Hi i am mentioning the sample data
///collection - test////
{
"_id" : {
"date" : ISODate("2020-02-11T17:00:00Z"),
"userId" : ObjectId("5e43e5cdc11f750864f46820"),
"adminId" : ObjectId("5e43de778b57693cd46859eb")
},
"outstanding" : 212.39999999999998,
"totalBill" : 342.4,
"totalPayment" : 130
}
{
"_id" : {
"date" : ISODate("2020-02-11T17:00:00Z"),
"userId" : ObjectId("5e43e73169fe1e3fc07eb7c5"),
"adminId" : ObjectId("5e43de778b57693cd46859eb")
},
"outstanding" : 797.8399999999999,
"totalBill" : 797.8399999999999,
"totalPayment" : 0
}
I need to structure a query which does following things-
I need to calculate the actualOutstanding:[(totalBill+outstanding)-totalPayment],
I need to save this actualOutstanding in the same collection & in the same document according to {"_id" : {"date","userId", "adminId" }}
NOTE: userId is different in both the documents.
Introduced in Mongo version 4.2+ pipelined updates, meaning we can now use aggregate expressions to update documents.
db.collection.updateOne(
{
"adminId" : ObjectId("5e43de778b57693cd46859eb")
'_id."userId" : ObjectId("5e43e73169fe1e3fc07eb7c5"),
'_id.date': ISODate("2020-02-11T18:30:00Z"),
},
[
{ '$set': {
actualOutstanding: {
$subtract:[ {$add: ['$totalBill','$outstanding']},'$totalPayment']
}
} }
]);
For any other Mongo version you have to split it into 2 actions, first query and calculate then update the document with the calculation.
Related
Two documents containing ObjectId("6148a371c13a6a0be492ebf4")
Document 1
{
"_id" : ObjectId("6144f66fb9543917f96fc"),
"refId" : "ford",
"template" : "6144f61cb96d772317f96f9",
"fieldValues" : {
"PDV" : [
"6126938cd24a8aa3d37b4992",
ObjectId("6148a371c13a6a0be492ebf4")
]
},
"group" : ObjectId("6144f66fb96d7731917f96fd"),
"createdAt" : ISODate("2021-09-17T20:11:27.440Z"),
"updatedAt" : ISODate("2021-09-20T15:06:26.146Z"),
"__v" : 0
}
Document 2
{
"_id" : ObjectId("6144f66fb96d77rr3217f96fc"),
"refId" : "CCM",
"template" : "6144f613296d7731917f96f9",
"fieldValues" : {
"DDB" : [
"6126938cd2448aa3d37b4992",
"5443938cd2448aa3d37b4992",
ObjectId("6148a371c13a6a0be492ebf4"),
]
},
"group" : ObjectId("6144f66fb96de431917f96fd"),
"createdAt" : ISODate("2021-09-17T20:11:27.440Z"),
"updatedAt" : ISODate("2021-09-20T15:06:26.146Z"),
"__v" : 0
}
ObjectId that we looking for is always inside fieldValues but instead of PDV or DDB we will always have the different naming.
So we can't use this type of query:
db.getCollection('products').find({"fieldValues.PDV":ObjectId('6148a371c13a6a0be492ebf4')})
PS. This query should work only on DB, we can't afford to query all products and do calculation on backend there might to be a millions of products.
You can use this one:
db.collection.aggregate([
{
$set: {
kv: { $first: { $objectToArray: "$fieldValues" } }
}
},
{ $match: { "kv.v": ObjectId("6148a371c13a6a0be492ebf3") } },
{ $unset: "kv" }
])
Mongo Playground
db.products.find({'_id': ObjectId("6148a371c13a6a0be492ebf4")})
The mistake in your code is that you used key instead of _id.
This way of writing it is much easier on the fingers though.
You'd think a solution like this would work but one reason why this may not is because you're trying to use === on an object. If you refer to this thread, it might help if you use .equals() instead of ===.
I have data in a collection ex:"jobs". I am trying to copy specific data from "jobs" after every 2 hours to a new collection (which may not exist initially) and also add a new key to the copied data.
