I have a collection with documents such as these.
What I want to do is get all distinct clusters coming from the document with the highest (recent) lastupdate field.
I think this should be the output:
[
"19":"Income2",
"20":"Income Modified",
"21":"Income Modified"
]
Please try this :
db.yourCollection.aggregate([{ $unwind: '$meta.clusters' },
{ $project: { '_id': { $objectToArray: '$meta.clusters' }, 'last_update': 1 } }, { $sort: { 'last_update': -1 } },
{ $group: { _id: '$_id.k', values: { $first: '$$ROOT' } } }, { $sort: { 'values.last_update': -1 } },
{ $replaceRoot: { 'newRoot': '$values' } },
{ $group: { _id: '', distinctCLusters: { $push: { $arrayToObject: "$_id" } } } }, { $project: { _id: 0 } }])
Output with provided data:
{
"distinctCLusters" : [
{
"21" : "Income Modified"
},
{
"19" : "Income2"
},
{
"20" : "Income Modified"
}
]
}
Related
I am running the following aggregation pipeline:
const agg = [
{
'$match': {
'aaa': 'bbb'
}
}, {
'$group': {
'_id': '',
'total': {
'$sum': '$num'
}
}
}
];
My problem is, when $match matches nothing, the pipeline returns 0 documents. How do I get the pipeline to always return 1 document?
In MongoDB version 6.0 you can do it like this one:
db.collection.aggregate([
{ $match: { aaa: 'bbb' } },
{
$group: {
_id: null,
total: { $sum: "$num" }
}
},
{
$densify: {
field: "total",
range: { step: 1, bounds: [0, 0] }
}
},
{ $set: { _id: { $cond: [{ $eq: [{ $type: "$_id" }, "missing"] }, MaxKey, "$_id"] } } },
{ $sort: { _id: 1 } },
{ $limit: 1 }
])
In version < 6.0 you can try this one:
db.collection.aggregate([
{
$facet: {
data: [
{ $match: { aaa: 'bbb' } },
{ $group: { _id: null, total: { $sum: "$num" } } }
],
default: [
{ $limit: 1 },
{ $group: { _id: null, total: { $sum: 0 } } },
{ $set: { _id: MaxKey } }
]
}
},
{ $replaceWith: { $mergeObjects: [{ $first: "$default" }, { $first: "$data" }] } },
])
Or this one:
db.collection.aggregate([
{ $match: { aaa: 'bbb' } },
{ $group: { _id: null, total: { $sum: "$num" } } },
{
$unionWith: {
coll: "collection",
pipeline: [
{ $limit: 1 },
{ $set: { _id: MaxKey, total: 0 } },
{ $project: { _id: 1, total: 1 } }
]
}
},
{ $sort: { _id: 1 } },
{ $limit: 1 }
])
I've created an aggregate query but for some reason it doesn't seem to work for custom fields created in the aggregation pipeline.
return this.repository.mongo().aggregate([
{
$match: { q1_avg: { $regex: baseQuery['value'], $options: 'i' } }, // NOT WORKING
},
{
$group: {
_id: '$product_sku',
id: { $first: "$_id" },
product_name: { $first: '$product_name' },
product_category: { $first: '$product_category' },
product_sku: { $first: '$product_sku' },
q1_cnt: { $sum: 1 },
q1_votes: { $push: "$final_rating" }
},
},
{
$facet: {
pagination: [ { $count: 'total' } ],
data: [
{
$project: {
_id: 1,
id: 1,
product_name: 1,
product_category: 1,
product_sku: 1,
q1_cnt: 1,
q1_votes: {
$filter: {
input: '$q1_votes',
as: 'item',
cond: { $ne: ['$$item', null] }
}
},
},
},
{
$set: {
q1_avg: { $round: [ { $avg: '$q1_votes' }, 2 ] },
}
},
{ $unset: ['q1_votes'] },
{ $skip: skip },
{ $limit: limit },
{ $sort: sortList }
]
}
},
{ $unwind : "$pagination" },
]).next();
q1_avg value is an integer and as far as I know, regex only works with strings. Could that be the reason
I have a collection that looks like below:
[
{
"orderNum": "100",
"createdTime": ISODate("2020-12-01T21:00:00.000Z"),
"amount": 100,
"memo": "100memo",
"list": [
1
]
},
{
"orderNum": "200",
"createdTime": ISODate("2020-12-01T21:01:00.000Z"),
"amount": 200,
"memo": "200memo",
"list": [
1,
2
]
},
{
"orderNum": "300",
"createdTime": ISODate("2020-12-01T21:02:00.000Z"),
"amount": 300,
"memo": "300memo"
},
{
"orderNum": "400",
"createdTime": ISODate("2020-12-01T21:03:00.000Z"),
"amount": 400,
"memo": "400memo"
},
]
and I'm trying to get the total amount of orders that were created before order# 300 (so order#100 and #200, total amount is 300).
Does anyone know how to get it via Mongoose?
You can use this one:
db.collection.aggregate([
{ $sort: { orderNum: 1 } }, // by default the order of documents in a collection is undetermined
{ $group: { _id: null, data: { $push: "$$ROOT" } } }, // put all documents into one document
{ $set: { data: { $slice: ["$data", { $indexOfArray: ["$data.orderNum", "300"] }] } } }, // cut desired elementes from array
{ $unwind: "$data" }, // transform back to documents
{ $replaceRoot: { newRoot: "$data" } },
{ $group: { _id: null, total_amount: { $sum: "$amount" } } } // make summary
])
Actually it is not needed to $unwind and $group, so the shortcut would be this:
db.collection.aggregate([
{ $sort: { orderNum: 1 } },
{ $group: { _id: null, data: { $push: "$$ROOT" } } },
{ $set: { data: { $slice: ["$data", { $indexOfArray: ["$data.orderNum", "300"] }] } } },
{ $project: { total_amount: { $sum: "$data.amount" } } }
])
But the answer from #turivishal is even better.
