I have a MongoDB database structure that looks something like this.
{
"peopleholder": {
"people": [
{
"otherdata": "asdf",
"name": "joe"
},
{
"otherdata": "asdf",
"name": "bob"
}
]
}
}
Now, I'm trying to construct a search query to select all people who have name "bob", right?
So, I've tried some things, looking at the $all suggestion, and come up with...
{
"peopleholder": {
"people": {
"$all": [
{
"name": "bob"
}
]
}
}
}
I've also tried it with people just equal to {"name": "bob"}, as that appears to be shorthand.
This should do it:
{ "peopleholder.people.name": "bob"}
Source Mongodb docs
Related
I have some data in mongo looks like
{ "name": "John", "city":"X", "location": ["A", "B"] }
{ "name": "Dude", "city":"X", "location": ["B"] }
{ "name": "Alan", "city":"Y", "location": ["A", "B"] }
{ "name": "Wang", "city":"Y", "location": ["X", "B"] }
There is a compound index
{
"city": 1,
"location": 1
}
This index is use to speed up query for names in specific city and location like
db.collection.find( { "city":"X", location: "A" } )
db.collection.find( { "city":"Y", location: { $in: ["A", "B"] } } )
What I want to do is to know how many rows exists for each location in a specific city, say X. With above data the result should be:
{ "_id": { "location":"A" }, amount: 1 }
{ "_id": { "location":"B" }, amount: 2 }
Here assumes that I do not know how many type of location it is. I mean I can not list all possible location elements before I query it.
If I know all possible locations and it is not too much, a simple thought is to issue multiple query and each of the query can fully utilize index without fetch any data from disk
db.collection.find( { "city":"X", location: "A" } ).count()
db.collection.find( { "city":"X", location: "B" } ).count()
db.collection.find( { "city":"X", location: "C" } ).count()
...
BUT, since I do no know all possible elements in advance, what comes to my mind is to use group by, like
db.collection.aggregate([
{ $match: { "city":"X" } },
{ $unwind: "$location" } },
{ $group: { _id: "$location", "amount": { "$sum": 1 } } }
])
However, when explain() this query, only the $match part can utilize the index, after $unwind, fetch data from disk is required (correct me if I am wrong).
Technically, the index contains all information required for the query. So I wonder is there any query that can fully utilize the index.
BTW, my mongo version is 3.6. If it can only be done in newer version, still please let me know. Thanks.
I'm using Nodejs with Mongoose package.
Given I've something like this:-
let people = [
{
"_id": 1,
"name": "Person 1",
"pets": [
{
"_id": 1,
"name": "Tom",
"category": "cat"
},
{
"_id": 2,
"name": "Jerry",
"category": "mouse"
}
]
}
]
I want to get only the data of Jerry in pets array using it's _id (result shown below)
{
"_id": 2,
"name": "Jerry",
"category": "mouse"
}
Can I get it without needing to specify the _id of person 1 when using $elemMatch? Right now I code like this:-
const pet = People.find(
{ "_id": "1"}, // specifying 'person 1 _id' first
{ pets: { $elemMatch: { _id: 2 } } } // using 'elemMatch' to get 'pet' with '_id' of '2'
)
And it gave me what I want like I've shown you above. But is there any other way I can do this without needing to specify the _id of it's parent first (in this case, the _id of the people array)
Assuming nested array's _id's are unique you can filter by nested array elements directly:
const pet = People.find(
{ "pets._id": 2 },
{ pets: { $elemMatch: { _id: 2 } } }
)
I have the following query and it works with $in but not with $nin.
I'm trying to remove the link list items by name (itemA and itemB) from all records that are NOT part of a document that has a user name which contains '#not_these' or '#nor_these'.
db.users.update({userName:{$nin: [ RegExp('#not_these.com'), RegExp('#nor_these.com') ]}},{$pull:{'myLinkList': {name: {$in: ['itemA', 'itemB']} } } } )
If I make it $in and and declare the RegExp() explicitly it does remove the array items as expected.
db.users.update({userName:{$in: [ RegExp('#yes_these.com'), RegExp('#and_these.com') ]}},{$pull:{'myLinkList': {name: {$in: ['itemA', 'itemB']} } } } )
This one does remove itemA and itemB array list items for those explicitly declared users.
