I have a array in mongodb document.
{
_id: 1,
jobs:[
{
_id:1,
time: "08:00",
status: "pending",
user: 'user1'
},
{
_id:2,
time: "09:00",
status: "pending",
user: 'user1'
},
{
_id:3,
time: "07:30",
status: "done",
user: 'user2'
}
]
}
now I have a updated jobs array like this.
jobs:[
{
_id:1,
time: "10:00",
status: "done"
},
{
_id:2,
time: "11:00",
status: "done"
}
]
updated document should like this
{
_id: 1,
jobs:[
{
_id:1,
time: "10:00", // updated
status: "done" // updated
user: 'user1'
},
{
_id:2,
time: "11:00", // updated
status: "done", // updated
user: "user1"
},
{
_id:3,
time: "07:30",
status: "done",
user: 'user2'
}
]
}
I tried using update and $set and no luck so far
how do I update the only the values in the updated array in to the mongodb document? thanks in advance
One option is using an update with a pipeline:
Add the new data into the document as newData
Using a $map to loop over the jobs items, for each item merge it with the matching item in newData.
EDIT (consider partial match):
db.collection.update(
{_id: 1},
[{$addFields: {
newData: [
{_id: 1, time: "10:00", status: "done"},
{_id: 2, time: "11:00", status: "done"}
]
}
},
{$project: {
jobs: {$map: {
input: "$jobs",
in: {$mergeObjects: [
"$$this",
{$cond: [
{$gte: [{$indexOfArray: ["$newData._id", "$$this._id"]}, 0]},
{$arrayElemAt: ["$newData", {$indexOfArray: ["$newData._id", "$$this._id"]}]},
]}
]}
]}
}}
}}
])
See how it works on the playground example
Related
I have a collection Shops. Each object in Shops collection has an array of Item objects called items.
{
_id: ObjectId(...),
shopName: 'Ice cream Shop',
items: [
<Item>{
itemName: 'Chocolate IC',
availabilities: [
{
city: 'NY',
arrivals: [
{
price: 3.99,
quantityLeft: 0,
date: 'yesterday'
},
{
price: 3.99,
quantityLeft: 40,
date: 'today'
}
]
},
{
city: 'LA',
arrivals: []
}
]
},
<Item>{
itemName: 'Strawberry IC',
availabilities: [
{
city: 'NY',
arrivals: [
{
price: 3.99,
quantityLeft: 0,
date: 'yesterday'
},
]
}
]
},
],
},
... anotherShops
I want to get list of Item objects which has overall quantityLeft more than 0 from a specific shop.
I tried this code to get all items with the name start with "Straw" from a Shop with shopName equal to 'Ice cream Shop':
const items = await Shop.aggregate()
.match({
shopName: 'Ice cream Shop',
})
.project({
items: {
$filter: {
input: "$items",
as: "item",
cond: {
$regexMatch: {
input: "$$item.itemName",
regex: `.*Straw.*`,
},
},
},
},
});
And it works. But I don't know how to sum up all quantityLeft values inside availabilities array of each item, and return only that items that has sum more than 0.
availabilities array can be an empty array [].
The city parameter also needs to be in condition. For example, only Items that are in stock in NY
I need this to get the list of items from a certain shop, and only the items that are still in stock.
Pretty hard.
I came up with this solution. If you have a better solution, please post it.
const shop = await GCShop.aggregate([
{
$match: {
shopName: 'Ice Cream Shop',
},
},
{
$unwind: "$items",
},
{
$unwind: "$items.availabilities",
},
{
$unwind: "$items.availabilities.arrivals",
},
{
$group: {
_id: "$items.id",
items_name: { $first: "$items.name" },
arrivals: {
$push: {
arrival_id: "$items.availabilities.arrivals.arrival_id",
price: "$items.availabilities.arrivals.price",
qtty: "$items.availabilities.arrivals.qtty",
},
},
totalQtty: { $sum: "$items.availabilities.arrivals.qtty" },
},
},
{
$project: {
offer_id: "$_id",
_id: 0,
offer_name: 1,
totalQtty: 1,
arrivals: 1,
},
},
{
$match: {
totalQtty: {
$gt: 0,
},
},
},
]).limit(20);
Inspired by another question I was looking for a common way to add a field with the index to each item in a nested array.