I have been trying with this query to copy the data:
db.getCollection("jobs").aggregate([{ $match: { "job_name": "UploadFile", "created_datetime" : {"$gte":"2021-08-18 12:00:00"} } },{"$merge":{into: {coll : "reports"}}}])
But after this, the count in "reports" collection is 0. Also, how can I update the documents (with an extract key "report_name") without using an extra updateMany() query?
The data in jobs collection is as shown:
{
"_id" : ObjectId("60fa8e8283dc22799134dc6f"),
"job_id" : "408a5654-9a89-4c15-82b4-b0dc894b19d7",
"job_name" : "UploadFile",
"data" : {
"path" : "share://LOCALNAS/Screenshot from 2021-07-23 10-34-34.png",
"file_name" : "Screenshot from 2021-07-23 10-34-34.png",
"parent_path" : "share://LOCALNAS",
"size" : 97710,
"md5sum" : "",
"file_uid" : "c4411f10-a745-48d0-a55d-164707b7d6c2",
"version_id" : "c3dfd31a-80ba-4de0-9115-2d9b778bcf02",
"session_id" : "c4411f10-a745-48d0-a55d-164707b7d6c2",
"resource_name" : "Screenshot from 2021-07-23 10-34-34.png",
"metadata" : {
"metadata" : {
"description" : "",
"tag_ids" : [ ]
},
"category_id" : "60eed9ea33c690a0dfc89b41",
"custom_metadata" : [ ]
},
"upload_token" : "upload_token_c5043927484e",
"upload_url" : "/mnt/share_LOCALNAS",
"vfs_action_handler_id" : "91be4282a9ad5067642cdadb75278230",
"element_type" : "file"
},
"user_id" : "60f6c507d4ba6ee28aee5723",
"node_id" : "syeda",
"state" : "COMPLETED",
"priority" : 2,
"resource_name" : "Screenshot from 2021-07-23 10-34-34.png",
"group_id" : "upload_group_0babf8b7ce0b",
"status_info" : {
"progress" : 100,
"status_msg" : "Upload Completed."
},
"error_code" : "",
"error_message" : "",
"created_datetime" : ISODate("2021-07-23T15:10:18.506Z"),
"modified_datetime" : ISODate("2021-07-23T15:10:18.506Z"),
"schema_version" : "1.0.0",
}
Your $match stage contains a condition which takes created_datetime as string while in your sample data it is an ISODate. Such condtion won't return any document, try:
{
$match: {
"job_name": "UploadFile",
"created_datetime": {
"$gte": ISODate("2021-07-01T12:00:00.000Z")
}
}
}
Mongo Playground
I have this collection in MongoDB:
{
"_id" : ObjectId("5df013b10a88910018267a89"),
"StockNo" : "33598",
"Description" : "some description",
"detections" : [
{
"lastDetectedOn" : ISODate("2020-01-29T04:36:41.191+0000"),
"lastDetectedBy" : "comp-t",
"_id" : ObjectId("5e3135f68c9e930017de8aec")
},
{
"lastDetectedOn" : ISODate("2019-12-21T18:12:06.571+0000"),
"lastDetectedBy" : "comp-n",
"_id" : ObjectId("5e3135f68c9e930017de8ae9")
},
{
"lastDetectedOn" : ISODate("2020-01-29T07:36:06.910+0000"),
"lastDetectedBy" : "comp-a",
"_id" : ObjectId("5e3135f68c9e930017de8ae7")
}
],
"createdAt" : ISODate("2019-12-10T21:52:49.788+0000"),
"updatedAt" : ISODate("2020-01-29T07:36:22.950+0000"),
"__v" : NumberInt(0)
}
I want to search by StockNo and get the name of the computer that last detected it (lastDetectedBy) only if lastDetectedOn was in the last 5 minutes with Mongoose in node.js with Express.
