I am new in MongoDB world.
I've following data in my collection
{
"_id" : ObjectId("5735d8d4d147aa34e440988f"),
"DeviceLogId" : "26962",
"DeviceId" : "10",
"UserId" : "78",
"LogDateTime" : ISODate("2016-05-12T07:52:44.000+0000")
}
{
"_id" : ObjectId("5735d8d4d147aa34e4409890"),
"DeviceLogId" : "26963",
"DeviceId" : "10",
"UserId" : "342",
"LogDateTime" : ISODate("2016-05-12T07:54:09.000+0000")
}
{
"_id" : ObjectId("5735d8d4d147aa34e4409891"),
"DeviceLogId" : "26964",
"DeviceId" : "10",
"UserId" : "342",
"LogDateTime" : ISODate("2016-05-12T07:54:10.000+0000")
}
{
"_id" : ObjectId("5735d8d4d147aa34e4409892"),
"DeviceLogId" : "26965",
"DeviceId" : "10",
"UserId" : "78",
"LogDateTime" : ISODate("2016-05-12T07:54:27.000+0000")
}
I want to query DeviceId of each user with maximum LogDateTime using group by.
I've written group by query like below but have no idea how would I get DeviceLogId for each record.
collectionName.aggregate(
[{
$match: { LogDateTime: { $gt: todaysDateStart, $lt: todayDateEnd } }
}, {
$group: {
_id: "$UserId",
maxPunchTime: { $max: { $add: [ "$LogDateTime", 330*60000 ] } },
}
}])
In MSSQL, I could easily do it with nested query but I've no idea how would I achieve that in MongoDB.
Thanks in advance.
Use the $addToSet Group Accumulator:
collectionName.aggregate(
[{
$match: { LogDateTime: { $gt: todaysDateStart, $lt: todayDateEnd } }
}
, {
$group: {
_id: "$UserId",
maxPunchTime: { $max: { $add: [ "$LogDateTime", 330*60000 ] } },
deviceLogIds:{$addToSet: "$DeviceLogId"} //<----
}
} ,
{ $sort: {"maxPunchTime" : -1} } , {$limit : 1} //Sort Descending + Limit to 1
])
Add deviceid to an array in group phase,
Device:{$addToSet:deviceId}
Related
Below is the document which has an array name datum and I want to filter the records based on StatusCode, group by Year and sum the amount value from the recent record of distinct Types.
{
"_id" : ObjectId("5fce46ca6ac9808276dfeb8c"),
"year" : 2018,
"datum" : [
{
"StatusCode" : "A",
"Type" : "1",
"Amount" : NumberDecimal("100"),
"Date" : ISODate("2018-05-30T00:46:12.784Z")
},
{
"StatusCode" : "A",
"Type" : "1",
"Amount" : NumberDecimal("300"),
"Date" : ISODate("2023-05-30T00:46:12.784Z")
},
{
"StatusCode" : "A",
"Type" : "2",
"Amount" : NumberDecimal("420"),
"Date" : ISODate("2032-05-30T00:46:12.784Z")
},
{
"StatusCode" : "B",
"Type" : "2",
"Amount" : NumberDecimal("420"),
"Date" : ISODate("2032-05-30T00:46:12.784Z")
}
]
}
In my case following is the expected result :
{
Total : 720
}
I want to achieve the result in the following aggregate Query pattern
db.collection.aggregate([
{
$addFields: {
datum: {
$reduce: {
input: "$datum",
initialValue: {},
"in": {
$cond: [
{
$and: [
{ $in: ["$$this.StatusCode", ["A"]] }
]
},
"$$this",
"$$value"
]
}
}
}
}
},
{
$group: {
_id: "$year",
RecentValue: { $sum: "$datum.Amount" }
}
}
])
You can first $unwind the datum array. Do the filtering and sort by the date. Then get the record with latest datum by a $group. Finally do another $group to calculate the sum.
Here is a mongo playground for your reference.
I have below collections in DB around 1 million records. Hpw to get distinct eventID and eventName
from the collections in D for any particular date like 29-07-2020?