Why can't the items '#yes_these' and '#and_these' be removed using the first example? It seems to do nothing when executed.
Sample document:
{
"_id": ObjectId('5e34741aa18d8a0c24078b61'),
"myLinkList": [
{
"name": "item",
"created": ISODate('2020-01-31T18:38:18.682Z'),
"managedBy": [
"imm"
]
},
{
"name": "itemA",
"created": ISODate('2020-01-31T18:38:18.682Z'),
"managedBy": [
"imm"
]
},
{
"name": "itemB",
"created": ISODate('2020-01-31T18:38:18.682Z'),
"managedBy": [
"imm"
]
}
],
"userName": "#yes_these.com"
}
After update (hopefully):
{
"_id": ObjectId('5e34741aa18d8a0c24078b61'),
"myLinkList": [
{
"name": "item",
"created": ISODate('2020-01-31T18:38:18.682Z'),
"managedBy": [
"imm"
]
}
],
"userName": "#yes_these.com"
}
I verified this did work:
db.users.updateMany({userName:{$nin: [ /#not_these\.com/), /#nor_these\.com/) ]}},{$pull:{'myLinkList': {name: {$in: ['itemA', 'itemB']} } } } )
I m working with mongodb and restheart.
In my nosql db i have a unique document with this structure:
{
"_id": "docID",
"users": [
{
"userID": "12",
"elements": [
{
"elementID": "1492446877599",
"events": [
{
"event1": "one"
},
{
"event2": "two",
}
]
}
},
{
"userID": "11",
"elements": [
{
"elementID": "14924",
"events": [
{
"event1": "one"
},
{
"event2": "two",
}
]
}
}
]
}
how can i build an url-query in order to get the user with id 11?
Using mongo shell it should be something like this one:
db.getCollection('collection').find({},{'users':{'$elemMatch':{'userID':'12'}}}).pretty()
I cannot find anything similar on restheart.
Could someone help me?
Using this
http://myHost:port/documents/docID?filter={%27users%27:{%27$elemMatch%27:{%27userID%27:%2712%27}}}
restheart returns me all the documents: userID 11 and 12.
Your request is against a document resource, i.e. the URL is http://myHost:port/documents/docID
The filter query parameter applies for collection requests, i.e. URLs such as http://myHost:port/documents
In any case you need to projection (the keys query parameter) to limit the returned properties.
You should achieve it with the following request (I haven't tried it) using the $elementMatch projection operator:
http://myHost:port/documents?keys={"users":{"$elemMatch":{"userID":"12"}}}
Considering the below bad model, as I am totally new to this.
{
"uid": "some-id",
"database": {
"name": "nameOfDatabase",
"collection": [
{
"name": "nameOfCollection",
"fields": {
"0": "field_1",
"1": "field_2"
}
},
{
"name": "nameOfAnotherCollection",
"fields": {
"0": "field_1"
}
}
]
}
}
I have the collection name (i.e database.collection.name) and I have a few fields to add to it or delete from it (there are some already existing ones under database.collection.fields, I want to add new ones or delete exiting ones).
In short how do I update/delete "fields", when I have the database name and the collection name.
I cannot figure out how to use positional operator $ in this context.
Using mongoose update as
Model.update(conditions, updates, options, callback);
I don't know what are correct conditions and correct updates parameters.
So far I have unsuccessfully used the below for model.update
conditions = {
"uid": req.body.uid,
"database.name": "test",
"database.collection":{ $elemMatch:{"name":req.body.collection.name}}
};
updates = {
$set: {
"fields": req.body.collection.fields
}
};
---------------------------------------------------------
conditions = {
"uid": req.body.uid,
"database.name": "test",
"database.collection.$.name":req.body.collection.name
};
updates = {
$addToSet: {
"fields": req.body.collection.fields
}
};
I tried a lot more but none did work, as I am totally new.
I am getting confused between $push, $set, $addToSet, what to use what not to?, how to?
The original schema is supposed to be as show below, but running queries on it is getting harder n harder.
{
"uid": "some-id",
"database": [
{ //array of database objects
"name": "nameOfDatabase",
"collection": [ //array of collection objects inside respective databases
{
"name": "nameOfCollection",
"fields": { //fields inside a this particular collection
"0": "field_1",
"1": "field_2"
}
}
]
}
]
}