How to query :
{
"_id" : Object Id("58787242f7d06edbbb88f46e"),
"name" : "aah",
"values" : [
"1484196300685",
"10"
],
"attributes" : {
}
}
i need time where value=10 result 1484196300685
db.collection.find(
{ values: { $elemMatch: { $eq: "10" } } }
)
Related
I have below user details in my bookings collection
{
"_id" : ObjectId("609a382b589346973c84c6fe"),
"Name" : "abc",
"UserId":1
"Status" : "Pending",
"BookingData" : {
"Date" : ISODate("2021-04-30T04:00:00.000Z"),
"info" : [],
"BookingDataMethod" : "avf",
"Message" : null,
"products" : [
{
"_id" : ObjectId("60a4e92775e5de3570578820"),
"ProductName" : "Test1",
"ProductID" : ObjectId("60a4e92475e5de357057880a"),
"IsDeliveryFailed" : "Yes"
},
{
"_id" : ObjectId("60a4e92775e5de357057881f"),
"ProductName" : "Test2",
"ProductID" : ObjectId("60a4e92475e5de357057880d")
}
],
}
}
I have prepared a query for the below conditions and when I run the below query I should get the "UserId":1 documents but I got 0 records
condition 1: products should not be null
condition 2: ProductID should exist in the products array and should not be null
condition 3: IsDeliveryFailed should not be "Yes"
Based on the above user only one product got delivery failed(IsDeliveryFailed": "Yes") so when I run this query it should return "UserId":1 document. if both products "IsDeliveryFailed": "Yes" then
we should not get this user
Query
db.getCollection('bookings').find({
"$and": [
{ "BookingData.products": { $ne: [] } },
{ "BookingData.products": {"$elemMatch":{ "ProductID": { "$exists": true ,$ne: null } }} },
{ "BookingData.products": {"$elemMatch":{ "IsDeliveryFailed": { $ne: 'Yes' } }} }
]
})
Could someone please tell me the issue on the above query or please help me to prepare a query for the above condition?
I think you can do it with aggregations
db.collection.aggregate([
{
$match: {
"BookingData.products": { "$exists": true }
}
},
{
$set: {
"BookingData.products": {
"$filter": {
"input": "$BookingData.products",
"cond": {
$and: [
{ $ne: [ "$$this.ProductID", undefined ] },
{ $ne: [ "$$this._id", null ] },
{ $ne: [ "$$this.IsDeliveryFailed", "Yes" ] }
]
}
}
}
}
},
{
$match: {
$expr: {
$ne: [ "$BookingData.products", [] ]
}
}
}
])
Working Mongo playground
I have a collection with date stored as strings YYYY-mm-DD_HH:MM:SS.UUUZ like 2020-10-20_12:15:22.123+0100
My goal is to query on strings treating those as dates.
What am I doing:
I'm unwinding some header data on multiple documents:
{
"$unwind": {
"path": "$events",
"preserveNullAndEmptyArrays": true
}
}
and also
{
"$unwind": {
"path": "$events.hi2",
"preserveNullAndEmptyArrays": true
}
}
I'm adding a new field made with the string parsed as Date
{
"$addFields": {
"events.hi2.ConnectTimets": {
"$dateFromString": {
"dateString": "$events.hi2.ConnectTime",
"format": "%Y-%m-%d_%H:%M:%S.%L%Z"
}
}
}}
then on a $match stage I try to filter all records with date newer than 1 June 2020:
{
"$match":{
"events.hi2.ConnectTimets": {
"$gt": {"$dateFromString": {
"dateString": "2020-06-01",
"format": "%Y-%m-%d"
}
}
}
}
}
my result is Fetched 0 record(s) in 0ms
even though exists (at least a single document) in the database with a date matching the filter:
{
"_id" : ObjectId("5f438dfbf1feb13c4352e9f4"),
"timestamp" : NumberLong(1598262779045),
"attribute1" : [
"common"
],
"events" : [
{
"eventType" : "ty1",
"timestamp" : NumberLong(1598262779018),
"docId" : NumberLong(282578800148736),
"hi2" : {
"Priority" : 3,
"ClientId" : "client1",
"ConnectTime" : "2020-08-24_09:52:58.993+0000",
"Direction" : 1
}
},
{
"eventType" : "ty2",
"timestamp" : NumberLong(1598262781071),
"docId" : NumberLong(282578800148736),
"hi2" : {
"ref" : "bbbb"
}
}
]
}
When I espected something like
{
"_id" : ObjectId("5f438dfbf1feb13c4352e9f4"),
"timestamp" : NumberLong(1598262779045),
"attribute1" : [
"common"
],
"events" : [
{
"eventType" : "ty1",
"timestamp" : NumberLong(1598262779018),
"docId" : NumberLong(282578800148736),
"hi2" : {
"Priority" : 3,
"ClientId" : "client1",
"ConnectTime" : "2020-08-24_09:52:58.993+0000",
"Direction" : 1
}
}
}
Note_: the add field is ok because if i fire it without the match stage outputs a field with the string parsed as date
You should never store date/time values as string, use always proper Date objects.
