How to pull all elements from array in MongoDB without any condition - node.js

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

Related

$merge, $match and $update in one aggregate query

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

$add,$subtract aggregation-framework in mongodb

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.

Query an array in MongoDB

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.

How to group a document with the same name that has different values for a specific attribute in one array using Mongodb?

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"
}
}
}}
])

MongoDB-Query Optimization

I have a collection with a sub-document consisting of more than 40K records.
My aggregate query takes about 300 secs. I have tried optimizing the same using compound as well as multi-key indexing, which completes in 180 secs.
I still require a reduced query time execution.
here is my collection:
{
"_id" : ObjectId("545b32cc7e9b99112e7ddd97"),
"grp_id" : 654,
"user_id" : 2,
"mod_on" : ISODate("2014-11-06T08:35:40.857Z"),
"crtd_on" : ISODate("2014-11-06T08:35:24.791Z"),
"uploadTp" : 0,
"tp" : 1,
"status" : 3,
"id_url" : [
{"mid":"xyz12793"},
{"mid":"xyz12794"},
{"mid":"xyz12795"},
{"mid":"xyz12796"}
],
"incl" : 1,
"total_cnt" : 25,
"succ_cnt" : 25,
"fail_cnt" : 0
}
and following is my query
db.member_id_transactions.aggregate([ { '$match':
{ id_url: { '$elemMatch': { mid: 'xyz12794' } } } },
{ '$unwind': '$id_url' },
{ '$match': { grp_id: 654, 'id_url.mid': 'xyz12794' } } ])
has anyone faced the same issue?
here's the o/p for aggregate query with explain option
{
"result" : [
{
"_id" : ObjectId("546342467e6d1f4951b56285"),
"grp_id" : 685,
"user_id" : 2,
"mod_on" : ISODate("2014-11-12T11:24:01.336Z"),
"crtd_on" : ISODate("2014-11-12T11:19:34.682Z"),
"uploadTp" : 1,
"tp" : 1,
"status" : 3,
"id_url" : [
{"mid":"xyz12793"},
{"mid":"xyz12794"},
{"mid":"xyz12795"},
{"mid":"xyz12796"}
],
"incl" : 1,
"__v" : 0,
"total_cnt" : 21406,
"succ_cnt" : 21402,
"fail_cnt" : 4
}
],
"ok" : 1,
"$gleStats" : {
"lastOpTime" : Timestamp(0, 0),
"electionId" : ObjectId("545c8d37ab9cc679383a1b1b")
}
}
One way to reduce the number of records being filtered further is to include the field grp_id, in the first $match operator.
db.member_id_transactions.aggregate([
{$match:{ "id_url.mid": 'xyz12794',"grp_id": 654 } },
{$unwind: "$id_url" },
{$match: { "id_url.mid": "xyz12794" } }
])
See how the performance is now. Add grp_id to the index to get better response time.
The above aggregation query though it works, is unnecessary. since you are not altering the structure of the document, and you expect only one element in the array to match the filter condition, you could just use a simple find and project.
db.member_id_transactions.find(
{ "id_url.mid": "xyz12794","grp_id": 654 },
{"_id":0,"grp_id":1,"id_url":{$elemMatch:{"mid":"xyz12794"}},
"user_id":1,"mod_on":1,"crtd_on":1,"uploadTp":1,
"tp":1,"status":1,"incl":1,"total_cnt":1,
"succ_cnt":1,"fail_cnt":1
}
)

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