I have a mongodb collection Users that looks like this:
{
"_id" : ObjectId("5dba8987b4a39c13bc104a23"),
"contact" : {
"firstName" : "Mark",
"lastName" : "Doe",
"parentsBloodType" : [
{
"type" : "AB+",
},
{
"type" : "A+",
},
],
},
"createdAt" : ISODate("2019-10-31T07:13:11.278Z"),
"updatedAt" : ISODate("2019-11-26T09:59:41.611Z")
}
I need to run a raw query to update from AB+ to O-. I would also like to check if they match before updating.
I tried this but it added an extra field to the User:
db.getCollection('users').update(
{"_id": ObjectId("5dba8987b4a39c13bc104a23")},
{"$set" : { 'parentsBloodType.' + '0' + '. type' : "O-"}}
)
This one would do the update:
db.users.update(
{ "_id": ObjectId("5dba8987b4a39c13bc104a23") },
{ "$set": { 'contact.parentsBloodType.0.type' : "O-"} }
)
You an check match with this:
db.users.update(
{
"_id": ObjectId("5dba8987b4a39c13bc104a23"),
"contact.parentsBloodType.type": "AB+"
},
{ "$set": { 'contact.parentsBloodType.0.type': "AB+" } }
)
This updates the document only if type AB+ exist (at any parent).
Or if you like to check whether the first type is AB+ then use
db.users.update(
{
"_id": ObjectId("5dba8987b4a39c13bc104a23"),
"contact.parentsBloodType.0.type": "AB+"
},
{ "$set": { 'contact.parentsBloodType.0.type': "AB+" } }
)
However, I assume you are actually looking for this:
db.users.update(
{ "_id": ObjectId("5dba8987b4a39c13bc104a23") },
{ "$set": { 'contact.parentsBloodType.$[p].type': "0-" } },
{ arrayFilters: [{ "p.type": "AB+" }] }
)
Which will update any AB+ to 0- no matter on which position it appears in the array.
You could use the positional $ operator to update the first element that matches the query document:
db.getCollection('users').update(
{ "_id": ObjectId("5dba8987b4a39c13bc104a23"), "parentsBloodType.type": "AB+" },
{ "$set" : { 'parentsBloodType.$.type' : "O-" } }
)
note that:
the positional $ operator acts as a placeholder for the first element that matches the query document, and
the array field must appear as part of the query document.
Or use the filtered positional operator $[] if you want to update all elements that match an array filter condition or conditions:
db.students.update(
{ "_id": ObjectId("5dba8987b4a39c13bc104a23") },
{ $set: { "parentsBloodType.$[element].type" : "O-" } },
{
arrayFilters: [ { "element.type": "AB+" } ]
}
)
Related
MongoDB Version - 3.4.2
I'm trying to query within the Sitecore Analytics database, trying to retrieve all users that are associated with a given List Id.
The example dataset I have follows the default Sitecore Analytics setup:
"Tags" : {
"Entries" : {
"ContactLists" : {
"Values" : {
"0" : {
"Value" : "{1E2D1AB7-72A0-4FF7-906B-DCDC020B87D2}",
"DateTime" : ISODate("2020-10-23T17:38:13.891Z")
},
"1" : {
"Value" : "{28BECCD3-476B-4B1D-9A75-02E59EF21286}",
"DateTime" : ISODate("2018-04-18T14:22:41.763Z")
},
"2" : {
"Value" : "{2C2BB0C3-483D-490E-B93A-9155BFBBE5DC}",
"DateTime" : ISODate("2018-05-10T14:26:08.494Z")
},
"3" : {
"Value" : "{DBE480F6-E305-4B35-9E6D-CBED64F4E44F}",
"DateTime" : ISODate("2018-10-27T02:41:28.776Z")
},
}
}
}
},
I want to iterate through all the entries within Values without having to specify 0/1/2/3, avoiding the following:
db.getCollection('Contacts').find({"Tags.Entries.ContactLists.Values.1.Value": "{28BECCD3-476B-4B1D-9A75-02E59EF21286}"})
I've tried the following:
db.getCollection('Contacts').find({"Tags.Entries.ContactLists.Values": {$elemMatch : {"Value":"{28BECCD3-476B-4B1D-9A75-02E59EF21286}"}}})
db.getCollection('Contacts').find({'Tags' : {$elemMatch : {$all : ['{28BECCD3-476B-4B1D-9A75-02E59EF21286}']}}})
db.getCollection('Contacts').forEach(function (doc) {
for(var i in doc.Tags.Entries.ContactLists.Values)
{
doc.Tags.Entries.ContactLists.Values[i].Value = "{28BECCD3-476B-4B1D-9A75-02E59EF21286}";
}
})
And a few other variations which I cannot recall now. And none work.
