mongo : update property of specific element in array - node.js

I have this collection :
{
"_id" : ObjectId("5ac69e90a9d1a5f3e01a5233"),
"category": "spain",
"products" : [
{
"label" : "uno"
},
{
"label" : "dos"
},
{
"label" : "tres"
}
]
},
{
"_id" : ObjectId("5ac69e90a9d1a5f3e01a5234"),
"category": "england",
"products" : [
{
"label" : "one"
},
{
"label" : "two"
},
{
"label" : "three"
}
]
}
I want to do the following operation : update the label from "one" to "four" of the object with the category england. But I have some troubles to design the most elegant and performant solution :
first solution : I could copy paste and rewrite the entire document with just replacing the one by four
second solution where I struggle : I would like to find the element with label equals to one and updates it to four, but I don't know how to do. I don't want to use mongo path index like 'products.O.label' because I can't garantee that the product with label one will be at position 0 in the products array.
Thanks in advance

You could use this one:
db.collection.updateMany(
{ category: "england" },
{ $set: { "products.$[element].label": "four" } },
{ arrayFilters: [{ "element.label": "one" }] }
)
If you prefer and aggregation pipeline it would be this one:
db.collection.updateMany(
{ category: "england" },
[{
$set: {
products: {
$map: {
input: "$products",
in: {
$cond: {
if: { $eq: ["$$this.label", "one"] },
then: { label: "four" },
else: "$$this"
}
}
}
}
}
}]
)
but it might be an overkill, in my opinion.

Further, referring to #Wernfried Domscheit, another way using aggregation.
> db.catg1.find();
{ "_id" : ObjectId("5ac69e90a9d1a5f3e01a5233"), "category" : "spain", "products" : [ { "label" : "uno" }, { "label" : "dos" }, { "label" : "tres" } ] }
{ "_id" : ObjectId("5ac69e90a9d1a5f3e01a5234"), "category" : "england", "products" : [ { "label" : "four" }, { "label" : "two two" }, { "label" : "three" } ] }
> db.catg1.aggregate([
... {$unwind:"$products"},
... {$match:{category:"england",
... "products.label":"four"
... }
... },
... ]).forEach(function(doc){
... print(doc._id);
... db.catg1.update(
... {"_id":doc._id},
... { $set:{"products.$[element].label":"one"}},
... {arrayFilters: [{"element.label":"four"}]}
... );
... });
ObjectId("5ac69e90a9d1a5f3e01a5234")
> db.catg1.find();
{ "_id" : ObjectId("5ac69e90a9d1a5f3e01a5233"), "category" : "spain", "products" : [ { "label" : "uno" }, { "label" : "dos" }, { "label" : "tres" } ] }
{ "_id" : ObjectId("5ac69e90a9d1a5f3e01a5234"), "category" : "england", "products" : [ { "label" : "one" }, { "label" : "two two" }, { "label" : "three" } ] }
> db.version();
4.2.6
>