Assuming my document looks like:
{
_id: ObjectId("5a934e000102030405000000"),
events: [
{
status: 0,
timestamp: ISODate("2022-05-29T13:26:00Z")
},
{
status: 8,
timestamp: ISODate("2022-05-29T14:41:00Z")
},
{
status: 4,
timestamp: ISODate("2022-05-31T10:13:00Z")
},
{
status: 3,
timestamp: ISODate("2022-05-31T10:18:00Z")
}
]
}
And I want each item to contain a new field which is the index of the item in the array:
{
_id: ObjectId("5a934e000102030405000000"),
events: [
{
arrayIndex: 0,
status: 0,
timestamp: ISODate("2022-05-29T13:26:00Z")
},
{
arrayIndex: 1,
status: 8,
timestamp: ISODate("2022-05-29T14:41:00Z")
},
{
arrayIndex: 2,
status: 4,
timestamp: ISODate("2022-05-31T10:13:00Z")
},
{
arrayIndex: 3,
status: 3,
timestamp: ISODate("2022-05-31T10:18:00Z")
}
]
}
Since mongoDB version 3.4, this can be done using an aggregation pipeline with a $reduce phase, which uses the size of the new accumulated array:
db.collection.aggregate([
{$project: {
events: {
$reduce: {
input: "$events",
initialValue: [],
in: {
$concatArrays: [
"$$value",
[
{$mergeObjects: [
"$$this",
{arrayIndex: {$size: "$$value"}}
]}
]
]
}
}
}
}}
])
See how it works on the playground example
Inspired by another question I was looking for a common way to couple items in a nested array, so the 1st item will be coupled with the 2nd item, and the 3rd item will be coupled with the 4th item.
Assuming my document looks like:
{
_id: ObjectId("5a934e000102030405000000"),
events: [
{
status: 0,
timestamp: ISODate("2022-05-29T13:26:00Z")
},
{
status: 8,
timestamp: ISODate("2022-05-29T14:41:00Z")
},
{
status: 4,
timestamp: ISODate("2022-05-31T10:13:00Z")
},
{
status: 3,
timestamp: ISODate("2022-05-31T10:18:00Z")
}
]
}
And I want to couple the items:
{
_id: ObjectId("5a934e000102030405000000"),
couples: [
[
{
mod: 0,
status: 0,
timestamp: ISODate("2022-05-29T13:26:00Z")
},
{
mod: 1,
status: 8,
timestamp: ISODate("2022-05-29T14:41:00Z")
}
],
[
{
mod: 0,
status: 4,
timestamp: ISODate("2022-05-31T10:13:00Z")
},
{
mod: 1,
status: 3,
timestamp: ISODate("2022-05-31T10:18:00Z")
}
]
]
}
Since mongoDB version 4.4*, One option is to use an aggregation pipeline with $reduce, $mod, $filter and $zip:
$reduce with $mod to add a new mod field to each item, with value 0 to each odd index (1, 3, 5,...) and value 1 to each even index (2, 4, 6,...)
$fiter into two arrays according to the mod value
$zip these two arrays to one array of couples
db.collection.aggregate([
{
$project: {
events: {
$reduce: {
input: "$events",
initialValue: [],
in: {$concatArrays: [
"$$value",
[
{
timestamp: "$$this.timestamp",
status: "$$this.status",
mod: {$mod: [{$size: "$$value"}, 2]}
}
]
]
}
}
}
}
},
{
$project: {
firstEvent: {$filter: {input: "$events", cond: {$eq: ["$$this.mod", 0]}}},
secondEvent: {$filter: {input: "$events", cond: {$eq: ["$$this.mod", 1]}}}
}
},
{$project: {couples: {$zip: {inputs: ["$firstEvent", "$secondEvent"]}}}}
])
See how it works on the playground example
*With older mongoDB versions, 3.4 or higher, the $mod can be replaces with a "manual" mod calculation.