Any ideas if this is possible or on how to do this?
I want the outcome to just show filter out the results showing only the entries containing the matching GUID
Many thanks!
Demo - https://mongoplayground.net/p/upgYxgzPwJQ
It can be done using aggregation pipeline
Use $objectToArray to convert array
Use $filter to filter the array
db.collection.aggregate([
{
$addFields: {
filteredValue: {
$filter: {
input: {
$objectToArray: "$Tags.Entries.ContactLists.Values"
},
as: "val",
cond: {
$eq: [ // filter condition
"$$val.v.Value",
"{28BECCD3-476B-4B1D-9A75-02E59EF21286}"
]
}
}
}
}
}
])
Output -
[
{
"Tags": {
"Entries": {
"ContactLists": {
"Values": {
"0": {
"DateTime": ISODate("2020-10-23T17:38:13.891Z"),
"Value": "{1E2D1AB7-72A0-4FF7-906B-DCDC020B87D2}"
},
"1": {
"DateTime": ISODate("2018-04-18T14:22:41.763Z"),
"Value": "{28BECCD3-476B-4B1D-9A75-02E59EF21286}"
},
"2": {
"DateTime": ISODate("2018-05-10T14:26:08.494Z"),
"Value": "{2C2BB0C3-483D-490E-B93A-9155BFBBE5DC}"
},
"3": {
"DateTime": ISODate("2018-10-27T02:41:28.776Z"),
"Value": "{DBE480F6-E305-4B35-9E6D-CBED64F4E44F}"
}
}
}
}
},
"_id": ObjectId("5a934e000102030405000000"),
"filteredValue": [
{
"k": "1",
"v": {
"DateTime": ISODate("2018-04-18T14:22:41.763Z"),
"Value": "{28BECCD3-476B-4B1D-9A75-02E59EF21286}"
}
}
]
}
]
You can not use $elemMatch because Values is not array, but object. You can solve the problem with Aggregation Pipeline:
$addFields to add new field Values_Array that will be array representation of Values object.
$objectToArray to transform Values object to array
$match to find all documents that has requested value in new Values_Array field
$project to specify which properties to return from the result
db.getCollection('Contacts').aggregate([
{
"$addFields": {
"Values_Array": {
"$objectToArray": "$Tags.Entries.ContactLists.Values"
}
}
},
{
"$match": {
"Values_Array.v.Value": "{28BECCD3-476B-4B1D-9A75-02E59EF21286}"
}
},
{
"$project": {
"Tags": 1
}
}
])
Here is the working example: https://mongoplayground.net/p/2gY-vu3Qrvz
I have a document like this:
{
"_id": ObjectId("5d779541bd4e75c58d598212")
"client": ObjectId("5d779558bd4e75c58d598213")
}
When I do $lookup like this:
{
from: 'client',
localField: 'client',
foreignField: 'id',
as: 'client',
}
I get:
{
"_id": ObjectId("5d779541bd4e75c58d598212")
"client":[
{
... client info wrapped in array
}
]
}
This forces me to add $unwind after the lookup stage.
This would work fine in this example because I know that it is a regular field (not array). But on other collections I have arrays of ObjectId's and I don't want to unwind them.
How should I tell mongo to unwind only if it's not an array?