Related

Mongo: filter documents from multiple collections and merge

I am new to mongo and NodeJS and have a use case where I want to get filtered results from multiple collection.
Advance apologies for the long post.
for ex:
collectionA
{
"_id" : "foo#gmail.com",
"name" : "Foo",
"location" : {
"coordinates" : [
-122.420170,
37.780080
],
"type" : "Point"
}
},
{
"_id" : "bar#gmail.com,
"name" : "Bar",
"location" : {
"coordinates" : [
-122.420060,
37.780180
],
"type" : "Point"
}
}
collectionB: Some attributes are not present for all the documents and hence optional
{
"_id" : "foo#gmail.com"
"AttributeA" : [
{
"name" : "AttA_Name",
"val" : "Coll_B_AttA_Val_Foo"
},
{
"name" : "AttA_Name1",
"val" : "Coll_B_AttA_Val_Foo"
}]
},
{
"_id" : "bar#gmail.com"
"AttributeA" : [
{
"name" : "AttA_Name",
"val" : "Coll_B_AttA_Val_Bar"
},
{
"name" : "AttA_Name2",
"val" : "Coll_B_AttA_Val_Bar"
}
],
"AttributeB" : [
{
"name" : "AttB_Name",
"val" : "Coll_B_AttB_Val_Bar"
}
]
}
CollectionC: Some attributes are not present for all the documents and hence optional
{
"_id" : "foo#gmail.com"
"AttributeA" : [
{
"name" : "Coll_C_AttA_Name",
"val" : "Coll_C_AttA_Val_Foo"
}]
},
{
"_id" : "bar#gmail.com"
"AttributeA" : [
{
"name" : "Coll_C_AttA_Name",
"val" : "Coll_C_AttA_Val_Bar"
}
],
"AttributeB" : [
{
"name" : "Coll_C_AttB_Name",
"val" : "Coll_C_AttB_Val_Bar"
}
]
}
I know Collection B and C schema looks the same but the purpose is different and they have to be different. DB design is not the question so I would appreciate if do not put all the focus on it.
Query:
Assume there is another user (Alan) with same attributes present as Bar that exist in the collection but is not living nearby the location of Bar.
The query I am trying to build on top of these is,
Find people living nearby from CollectionA
And Collection B, if AttributeA exist and have an element with name: AttA_Name
And in Collection C, if AttributeA exist and have an name: Coll_C_AttA_Name
In the above case I am expecting a result as
{
"_id" : "foo#gmail.com",
"name" : "Foo",
"location" : {
"coordinates" : [
-122.420170,
37.780080
],
"type" : "Point"
},
"collectionB_AttributeA" : [
{
"name" : "AttA_Name",
"val" : "Coll_B_AttA_Val_Foo"
},
{
"name" : "AttA_Name1",
"val" : "Coll_B_AttA_Val_Foo"
}]
,
"collectionC_AttributeA" : [
{
"name" : "Coll_C_AttA_Name",
"val" : "Coll_C_AttA_Val_Foo"
}]
},
{
"_id" : "bar#gmail.com,
"name" : "Bar",
"location" : {
"coordinates" : [
-122.420060,
37.780180
],
"type" : "Point"
},
"collectionB_AttributeA":[
{
"name" : "AttA_Name",
"val" : "Coll_B_AttA_Val_Bar"
},
{
"name" : "AttA_Name2",
"val" : "Coll_B_AttA_Val_Bar"
}
],
"collectionC_AttributeA":[
{
"name" : "Coll_C_AttA_Name",
"val" : "Coll_C_AttA_Val_Bar"
}
]
}
There is one way of doing is in parts:
query Collection A and get the nearby people
Loop through the result of 1 and find in CollectionB if they have AttributeA and an element with name AttA_Name and eliminate if they don't match.
Loop through the filtered results from 2 and find in CollectionC if they have AttributeA and and element with name Coll_C_AttA_Name and if they don't eliminate such documents.
Is there a way I can use aggregate to build this query as one? I tried reading and trying the aggregate but seems like my understanding is incomplete.
let result = await CollectionASchema.aggregate([
{
$geoNear: {
near: { type: "Point", coordinates: [ Number(long) , Number(lat) ] },
distanceField: "dist.calculated",
minDistance: 0,
maxDistance: radiusinmetres,
spherical: true
}
},
{
$lookup:
{
from: 'collectionB',
pipeline: [
{ $match : { $and: [{ AttributeA :{$exists: true}}, { [category]: { $elemMatch: { name: “AttA_Name” } } }] }},
{ $project: { AttributeA: 0 } }
],
as: "collectionB_AttributeA"
}
}
])
If you can explain if this is possible or let me know off this is the right approach that would be helpful.

how to get data in mongoose where last element in array?