I also have this collection:
{
"_id" : ObjectId("5df113b10d35670018267a89"),
"InvoiceNo" : "1",
"InvoiceDate" : ISODate("2020-01-14T02:18:11.196+0000"),
"InvoiceContact : "",
"isActive" : true
},
{
"_id" : ObjectId("5df013c90a88910018267a8a"),
"InvoiceNo" : "2",
"InvoiceDate" : ISODate("2020-01-14T02:18:44.279+0000"),
"InvoiceContact : "Bob Smith",
"isActive" : true
},
{
"_id" : ObjectId("5e3096bb8c9e930017dc6e20"),
"InvoiceNo" : "3",
"InvoiceDate" : ISODate("2020-01-14T02:19:50.155+0000"),
"InvoiceContact : "",
"isActive" : true
}
And I want to update all the documents with empty InvoiceContact which has been issued in the last 30 seconds (or any date range between now and sometime in the past) with isActive equals true to isActive equals false. So for example, the first record has been issued in the last 30 seconds without InvoiceContact and isActive is true so this must be updated but the next two records will remain untouched for different reasons, the second record has InvoiceContact and the third record is out of range.
First Part
var mins5 = new Date(ISODate() - 1000* 60 * 5 )
db.getCollection('user').find({$and:[
{ "StockNo":"33598"},
{"detections.lastDetectedOn" : { $gte : mins5 }}
]})
.map(function(list){
var results = [];
list.detections.forEach(function (detections){
if(detections.lastDetectedOn > mins5){
results.push(detections.lastDetectedBy);
}
})
return results;
});
Second Part could be solved by a similar query using update instead of find.
If I have these objects :
{
"_id" : ObjectId("5caf2c1642e3731464c2c79d"),
"requested" : [],
"roomNo" : "E0-1-09",
"capacity" : 40,
"venueType" : "LR(M)",
"seatingType" : "TB",
"slotStart" : "8:30AM",
"slotEnd" : "9:50AM",
"__v" : 0
}
/* 2 */
{
"_id" : ObjectId("5caf2deb4a7f5222305b55d5"),
"requested" : [],
"roomNo" : "E0-1-09",
"capacity" : 40,
"venueType" : "LR(M)",
"seatingType" : "TB",
"slotStart" : "10:00AM",
"slotEnd" : "11:20AM",
"__v" : 0
}
is it possible to get something like this using aggregate in mongodb?
[{ roomNo: "E0-1-09" , availability : [{slotStart : "8:30AM", slotEnd: "9:50AM"} ,
{slotStart: "10:00AM", slotEnd : "11:20AM"}]
what im using currently:
db.getDB().collection(collection).aggregate([
{ $group: {_id:{roomNo: "$roomNo", availability :[{slotStart:"$slotStart", slotEnd:"$slotEnd"}]}}}
])
actually getting it twice like so :
[{ roomNo: "E0-1-09" , availability : [{slotStart : "8:30AM", slotEnd: "9:50AM"}]
[{ roomNo: "E0-1-09" , availability : [{slotStart: "10:00AM", slotEnd : "11:20AM"}]
You have to use $push accumulator
db.collection.aggregate([
{ "$group": {
"_id": "$roomNo",
"availability": {
"$push": {
"slotEnd": "$slotEnd",
"slotStart": "$slotStart"
}
}
}}
])
I have a document as below, and I want to pull all the elements in this array without any condition just via one statement. how can I do?
"energy_sent" : [
{
"player_id" : "034010000093",
"_id" : ObjectId("53675b8d251c20490d9679c6"),
"time" : ISODate("2014-05-05T09:36:13.629Z"),
"has_accepted" : 0,
"energy_value" : 2
},
{
"player_id" : "034010000094",
"_id" : ObjectId("53675cfa251c20490d9679cc"),
"time" : ISODate("2014-05-05T09:42:18.015Z"),
"has_accepted" : 0,
"energy_value" : 2
},
{
"player_id" : "034010000116",
"_id" : ObjectId("5367767889f8e3ee137dd239"),
"time" : ISODate("2014-05-05T11:31:04.457Z"),
"has_accepted" : 0,
"energy_value" : 2
}
]
If you are just after emptying the entire array just set it to empty:
db.collection.update(
{ /* query to match document */ },
{ "$set": { "energy_sent": [] }
)
So just use the $set operator