Add $project stage with $arrayElemAt
{ $lookup ..... },
{ $project: { client: { $arrayElemAt: [ "$client" , 0 ]}} // Add other filed
The lookup always returns an array as it doesn't know if its a one-to-one or one-to-many mapping. But we can ensure that the lookup returns a single document and that document would hold all documents which were supposed to come as an array in the general lookup.
Following is the way:
db.collection.aggregate([
{
$lookup:{
"from":"client",
"let":{
"client":"$client"
},
"pipeline":[
{
$match:{
$expr:{
$eq:["$id","$$client"]
}
}
},
{
$group:{
"_id":null,
"data":{
$push:"$$ROOT"
}
}
},
{
$project:{
"_id":0
}
}
],
"as":"clientLookup"
}
},
{
$unwind:"$clientLookup"
}
]).pretty()
Query analysis: We are looking up into client collection and executing a pipeline inside that. The output of that pipeline would hold every matched document inside data field.
Data set:
Collection: collection
{
"client":1
}
{
"client":2
}
Collection: client
{
"id":1,
"name":"Tony"
}
{
"id":1,
"name":"Thor"
}
{
"id":1,
"name":"Natasha"
}
{
"id":2,
"name":"Banner"
}
Output:
{
"_id" : ObjectId("5d7792c6bd4e75c58d59820c"),
"client" : 1,
"clientLookup" : {
"data" : [
{
"_id" : ObjectId("5d779322bd4e75c58d59820e"),
"id" : 1,
"name" : "Tony"
},
{
"_id" : ObjectId("5d779322bd4e75c58d59820f"),
"id" : 1,
"name" : "Thor"
},
{
"_id" : ObjectId("5d779322bd4e75c58d598210"),
"id" : 1,
"name" : "Natasha"
}
]
}
}
{
"_id" : ObjectId("5d7792c6bd4e75c58d59820d"),
"client" : 2,
"clientLookup" : {
"data" : [
{
"_id" : ObjectId("5d779322bd4e75c58d598211"),
"id" : 2,
"name" : "Banner"
}
]
}
}
I have a collection that looks like this:
{
"value" : "20",
"type" : "square",
"name" : "form1"
}
{
"value" : "24",
"type" : "circle",
"name" : "form2"
}
{
"value" : "12",
"type" : "square",
"name" : "form3"
}
I want to extract a document with name = form2 so I type:
db.myCollec.find({"name":"form2"} , {"name":1, "type":1, "_id":0})
The result is:
{ "name" : "form2", "type" : "circle" }
Now if I want to find a document with name = form4 I type:
db.myCollec.find({"name":"form4"} , {"name":1, "type":1, "_id":0})
But this returns nothing because there is no document with this name.
However I want the return value to look like this:
{ "name" : "form4", "type" : null }
How would I do this?
You can use below aggregation
Mongodb doesn't produce the result if there is not $matched data found with the query.
But you can use $facet aggregation which processes multiple aggregation pipeline within single stage.
So first use $facet to get the $matched documents and use $projection if no ($ifNull) data found.
let searchTerm = "form2"
db.myCollec.aggregate([
{ "$facet": {
"data": [
{ "$match": { "name": searchTerm }},
{ "$project": { "name": 1, "type": 1, "_id": 0 }}
]
}},
{ "$project": {
"name": {
"$ifNull": [{ "$arrayElemAt": ["$data.name", 0] }, searchTerm ]
},
"type": {
"$ifNull": [{ "$arrayElemAt": ["$data.type", 0] }, null]
}
}}
])
Why you dont check in callback if result==null and create your own empty object?
let name = "form4";
db.myCollec.find({"name":name} , {"name":1, "type":1, "_id":0}, function(err, result){
if(err) {
// Error handling
return;
}
if (result==null){
result = {"name":name, "type":null};
}
});
I want to aggregate over a collection where a type is given. If the type is foo I want to group by the field author, if the type is bar I want to group by user.
All this should happen in one query.