{
"_id" : 1814099,
"eventId" : "LAS012",
"eventName" : "CustomerTab",
"timeStamp" : ISODate("2018-12-31T20:09:09.820Z"),
"eventMethod" : "click",
"resourceName" : "CustomerTab",
"targetType" : "",
"resourseUrl" : "",
"operationName" : "",
"functionStatus" : "",
"results" : "",
"pageId" : "CustomerPage",
"ban" : "290824901",
"jobId" : "87377713",
"wrid" : "87377713",
"jobType" : "IBJ7FXXS",
"Uid" : "sc343x",
"techRegion" : "W",
"mgmtReportingFunction" : "N",
"recordPublishIndicator" : "Y",
"__v" : 0
}
You can use distinct, for example to fetch unique eventID:
let eventIds = await db.collection.distinct('eventID', {
"timeStamp": {
$gte: ISODate("2018-12-30T00:00:00.000Z"),
$lt: ISODate("2018-12-31T00:00:00.000Z")
}
})
If you want to retrieve both fields at the same time you'll have to use an aggregation:
db.collection.aggregate([
{
$match: {
"timeStamp": {
$gte: ISODate("2018-12-30T00:00:00.000Z"),
$lt: ISODate("2018-12-31T00:00:00.000Z")
}
}
},
{
$facet: {
eventIds: [
{
$group: {
_id: "$eventID"
}
}
],
eventName: [
{
$group: {
_id: "$eventName"
}
}
]
}
}
])
And if eventID and eventName are linked to one another:
db.collection.aggregate([
{
$match: {
"timeStamp": {
$gte: ISODate("2018-12-30T00:00:00.000Z"),
$lt: ISODate("2018-12-31T00:00:00.000Z")
}
}
},
{
$group: {
_id: {eventID: "$eventID", eventName: "$eventName"}
}
}
])
I have json object as following.
{
"_id" : ObjectId("123209sfekjern"),
"Name" : "Test1",
"Orders" : [
{
"Date" : "2020-05-05",
"Total" : "100.00"
},
{
"Date" : "2020-05-10",
"Total" : "110.00"
},
{
"Date" : "2020-05-11",
"Total" : "100.00"
},
{
"Date" : "2020-05-14",
"Total" : "110.00"
},
{
"Date" : "2020-05-20",
"Total" : "100.00"
},
{
"Date" : "2020-05-15",
"Total" : "100.00"
},
{
"Date" : "2020-05-12",
"Total" : "110.00"
},
{
"Date" : "2020-05-18",
"Total" : "100.00"
},
{
"Date" : "2020-05-31",
"Total" : "110.00"
}
]
}
I need customername, orders.Date and Order.Total for all the orders which is greater than 100.00
I tried following query..
db.Customers.aggregate
(
[
{
$match: {
$and: [
{"Orders.Date":{$gte:"2020-05-15"}},//ISODate('2020-05-15 10:00:00.000Z')
{ "Orders.Total": { $gte: "100.00" } },
]
}
},
{ $project: { _id:0, Name: 1, "Orders.Total": 1, "Orders.Date": 1} },
]
)
The above query returns all the records. I m still beginner and learning mongodb.
any help would be appreciated.
thank you.
$match filters on a document level so entire document will be returned if at least one subdocument matches your conditions. In order to filter a nested array you need $filter:
db.Customers.aggregate([
{
$project: {
_id: 0,
Name: 1,
Orders: {
$filter: {
input: "$Orders",
cond: {
$and: [
{ $gte: [ "$$this.Date", "2020-05-15" ] },
{ $gte: [ "$$this.Total", "100.00" ] },
]
}
}
}
}
}
])
Mongo Playground
How to get percentage total of data with group by date in MongoDB ?