I need to modify a document inside an array that is inside another array.
I know MongoDB doesn't support multiple '$' to iterate on multiple arrays at the same time, but they introduced arrayFilters for that.
See: https://jira.mongodb.org/browse/SERVER-831
MongoDB's sample code:
db.coll.update({}, {$set: {“a.$[i].c.$[j].d”: 2}}, {arrayFilters: [{“i.b”: 0}, {“j.d”: 0}]})
Input: {a: [{b: 0, c: [{d: 0}, {d: 1}]}, {b: 1, c: [{d: 0}, {d: 1}]}]}
Output: {a: [{b: 0, c: [{d: 2}, {d: 1}]}, {b: 1, c: [{d: 0}, {d: 1}]}]}
Here's how the documents are set:
{
"_id" : ObjectId("5a05a8b7e0ce3444f8ec5bd7"),
"name" : "support",
"contactTypes" : {
"nonWorkingHours" : [],
"workingHours" : []
},
"workingDays" : [],
"people" : [
{
"enabled" : true,
"level" : "1",
"name" : "Someone",
"_id" : ObjectId("5a05a8c3e0ce3444f8ec5bd8"),
"contacts" : [
{
"_id" : ObjectId("5a05a8dee0ce3444f8ec5bda"),
"retries" : "1",
"priority" : "1",
"type" : "email",
"data" : "some.email#email.com"
}
]
}
],
"__v" : 0
}
Here's the schema:
const ContactSchema = new Schema({
data: String,
type: String,
priority: String,
retries: String
});
const PersonSchema = new Schema({
name: String,
level: String,
priority: String,
enabled: Boolean,
contacts: [ContactSchema]
});
const GroupSchema = new Schema({
name: String,
people: [PersonSchema],
workingHours: { start: String, end: String },
workingDays: [Number],
contactTypes: { workingHours: [String], nonWorkingHours: [String] }
});
I need to update a contact. This is what I tried using arrayFilters:
Group.update(
{},
{'$set': {'people.$[i].contacts.$[j].data': 'new data'}},
{arrayFilters: [
{'i._id': mongoose.Types.ObjectId(req.params.personId)},
{'j._id': mongoose.Types.ObjectId(req.params.contactId)}]},
function(err, doc) {
if (err) {
res.status(500).send(err);
}
res.send(doc);
}
);
The document is never updated and I get this response:
{
"ok": 0,
"n": 0,
"nModified": 0
}
What am I doing wrong?
So the arrayFilters option with positional filtered $[<identifier>] does actually work properly with the development release series since MongoDB 3.5.12 and also in the current release candidates for the MongoDB 3.6 series, where this will actually be officially released. The only problem is of course is that the "drivers" in use have not actually caught up to this yet.
Re-iterating the same content I have already placed on Updating a Nested Array with MongoDB:
NOTE Somewhat ironically, since this is specified in the "options" argument for .update() and like methods, the syntax is generally compatible with all recent release driver versions.
However this is not true of the mongo shell, since the way the method is implemented there ( "ironically for backward compatibility" ) the arrayFilters argument is not recognized and removed by an internal method that parses the options in order to deliver "backward compatibility" with prior MongoDB server versions and a "legacy" .update() API call syntax.
So if you want to use the command in the mongo shell or other "shell based" products ( notably Robo 3T ) you need a latest version from either the development branch or production release as of 3.6 or greater.
All this means is that the current "driver" implementation of .update() actually "removes" the necessary arguments with the definition of arrayFilters. For NodeJS this will be addressed in the 3.x release series of the driver, and of course "mongoose" will then likely take some time after that release to implement it's own dependencies on the updated driver, which would then no longer "strip" such actions.