how to get data in mongoose where last element in array?
I have data looks like this:
[
{
"_id" : ObjectId("5b56eb3deb869312d85a8e69"),
"transactionStatus" : [
{
"status" : "pending",
"createdAt" : ISODate("2018-07-24T09:02:53.347Z")
},
{
"status" : "process",
"createdAt" : ISODate("2018-07-24T09:02:53.347Z")
}
]
},
{
"_id" : ObjectId("5b56eb3deb869312d8589765"),
"transactionStatus" : [
{
"status" : "pending",
"createdAt" : ISODate("2018-07-24T09:02:53.347Z")
},
{
"status" : "process",
"createdAt" : ISODate("2018-07-24T09:03:30.347Z")
},
{
"status" : "done",
"createdAt" : ISODate("2018-07-24T09:04:22.347Z")
}
]
}
]
And, I want to get data above where last object transactionStatus.status = process, so the result should be:
{
"_id" : ObjectId("5b56eb3deb869312d85a8e69"),
"transactionStatus" : [
{
"status" : "pending",
"createdAt" : ISODate("2018-07-24T09:02:53.347Z")
},
{
"status" : "process",
"createdAt" : ISODate("2018-07-24T09:02:53.347Z")
}
]
}
how to do that with mongoose?
You can use $expr (MongoDB 3.6+) inside of match. Using $let and $arrayElemAt passing -1 as second argument you can get the last element as a temporary variable and then you can compare the values:
db.col.aggregate([
{
$match: {
$expr: {
$let: {
vars: { last: { $arrayElemAt: [ "$transactionStatus", -1 ] } },
in: { $eq: [ "$$last.status", "process" ] }
}
}
}
}
])
The same result can be achieved for lower versions of MongoDB using $addFields and $match. You can add $project then to remove that temporary field:
db.col.aggregate([
{
$addFields: {
last: { $arrayElemAt: [ "$transactionStatus", -1 ] }
}
},
{
$match: { "last.status": "process" }
},
{
$project: { last: 0 }
}
])
//Always update new status at Position 0 using $position operator
db.update({
"_id": ObjectId("5b56eb3deb869312d85a8e69")
},
{
"$push": {
"transactionStatus": {
"$each": [
{
"status": "process",
"createdAt": ISODate("2018-07-24T09:02:53.347Z")
}
],
"$position": 0
}
}
}
)
//Your Query for checking first element status is process
db.find(
{
"transactionStatus.0.status": "process"
}
)
refer $position, $each

How to use aggregation correctly in MongoDB with embbeded documents?

I have a collection with folowing data:
{
"_id" : ObjectId("5b5066b716d3112cfc2a5deb"),
"username" : "admin",
"password" : "123456",
"token" : "0123",
"bots" : [
{
"name" : "mybot",
"installations" : [
{
"date" : ISODate("2018-07-19T10:23:51.774Z")
},
{
"date" : ISODate("2018-07-19T10:23:51.774Z")
}
],
"commands" : [
{
"name" : "read",
"date" : ISODate("2018-07-19T10:23:51.774Z")
},
{
"name" : "answer",
"date" : ISODate("2018-07-19T10:23:51.774Z")
},
{
"name" : "get",
"date" : ISODate("2018-07-19T11:55:28.858Z")
},
{
"name" : "get",
"date" : ISODate("2018-07-19T11:56:47.419Z")
},
{
"name" : "get",
"date" : ISODate("2018-07-19T11:56:48.499Z")
},
{
"name" : "get",
"date" : ISODate("2018-07-19T11:56:49.089Z")
}
]
}
]
},
{
"_id" : ObjectId("5b50bbfe3ed35b6f2bde6923"),
"username" : "user",
"password" : "123456",
"token" : "44444",
"bots" : [
{
"name" : "anotherBotName",
"installations" : [
{
"date" : ISODate("2018-07-19T16:27:42.012Z")
},
{
"date" : ISODate("2018-07-19T16:27:42.012Z")
}
],
"commands" : [
{
"name" : "update",
"date" : ISODate("2018-07-19T16:27:42.012Z")
},
{
"name" : "update",
"date" : ISODate("2018-07-19T16:27:42.012Z")
}
]
}
]
}
I want to execute SQL-equivalent query
SELECT commands.name, COUNT(commands.name), GROUP BY commands.name
and get a result like:
[
{update: 2},
{get: 4},
{read: 1},
{answer: 1}
]
but when I execute this query in mongo:
.collection(collectionName).aggregate({{'$group': {_id: "$bots.commands.name",count:{$sum:1}}}
}).toArray(callback)
I get such a result:
[
{
_id: [
[ 'test', 'test1' ]
],
count: 1
},
{
_id: [
[ 'read', 'answer', 'get', 'get', 'get', 'get' ]
],
count: 1
}
]
I googled and read about agregation in MongoDB and still don't get much. It's hard to move from SQL to NoN-SQL database
My questions are:
Why my query shows not the result I want to see?
How to fix it?
Thanks in advance!
Since you have two nested arrays in your schema you should use $unwind operator twice before you apply your $group. After $unwind you'll get separate document for each name. Try:
db.col.aggregate([
{
$unwind: "$bots"
},
{
$unwind: "$bots.commands"
},
{
$group: {
_id: "$bots.commands.name",
count: { $sum: 1 }
}
},
{
$replaceRoot: {
newRoot: {
$let: {
vars: { obj: [ { k: "$_id", v: "$count" } ] },
in: { $arrayToObject: "$$obj" }
}
}
}
}
])
In the last stage you can use $replaceRoot with $arrayToObject to set _id as keys in your final objects.
Outputs:
{ "update" : 2 }
{ "get" : 4 }
{ "answer" : 1 }
{ "read" : 1 }

