matched (i.e. the object with parameters.name == "Andrew", which here is xxx.
Here's a playground link to the problem https://mongoplayground.net/p/v-j1tCCjiWq
Also, I am using a really old version (3.2) of MongoDb. It would be preferable if the solution worked with that.
With MongoDB v4.4+, you can first $match with your criteria. Chain up $first with $filter to extract the array element you want. Use $concatArrays to append a new element(i.e. same as $push) to the array and $merge to update back into the collection.
db.coll.aggregate([
{
$match: {
"parameters.name": "Andrew"
}
},
{
$set: {
parameters: {
"$concatArrays": [
"$parameters",
[
{
"$mergeObjects": [
// get the object matched
{
"$first": {
"$filter": {
"input": "$parameters",
"as": "p",
"cond": {
$eq: [
"Andrew",
"$$p.name"
]
}
}
}
},
// update the object matched with other fields with constant value
{
"name": "bar",
"value": "10"
}
]
}
]
]
}
}
},
{
"$merge": {
"into": "coll1",
"on": "_id"
}
}
])
Mongo Playground
I have the following MongoDB documents like this one:
{
"_id": "ABC",
"properties":
[
{
"_id": "123",
"weight":
{
"$numberInt": "0"
},
"name": "Alice"
},
{
"_id": "456",
"weight":
{
"$numberInt": "1"
},
"name": "Bob"
},
{
"_id": "789",
"weight":
{
"$numberInt": "1"
},
"name": "Charlie"
}
]
}
And I would like to find the _id of the property with name "Alice", or the _id of the property with "$numberInt": "0".
I'm using pymongo.
The following approach:
from pymongo import MongoClient
mongo_client = MongoClient("mymongourl")
mongo_collection = mongo_client.mongo_database.mongo_collection
mongo_collection.find({'properties.name': 'Alice'}, {'properties': 1})[0]['_id']
Gives the very first _id ("123")
But since I filtered for the document, if Alice was in the second element of the properties array (_id: "456") I would have missed her.
Which is the best method to find for the specific _id associated with the element with the specified name?
You can simply use $reduce to iterate through the properties array. Conditionally store the _id field if it matches your conditions.
db.collection.aggregate([
{
"$addFields": {
"answer": {
"$reduce": {
"input": "$properties",
"initialValue": null,
"in": {
"$cond": {
"if": {
$or: [
{
$eq: [
"$$this.name",
"Alice"
]
},
{
$eq: [
"$$this.weight",
0
]
}
]
},
"then": "$$this._id",
"else": "$$value"
}
}
}
}
}
}
])
Mongo Playground
Let's assume we have the following documents in the Mongo db
[
{
"Name": "Jack",
"info": {
"eyes": "brown",
"city": "paris",
"accomodation": "house"
}
},
{
"Name": "Mathew",
"info": {
"eyes": "yellow",
"city": "rome",
"accomodation": "apartment"
}
},
{
"Name": "Peter",
"info": {
"eyes": "brown",
"city": "barcelona",
"accomodation": "house",
"hair_color": "black"
}
}
]
Let's say the input JSON is
{
"eyes": "brown",
"city": "paris",
"accomodation": "house",
"hair_color": "black"
}
I would like to construct a query such that all the key-value pairs of the document should be present in the input json document but not necessarily the other way round.
For the above example - the output should be
{
"Name": "Jack",
"info": {
"eyes": "brown",
"city": "paris",
"accomodation": "house"
}
}
Since all the key value pairs of Jack were met by the input json document even though the input JSON document had hair_color which wasn't present in Jack document
Mongo playground with input : https://mongoplayground.net/p/1T0ZL8yGhPW
All you have to do is convert both your input and info field to an array using $objectToArray and check if their if there's any none matches, like so:
db.collection.aggregate([
{
$addFields: {
rawInput: { // better if you do this in code once and drop this stage.
"$objectToArray": {
"eyes": "brown",
"city": "paris",
"accomodation": "house",
"hair_color": "black"
}
}
}
},
{
$match: {
$expr: {
$eq: [
{
$size: {
$filter: {
input: {
"$objectToArray": "$info"
},
as: "elem",
cond: {
$not: {
"$in": [
"$$elem",
"$rawInput"
]
}
}
}
}
},
0
]
}
}
},
{
"$project": {
Name: 1,
info: 1
}
}
])
Mongo Playground
We have the following problem
Given are the tables and fields
Offer
OfferId
State
Article
OfferId
ArticleId
NetPrice
GrossPrice
VatRate
Example-data:
Offer-Collection
{
"_id": "1",
"State": "INITIAL",
"_class": "com.example.dto.OfferData"
}
{
"_id": "2",
"State": "COMPLETED",
"_class": "com.example.dto.OfferData"
}
Article-Collection
{
"_id": {
"$oid": "a"
},
"Description": "asdf",
"NetPrice": "100",
"GrossPrice": "116",
"VatRate": "16",
"OfferId": "1",
"_class": "com.example.dto.Article"
}
{
"_id": {
"$oid": "b"
},
"Description": "my description",
"NetPrice": "100",
"GrossPrice": "119",
"VatRate": "19",
"OfferId": "1",
"_class": "com.example.dto.Article"
}
{
"_id": {
"$oid": "c"
},
"Description": "my description",
"NetPrice": "100",
"GrossPrice": "116",
"VatRate": "16",
"OfferId": "2",
"_class": "com.example.dto.Article"
}
Now we have to update all articles belonging to an offer with the state "initial" in the following way: if the VatRate is equal to 16 than it must be updated to 19 AND the GrossPrice must be recalculated from the existing NetPrice.