You can however still run this on a supported server instance, by dropping back to the basic "update command" syntax usage, since this bypassed the implemented driver method:
const mongoose = require('mongoose'),
Schema = mongoose.Schema,
ObjectId = mongoose.Types.ObjectId;
mongoose.Promise = global.Promise;
mongoose.set('debug',true);
const uri = 'mongodb://localhost/test',
options = { useMongoClient: true };
const contactSchema = new Schema({
data: String,
type: String,
priority: String,
retries: String
});
const personSchema = new Schema({
name: String,
level: String,
priority: String,
enabled: Boolean,
contacts: [contactSchema]
});
const groupSchema = new Schema({
name: String,
people: [personSchema],
workingHours: { start: String, end: String },
workingDays: { type: [Number], default: undefined },
contactTypes: {
workingHours: { type: [String], default: undefined },
contactTypes: { type: [String], default: undefined }
}
});
const Group = mongoose.model('Group', groupSchema);
function log(data) {
console.log(JSON.stringify(data, undefined, 2))
}
(async function() {
try {
const conn = await mongoose.connect(uri,options);
// Clean data
await Promise.all(
Object.entries(conn.models).map(([k,m]) => m.remove() )
);
// Create sample
await Group.create({
name: "support",
people: [
{
"_id": ObjectId("5a05a8c3e0ce3444f8ec5bd8"),
"enabled": true,
"level": "1",
"name": "Someone",
"contacts": [
{
"type": "email",
"data": "adifferent.email#example.com"
},
{
"_id": ObjectId("5a05a8dee0ce3444f8ec5bda"),
"retries": "1",
"priority": "1",
"type": "email",
"data": "some.email#example.com"
}
]
}
]
});
let result = await conn.db.command({
"update": Group.collection.name,
"updates": [
{
"q": {},
"u": { "$set": { "people.$[i].contacts.$[j].data": "new data" } },
"multi": true,
"arrayFilters": [
{ "i._id": ObjectId("5a05a8c3e0ce3444f8ec5bd8") },
{ "j._id": ObjectId("5a05a8dee0ce3444f8ec5bda") }
]
}
]
});
log(result);
let group = await Group.findOne();
log(group);
} catch(e) {
console.error(e);
} finally {
mongoose.disconnect();
}
})()
Since that sends the "command" directly through to the server, we see the expected update does in fact take place:
Mongoose: groups.remove({}, {})
Mongoose: groups.insert({ name: 'support', _id: ObjectId("5a06557fb568aa0ad793c5e4"), people: [ { _id: ObjectId("5a05a8c3e0ce3444f8ec5bd8"), enabled: true, level: '1', name: 'Someone', contacts: [ { type: 'email', data: 'adifferent.email#example.com', _id: ObjectId("5a06557fb568aa0ad793c5e5") }, { _id: ObjectId("5a05a8dee0ce3444f8ec5bda"), retries: '1', priority: '1', type: 'email', data: 'some.email#example.com' } ] } ], __v: 0 })
{ n: 1,
nModified: 1,
opTime:
{ ts: Timestamp { _bsontype: 'Timestamp', low_: 3, high_: 1510364543 },
t: 24 },
electionId: 7fffffff0000000000000018,
ok: 1,
operationTime: Timestamp { _bsontype: 'Timestamp', low_: 3, high_: 1510364543 },
'$clusterTime':
{ clusterTime: Timestamp { _bsontype: 'Timestamp', low_: 3, high_: 1510364543 },
signature: { hash: [Object], keyId: 0 } } }
Mongoose: groups.findOne({}, { fields: {} })
{
"_id": "5a06557fb568aa0ad793c5e4",
"name": "support",
"__v": 0,
"people": [
{
"_id": "5a05a8c3e0ce3444f8ec5bd8",
"enabled": true,
"level": "1",
"name": "Someone",
"contacts": [
{
"type": "email",
"data": "adifferent.email#example.com",
"_id": "5a06557fb568aa0ad793c5e5"
},
{
"_id": "5a05a8dee0ce3444f8ec5bda",
"retries": "1",
"priority": "1",
"type": "email",
"data": "new data" // <-- updated here
}
]
}
]
}
So right "now"[1] the drivers available "off the shelf" don't actually implement .update() or it's other implementing counterparts in a way that is compatible with actually passing through the necessary arrayFilters argument. So if you are "playing with" a development series or release candiate server, then you really should be prepared to be working with the "bleeding edge" and unreleased drivers as well.