Get array elements across all documents in the collection that match a specific array element content

I have the following document structure in my MongoDB and I am trying to return an array of objects containing all prices for itemID "5a59c587fa9b4a212b0a1312" across all documents using the following query but unfortunately it is always returning an empty array. Can someone please advice what I might be doing wrong here? and how I can get such a result?
Note: I am using promised-mongo in a Node.js app to access my MongoDB
Query I tried:
{ transDetails: { $elemMatch: { itemID: "5a59c587fa9b4a212b0a1312" } } }
DB sample:
{
"_id" : ObjectId("5a688e7ea52deb6d4a6b6663"),
"transactionID" : "1",
"transDetails" : [
{
"itemID" : "5a59c587fa9b4a212b0a1312",
"price" : "22"
},
{
"itemID" : "5a59c95b081c6c612bd17058",
"price" : "24"
}
] }
{
"_id" : ObjectId("5a6aa99a52deb6d4a67714"),
"transactionID" : "2",
"transDetails" : [
{
"itemID" : "5a59c587fa9b4a212b0a1312",
"price" : "35"
},
{
"itemID" : "5a59c95b081c6c612bd17058",
"price" : "24"
}
] }
Find with projection to have only matched items in the transDetails:
.find({"transDetails.itemID": "5a59c587fa9b4a212b0a1312"}, {_id:0, "transDetails.$": 1})
Will return
{
"transDetails" : [
{
"itemID" : "5a59c587fa9b4a212b0a1312",
"price" : "22"
}
]
},
{
"transDetails" : [
{
"itemID" : "5a59c587fa9b4a212b0a1312",
"price" : "35"
}
]
},
....
Wish you re-shape the documents, you can use aggregation:
.aggregate([
{ $match: { "transDetails.itemID": "5a59c587fa9b4a212b0a1312" } },
{ $project: {
_id: 0,
transDetails: {
$filter: {
input: "$transDetails",
as: "item",
cond: { $eq: [ "$$item.itemID", "5a59c587fa9b4a212b0a1312" ] }
}
}
} },
{ $unwind: "$transDetails"},
{ $project: {price: "$transDetails.price"}}
])
Which will give you
{
"price" : "22"
},
{
"price" : "35"
},
...