Then the query is much simpler:
db.logging.aggregate([
{
$addFields: {
"events.hi2.ConnectTimets": {
$dateFromString: {
dateString: "$events.hi2.ConnectTime",
format: "%Y-%m-%d_%H:%M:%S.%L%Z"
}
}
}
},
{ $match: { "events.hi2.ConnectTimets": { $gte: ISODate("2020-06-01") } } }
])
When you have to work with date/time values then I recommend moment.js. Then you query could look like these:
{ $match: { "events.hi2.ConnectTimets": { $gte: moment("2020-06-01").toDate() } } }
{ $match: { "events.hi2.ConnectTimets": { $gte: moment("2020-06-01").tz('Europe/Zurich').toDate() } } }
{ $match: { "events.hi2.ConnectTimets": { $lte: moment.tz('Europe/Zurich').endOf('day').toDate() } } }
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
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: [ "$$item.itemID", "5a59c587fa9b4a212b0a1312" ] }
}
}
} },
{ $unwind: "$transDetails"},
{ $project: {price: "$transDetails.price"}}
])
Which will give you
{
"price" : "22"
},
{
"price" : "35"
},
...
I have a collection called "products" which has an array of "bids" objects.
I want to find out the Maximum bid for each product, for this I am aggregating Products on $max with $bids.bidamount field. However this is only giving me the largest bid amount. How do I project all the bid fields for the max aggregation.
Here is a sample document
{
"_id" : ObjectId("58109a5138fe12215cfdc064"),
"product_id" : 2,
"item_name" : "Auction Item1",
"item_description" : "Test",
"seller_name" : "ak#gmail.com",
"item_price" : "20",
"item_quantity" : 7,
"sale_type" : "Auction",
"posted_at" : "2016:10:26 04:58:09",
"expires_at" : "2016:10:30 04:58:09",
"bids" : [
{
"bid_id" : 1,
"bidder" : "ak#gmail.com",
"bid_amount" : 300,
"bit_time" : "2016:10:26 22:36:29"
},
{
"bid_id" : 2,
"bidder" : "ak#gmail.com",
"bid_amount" : 100,
"bit_time" : "2016:10:26 22:37:29"
}
],
"orders" : [
{
"buyer" : "ak#gmail.com",
"quantity" : "2"
},
{
"buyer" : "ak#gmail.com",
"quantity" : "3"
}
]
}
Here is my mongo query:
db.products.aggregate([
{
$project: {
bidMax: { $max: "$bids.bid_amount"}
}
}
])
which gives the following result:
{
"_id" : ObjectId("58109a5138fe12215cfdc064"),
"bidMax" : 300
}
db.products.aggregate([{$unwind:"$bids"},{$group:{_id:"$_id", sum:{$sum:"$bids.bid_amount"}}},{$project:{doc:"$$ROOT", _id:1, sum:1}, {$sort:{"sum":-1}},{$limit:1}]),
which return something like { "_id" : ObjectId("5811b667c50fb1ec88227860"), "sum" : 600, doc:{your document....} }
This should do it:
db.products.aggregate([{
$unwind: '$bids'
}, {
$group: {
_id: '$products_id',
maxBid: {
$max: '$bids.bid_amount'
}
}
}])
db.collectionName.aggregate(
[
{
$group:
{
_id: "$product_id",
maxBidAmount: { $max: "$bids.bid_amount" }
}
}
]
)
Hey use this query, you will get the result.