Update for additional field
{
$set: {
data: { $slice: ["$data", { $indexOfArray: ["$data.orderNum", "300"] }] },
memo: { $arrayElemAt: [ "$data.memo", { $indexOfArray: ["$data.orderNum", "300"] } ] }
}
}
or
{ $set: { data: { $slice: ["$data", { $indexOfArray: ["$data.orderNum", "300"] }] } } },
{ $set: { memo: { $last: { "$data.memo" } } },
$match orderNum less than 300
$group by null and get totalAmount using $sum of amount
YourSchemaModel.aggregate([
{ $match: { orderNum: { $lt: "300" } } },
{
$group: {
_id: null,
totalAmount: { $sum: "$amount" }
}
}
])
Playground
I have a sample collection containing users and their departments
db.user.insertMany([
{
"department":"IT",
"firstName":{
"en":"Frodo",
"ru":"Фродо"
},
"lastName":{
"en":"Baggins",
"ru":"Беггинс"
}
},
{
"department":"IT",
"firstName":{
"en":"Bilbo",
"ru":"Билбо"
},
"lastName":{
"en":"Baggins",
"ru":"Беггинс"
}
},
{
"department":"Marketing",
"firstName":{
"en":"Merry",
"ru":"Мери"
},
"lastName":{
"en":"Brandybuck",
"ru":"Брендибак"
}
},
{
"department":"Marketing",
"firstName":{
"en":"Pippin",
"ru":"Пипин"
},
"lastName":{
"en":"Took",
"ru":"Тук"
}
}
])
Now what I want to do, is to query them grouped by the department, and apply localization.
So the desired output is
{
"IT":[
{
"_id":"5e808532ed036001cb7fe366",
"firstName":"Frodo",
"lastName":"Baggins"
},
{
"_id":"5e808532ed036001cb7fe367",
"firstName":"Bilbo",
"lastName":"Baggins"
}
],
"Marketing":[
{
"_id":"5e808532ed036001cb7fe368",
"firstName":"Merry",
"lastName":"Brandybuck"
},
{
"_id":"5e808532ed036001cb7fe369",
"firstName":"Pippin",
"lastName":"Took"
}
]
}
I have the following query which applies localization
db.user.aggregate([
{
$project: {
_id: '$_id',
firstName: '$firstName.en',
lastName: '$lastName.en'
}
}
]).pretty()
I looked through the $group documentation, but it seems to require an aggregate function, which is not what I need. How should I group the data?
You have to use $group.
db.collection.aggregate([
{
$group: {
_id: "$department",
data: {
$push: {
_id: "$_id",
firstName: "$firstName",
lastName: "$lastName"
}
}
}
},
{
$group: {
_id: null,
data: {
$push: {
k: "$_id",
v: "$data"
}
}
}
},
{
$replaceRoot: {
newRoot: {
$arrayToObject: "$data"
}
}
}
])
Playground
I have the data like below:
{
"order_id" : 1234567,
"order_pay_time" : 1437373297,
"pay_info" : [
{
"pay_type" : 0,
"pay_time" : 1437369046
},
{
"pay_type" : 0,
"pay_time" : 1437369123
},
{
"pay_type" : 0,
"pay_time" : 1437369348
}
]}
what I want to get is the last payment is of type 1, but $elemMatch just match the list where pay_type:1 exists, how can I match the orders which last payment is of "pay_type" : 1
You can use aggregation to get expected output. The query will be like following:
db.collection.aggregate({
$unwind: "$pay_info"
}, {
$match: {
"pay_info.pay_type": 1
}
}, {
$group: {
_id: "$_id",
"pay_info": {
$push: "$pay_info"
},
"order_id": {
$first: "$order_id"
},
"order_pay_time": {
$first: "$order_pay_time"
}
}
})
Moreover if you want latest pay_info.pay_time then you can sort it by descending order with limit 1, some what like following:
db.collection.aggregate({
$unwind: "$pay_info"
}, {
$match: {
"pay_info.pay_type": 1
}
}, {
$sort: {
"pay_info.pay_time": -1
}
}, {
$limit: 1
}, {
$group: {
_id: "$_id",
"pay_info": {
$push: "$pay_info"
},
"order_id": {
$first: "$order_id"
},
"order_pay_time": {
$first: "$order_pay_time"
}
}
})
Edit
Also you can use $redact to avoid $unwind like following:
db.collection.aggregate({
$match: {
"pay_info": {
$elemMatch: {
"pay_type": 1
}
}
}
}, {
$sort: {
"pay_info.pay_time": -1
}
}, {
$limit: 1
}, {
$redact: {
$cond: {
if: {
$eq: [{
"$ifNull": ["$pay_type", 1]
}, 1]
},
then: "$$DESCEND",
else: "$$PRUNE"
}
}
}).pretty()
Just found this thread for a similar problem I've had.
I ended up doing this, maybe that will be of interest to someone:
db.collection.find({
$where: function(){
return this.pay_info[this.pay_info.length-1].pay_type === 1
}
})