MongoDB aggregate on Nested data

I have nested data as below,
{
"_id" : ObjectId("5a30ee450889c5f0ebc21116"),
"academicyear" : "2017-18",
"fid" : "be02",
"fname" : "ABC",
"fdept" : "Comp",
"degree" : "BE",
"class" : "1",
"sem" : "8",
"dept" : "Comp",
"section" : "Theory",
"subname" : "BDA",
"fbValueList" : [
{
"_id" : ObjectId("5a30eecd3e3457056c93f7af"),
"score" : 20,
"rating" : "Fair"
},
{
"_id" : ObjectId("5a30eefd3e3457056c93f7b0"),
"score" : 10,
"rating" : "Fair"
},
{
"_id" : ObjectId("5a337e53341bf419040865c4"),
"score" : 88,
"rating" : "Excellent"
},
{
"_id" : ObjectId("5a337ee2341bf419040865c7"),
"score" : 75,
"rating" : "Very Good"
},
{
"_id" : ObjectId("5a3380b583dde50ddcea350e"),
"score" : 72,
"rating" : "Very Good"
}
]
},
{
"_id" : ObjectId("5a3764f1bc19b77dd9fd9a57"),
"academicyear" : "2017-18",
"fid" : "be02",
"fname" : "ABC",
"fdept" : "Comp",
"degree" : "BE",
"class" : "1",
"sem" : "5",
"dept" : "Comp",
"section" : "Theory",
"subname" : "BDA",
"fbValueList" : [
{
"_id" : ObjectId("5a3764f1bc19b77dd9fd9a59"),
"score" : 88,
"rating" : "Excellent"
},
{
"_id" : ObjectId("5a37667aee64bce1b14747d2"),
"score" : 74,
"rating" : "Good"
},
{
"_id" : ObjectId("5a3766b3ee64bce1b14747dc"),
"score" : 74,
"rating" : "Good"
}
]
}
We are trying to perform aggregation using this,
db.fbresults.aggregate([{$match:{academicyear:"2017-18",fdept:'Comp'}},{$group:{_id: {fname: "$fname", rating:"$fbValueList.rating"},count: {"$sum":1}}}])
and we get result like,
{ "_id" : { "fname" : "ABC", "rating" : [ "Fair","Fair","Excellent","Very Good", "Very Good", "Excellent", "Good", "Good" ] }, "count" : 2 }
but we are expecting result like,
{ "_id" : { "fname" : "ABC", "rating_group" : [
{
rating: "Excellent"
count: 2
},
{
rating: "Very Good"
count: 2
},
{
rating: "Good"
count: 2
},
{
rating: "Fair"
count: 2
},
] }, "count" : 2 }
We want to get individual faculty group by their name and inside that group by their rating response and count of rating.
We have already tried this one but we did not the result.
Mongodb Aggregate Nested Group
This should get you going:
db.collection.aggregate([{
$match: {
academicyear: "2017-18",
fdept:'Comp'
}
}, {
$unwind: "$fbValueList" // flatten the fbValueList array into multiple documents
}, {
$group: {
_id: {
fname: "$fname",
rating:"$fbValueList.rating"
},
count: {
"$sum": 1 // this will give us the count per combination of fname and fbValueList.rating
}
}
}, {
$group: {
_id: "$_id.fname", // we only want one bucket per fname
rating_group: {
$push: { // we push the exact structure you were asking for
rating: "$_id.rating",
count: "$count"
}
},
count: {
$avg: "$count" // this will be the average across all entries in the fname bucket
}
}
}])
This is a long aggregation pipeline, there may be some aggregations that are un-necessary, so please check and discard whichever are irrelevant.
NOTE: This will only work with Mongo 3.4+.
You need to use $unwind and then $group and $push ratings with their counts.
matchAcademicYear = {
$match: {
academicyear:"2017-18", fdept:'Comp'
}
}
groupByNameAndRating = {
$group: {
_id: {
fname: "$fname", rating:"$fbValueList.rating"
},
count: {
"$sum":1
}
}
}
unwindRating = {
$unwind: "$_id.rating"
}
addFullRating = {
$addFields: {
"_id.full_rating": "$count"
}
}
replaceIdRoot = {
$replaceRoot: {
newRoot: "$_id"
}
}
groupByRatingAndFname = {
$group: {
_id: {
"rating": "$rating",
"fname": "$fname"
},
count: {"$sum": 1},
full_rating: {"$first": "$full_rating"}
}
}
addFullRatingAndCount = {
$addFields: {
"_id.count": "$count",
"_id.full_rating": "$full_count"
}
}
groupByFname = {
$group: {
_id: "$fname",
rating_group: { $push: {rating: "$rating", count: "$count"}},
count: { $first: "$full_rating"}
}
}
db.fbresults.aggregate([
matchAcademicYear,
groupByNameAndRating,
unwindRating,
addFullRating,
unwindRating,
replaceIdRoot,
groupByRatingAndFname,
addFullRatingAndCount,
replaceIdRoot,
groupByFname
])

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