Example Data:
{
"_id": 1,
"author": {
"someField": "abc",
},
"type": "foo"
}
{
"_id": 2,
"author": {
"someField": "abc",
},
"type": "foo"
}
{
"_id": 3,
"user": {
"someField": "abc",
},
"type": "bar"
}
This user field is only existing if the type is bar.
So basically something like that... tried to express it with an $or.
function () {
var results = db.vote.aggregate( [
{ $or: [ {
{ $match : { type : "foo" } },
{ $group : { _id : "$author", sumAuthor : {$sum : 1} } } },
{ { $match : { type : "bar" } },
{ $group : { _id : "$user", sumUser : {$sum : 1} } }
} ] }
] );
return results;
}
Does someone have a good solution for this?
I think it can be done by
db.c.aggregate([{
$group : {
_id : {
$cond : [{
$eq : [ "$type", "foo"]
}, "author", "user"]
},
sum : {
$sum : 1
}
}
}]);
The solution below can be cleaned up a bit...
For "bar" (note: for "foo", you have to change a bit)
db.vote.aggregate(
{
$project:{
user:{ $ifNull: ["$user", "notbar"]},
type:1
}
},
{
$group:{
_id:{_id:"$user.someField"},
sumUser:{$sum:1}
}
}
)
Also note: In you final answer, anything that is not of type "bar" will have an _id=null
What you want here is the $cond operator, which is a ternary operator returning a specific value where the condition is true or false.
db.vote.aggregate([
{ "$group": {
"_id": null,
"sumUser": {
"$sum": {
"$cond": [ { "$eq": [ "$type", "user" ] }, 1, 0 ]
}
},
"sumAuhtor": {
"$sum": {
"$cond": [ { "$eq": [ "$type", "auhtor" ] }, 1, 0 ]
}
}
}}
])
This basically tests the "type" of the current document and decides whether to pass either 1 or 0 to the $sum operation.
This also avoids errant grouping should the "user" and "author" fields contain the same values as they do in your example. The end result is a single document with the count of both types.
I have a collection in mogodb like this:
{
"_id" : ObjectId("5393006538efaae30ec2d458"),
"userName" : "shiva",
"userUnderApiKey" : 123456,
"groups" : [
{
"groupName" : "Default",
"groupMembers" : [ ]
}
]
}
I want to add a new group in the groups array as sub document, like the below
{
"_id" : ObjectId("5393006538efaae30ec2d458"),
"userName" : "shiva",
"userUnderApiKey" : 123456,
"groups" : [
{
"groupName" : "Default",
"groupMembers" : [ ]
},
{
"groupName" : "Family",
"groupMembers" : [ ]
}
]
}
How to insert new sub document in the array of sub documents.Any help would be appriciated
To add a new member to the array you just use $push as you normally would:
db.collection.update(
{ "_id": ObjectId("5393006538efaae30ec2d458") },
{
"$push": {
"groups": {
"groupName" : "Family",
"groupMembers" : [ ]
}
}
}
)
If you then wanted to add members to the array that member contains then you need to match the element you want to add to:
db.collection.update(
{
"_id": ObjectId("5393006538efaae30ec2d458"),
"groups.groupName" : "Family",
},
{
"$push": {
"groups.$.groupMembers" : "bill"
}
}
)
I think you would be interested in $push
The $push operator appends a specified value to an array.
and $addToSet
The $addToSet operator adds a value to an array only if the value is not already in the array. If the value is in the array, $addToSet does not modify the array.
you can find examples in the documents above. It would be something like:
db.collection.update({
_id: ObjectId("5393006538efaae30ec2d458")
}, {
$push: {
groups: {
"groupName": "Family",
"groupMembers": []
}
}
});
SampleModel:
{
"Name":String,
"brandid": {
type: Schema.ObjectId,
ref: 'BrandList.BrandItems',
}
}
BrandModel:
{
"BrandName" : String,
"BrandItems": [{
"KG": Number,
"_id" : {type: Schema.ObjectId}
}]
}
How to refered subdocument array Object id to another model..and also how to use populate for this "brandid"..
Pls give me some solutin to solve this problem....