But you can actually do this as demonstrated in any driver, in the correct form where the command being issued is not going to be altered.
[1] As of writing on November 11th 2017 there is no "official" release of MongoDB or the supported drivers that actually implement this. Production usage should be based on official releases of the server and supported drivers only.
I had a similar use case. But my second level nested array doesn't have a key. While most examples out there showcase an example with arrays having a key like this:
{
"id": 1,
"items": [
{
"name": "Product 1",
"colors": ["yellow", "blue", "black"]
}
]
}
My use case is like this, without the key:
{
"colors": [
["yellow"],
["blue"],
["black"]
]
}
I managed to use the arrayfilters by ommiting the label of the first level of the array nest. Example document:
db.createCollection('ProductFlow')
db.ProductFlow.insertOne(
{
"steps": [
[
{
"actionType": "dispatch",
"payload": {
"vehicle": {
"name": "Livestock Truck",
"type": "road",
"thirdParty": true
}
}
},
{
"actionType": "dispatch",
"payload": {
"vehicle": {
"name": "Airplane",
"type": "air",
"thirdParty": true
}
}
}
],
[
{
"actionType": "store",
"payload": {
"company": "Company A",
"is_supplier": false
}
}
],
[
{
"actionType": "sell",
"payload": {
"reseller": "Company B",
"is_supplier": false
}
}
]
]
}
)
In my case, I want to:
Find all documents that have any steps with payload.vehicle.thirdParty=true and actionType=dispatch
Update the actions set payload.vehicle.thirdParty=true only for the actions that have actionType=dispatch.
My first approach was withour arrayfilters. But it would create the property payload.vehicle.thirdParty=true inside the steps with actionType store and sell.
The final query that updated the properties only inside the steps with actionType=dispatch:
Mongo Shell:
db.ProductFlow.updateMany(
{"steps": {"$elemMatch": {"$elemMatch": {"payload.vehicle.thirdParty": true, "actionType": "dispatch"}}}},
{"$set": {"steps.$[].$[i].payload.vehicle.thirdParty": false}},
{"arrayFilters": [ { "i.actionType": "dispatch" } ], multi: true}
)
PyMongo:
query = {
"steps": {"$elemMatch": {"$elemMatch": {"payload.vehicle.thirdParty": True, "actionType": "dispatch"}}}
}
update_statement = {
"$set": {
"steps.$[].$[i].payload.vehicle.thirdParty": False
}
}
array_filters = [
{ "i.actionType": "dispatch" }
]
NOTE that I'm omitting the label on the first array at the update statement steps.$[].$[i].payload.vehicle.thirdParty. Most examples out there will use both labels because their objects have a key for the array. I took me some time to figure that out.
Suppose I have a document of the following prototype.
{
cust_id: "abc123",
ord_date: ISODate("2012-11-02T17:04:11.102Z"),
status: 'A',
price: 50,
items: [
{ sku: "xxx", qty: 25, price: 1 },
{ sku: "yyy", qty: 25, price: 1 }
]
}
My requirement is to get the total price for SKU "XXX" which is 50 * 25 (Price times quantity). How can I achieve this query's result in MONGODB?
db.YOUR_COLLECTION.aggregate({
$match: {
items.sku: "xxx"
},
$project: {
"product": {$multiply: ["$items.qty","$items.price"]},
_id: 0
}
});
I am able to achieve the solution to this by separating the query into two blocks as below.
var pipeline1 = [
{
{
"$unwind": "$items"
},
$match: {
items.sku: "xxx"
},
$project: {
"product":
{
$multiply: ["$items.qty","$items.price"]
},
_id: 0
}
}];
R = db.tb.aggregate( pipeline );