The result should be: the article with _id = "a" and VatRate = 16 for OfferId = 1 (State = INITIAL) should have VatRate = 19 and GrossPrice = 119. The fields should be updated and persisted in the original MongoDB collection.
Can we do this only with Mongo-shell? Our Version is 3.6.
Our tries:
We have played around with .aggregate, $lookup, $match and $project but without much luck. It's the first time we are using the Mongo-shell.
db.getCollection("Offers").aggregate([{
$lookup:{
from:"Articles",
localField:"OfferId",
foreignField:"OfferId",
as:"selected-articles"
}
},
{
$match: { "state": { "$eq": "INITIAL" } }
},
{
$project: { "articles": 1 }
}
]).forEach(...?)
$match your State condition
$lookup with Articles collection
$map to iterate loop of selected-articles array, check condition using $cond if VatRate is "16" then updated to 19 and recalculate GrossPrice as per NetPrice using $multiply before it convert NetPrice to integer because its in string type, back to merge objects with current objects using $mergeObjects
db.getCollection("Offers").aggregate([
{ $match: { State: { $eq: "INITIAL" } } },
{
$lookup: {
from: "Articles",
localField: "_id",
foreignField: "OfferId",
as: "selected-articles"
}
},
{
$addFields: {
"selected-articles": {
$map: {
input: "$selected-articles",
in: {
$mergeObjects: [
"$$this",
{
$cond: [
{ $eq: ["$$this.VatRate", "16"] },
{
VatRate: 19,
GrossPrice: {
$multiply: [{ $toInt: "$$this.NetPrice" }, 19]
}
},
{}
]
}
]
}
}
}
}
}
])
Playground
I have a mongo Database I'll like to "join" two of them and then merge some other fields:
Let's see the schemas:
Students Schema (and data):
{
"_id": ObjectId("5fbd564981b1313de790b580"),
"name": "John Doe",
"age": "21",
"image": "https://XXXX/481.png",
"subjects": [
{
"_id": ObjectId("5fbd4e6881b1313de790b56b"),
"passed": true,
},
{
"_id": ObjectId("5fcb63fa8814d96876c687bf"),
}
],
"__v": NumberInt("1"),
}
and Subject schema:
{
"_id": ObjectId("5fbd4e6881b1313de790b56b"),
"course": 3,
"teacher": "John Smith",
"name": "Math",
},
{
"_id": ObjectId("5fcb63fa8814d96876c687bf"),
"name": "IT",
"course": 8,
"teacher": "John Peter",
}
What I'll like to make a query with the subjects (all info) of a student, also if the student have additional fields in subject like passed add it to the subject subdocument.
Here is my query till now:
db.students.aggregate([
{
$match:
{
_id : ObjectId('5fbd564981b1313de790b580')
}
},
{
$lookup :
{
from : "subjects",
localField : "subjects._id",
foreignField : "_id",
as : "FoundSubject"
}
}
]);
which correctly make the "join" but the merge is still missing, I got as result:
{
"_id": ObjectId("5fbd564981b1313de790b580"),
"name": "John Doe",
"age": "21",
"image": "https://XXXX/481.png",
"subjects": [
{
"_id": ObjectId("5fbd4e6881b1313de790b56b"),
"passed": true,
},
{
"_id": ObjectId("5fcb63fa8814d96876c687bf"),
}
],
"__v": NumberInt("1"),
"FoundSubject": [
{
"_id": ObjectId("5fbd4e6881b1313de790b56b"),
"course": 3,
"teacher": "John Smith",
"name": "Math"
},
{
"_id": ObjectId("5fcb63fa8814d96876c687bf"),
"name": "IT",
"course": 8,
"teacher": "John Peter"
}
]
}
but I'll like to have:
{
"_id": ObjectId("5fbd564981b1313de790b580"),
"name": "John Doe",
"age": "21",
"image": "https://XXXX/481.png",
"subjects": [
{
"_id": ObjectId("5fbd4e6881b1313de790b56b"),
"course": 3,
"teacher": "John Smith",
"name": "Math",
"passed": true,
},
{
"_id": ObjectId("5fcb63fa8814d96876c687bf"),
"name": "IT",
"course": 8,
"teacher": "John Peter"
}
],
"__v": NumberInt("1"),
}
with merged data and field "passed" added. How can accomplish that?
I'm new to MongoDB coming from MySQL.
Thanks
You need to merge both objects, add below stage after $lookup,
MongoDB Version From 3.4
$map to iterate loop of students array
$reduce to iterate loop of FoundSubject array, check condition if condition match then return required fields otherwise return initial value
$project to remove FoundSubject from result
{
$addFields: {
subjects: {
$map: {
input: "$subjects",
as: "s",
in: {
$reduce: {
input: "$FoundSubject",
initialValue: {},
in: {
$cond: [
{ $eq: ["$$s._id", "$$this._id"] },
{
_id: "$$this._id",
course: "$$this.course",
name: "$$this.name",
teacher: "$$this.teacher",
passed: "$$s.passed"
},
"$$value"
]
}
}
}
}
}
}
},
{ $project: { FoundSubject: 0 } }
Playground
MongoDB Version From 4.4
$map to iterate loop of students array,
$filter to get matching document from FoundSubject array and $first to get first object from array returned by filter
$mergeObjects to merge current objects with found result object from filter
remove FoundSubject using $$REMOVE
// skipping your stages
{
$addFields: {
FoundSubject: "$$REMOVE",
subjects: {
$map: {
input: "$subjects",
as: "s",
in: {
$mergeObjects: [
"$$s",
{
$first: {
$filter: {
input: "$FoundSubject",
cond: { $eq: ["$$s._id", "$$this._id"] }
}
}
}
]
}
}
}
}
}
Playground