Link example : https://mongoplayground.net/p/aNND4EPQhcb
I have some collection structure like this
{
"_id" : ObjectId("5ccbb96706d1d47a4b2ced4b"),
"date" : "2019-05-03T10:39:53.108Z",
"id" : 166,
"update_at" : "2019-05-03T10:45:36.208Z",
"type" : "image"
}
{
"_id" : ObjectId("5ccbb96706d1d47a4b2ced4c"),
"date" : "2019-05-03T10:39:53.133Z",
"id" : 166,
"update_at" : "2019-05-03T10:45:36.208Z",
"type" : "image"
}
{
"_id" : ObjectId("5ccbb96706d1d47a4b2ced4d"),
"date" : "2019-05-03T10:39:53.180Z",
"id" : 166,
"update_at" : "2019-05-03T10:45:36.208Z",
"type" : "image"
}
{
"_id" : ObjectId("5ccbb96706d1d47a4b2ced4e"),
"date" : "2019-05-03T10:39:53.218Z",
"id" : 166,
"update_at" : "2019-05-03T10:45:36.208Z",
"type" : "image"
}
And I have query in mongodb to get data of collection, how to get percentage of total data. in bellow example query to get data :
db.name_collection.aggregate(
[
{ "$match": {
"update_at": { "$gte": "2019-11-04T00:00:00.0Z", "$lt": "2019-11-06T00:00:00.0Z"},
"id": { "$in": [166] }
} },
{
"$group" : {
"_id": {
$substr: [ '$update_at', 0, 10 ]
},
"count" : {
"$sum" : 1
}
}
},
{
"$project" : {
"_id" : 0,
"date" : "$_id",
"count" : "$count"
}
},
{
"$sort" : {
"date" : 1
}
}
]
)
and this response :
{
"date" : "2019-11-04",
"count" : 39
},
{
"date" : "2019-11-05",
"count" : 135
}
how to get percentage data total from key count ? example response to this :
{
"date" : "2019-11-04",
"count" : 39,
"percentage" : "22%"
},
{
"date" : "2019-11-05",
"count" : 135,
"percentage" : "78%"
}
You have to group by null to get total count and then use $map to calculate the percentage. $round will be a useful operator in such case. Finally you can $unwind and $replaceRoot to get back the same number of documents:
db.collection.aggregate([
// previous aggregation steps
{
$group: {
_id: null,
total: { $sum: "$count" },
docs: { $push: "$$ROOT" }
}
},
{
$project: {
docs: {
$map: {
input: "$docs",
in: {
date: "$$this.date",
count: "$$this.count",
percentage: { $concat: [ { $toString: { $round: { $multiply: [ { $divide: [ "$$this.count", "$total" ] }, 100 ] } } }, '%' ] }
}
}
}
}
},
{
$unwind: "$docs"
},
{
$replaceRoot: { newRoot: "$docs" }
}
])
Mongo Playground
I'm trying to clean a huge database.
Sample DB :
{
"_id" : ObjectId("59fc5249d5ab401d99f3de7f"),
"addedAt" : ISODate("2017-11-03T11:26:01.744Z"),
"__v" : 0,
"check" : 17602,
"lastCheck" : ISODate("2018-04-05T11:47:00.609Z"),
"tracking" : [
{
"timeCheck" : ISODate("2017-11-06T13:17:20.861Z"),
"_id" : ObjectId("5a0060e00f3c330012bafe39"),
"rank" : 2395,
},
{
"timeCheck" : ISODate("2017-11-06T13:22:31.254Z"),
"_id" : ObjectId("5a0062170f3c330012bafe77"),
"rank" : 2395,
},
{
"timeCheck" : ISODate("2017-11-06T13:27:40.551Z"),
"_id" : ObjectId("5a00634c0f3c330012bafebe"),
"rank" : 2379,
},
{
"timeCheck" : ISODate("2017-11-06T13:32:41.084Z"),
"_id" : ObjectId("5a0064790f3c330012baff03"),
"rank" : 2395,
},
{
"timeCheck" : ISODate("2017-11-06T13:37:51.012Z"),
"_id" : ObjectId("5a0065af0f3c330012baff32"),
"rank" : 2379,
},
{
"timeCheck" : ISODate("2017-11-07T13:37:51.012Z"),
"_id" : ObjectId("5a0065af0f3c330012baff34"),
"rank" : 2379,
}]
}
I have a lot of duplicate value but I need to clean only by day.
To obtain this for example :
{
"_id" : ObjectId("59fc5249d5ab401d99f3de7f"),
"addedAt" : ISODate("2017-11-03T11:26:01.744Z"),
"__v" : 0,
"check" : 17602,
"lastCheck" : ISODate("2018-04-05T11:47:00.609Z"),
"tracking" : [
{
"timeCheck" : ISODate("2017-11-06T13:17:20.861Z"),
"_id" : ObjectId("5a0060e00f3c330012bafe39"),
"rank" : 2395,
},
{
"timeCheck" : ISODate("2017-11-06T13:27:40.551Z"),
"_id" : ObjectId("5a00634c0f3c330012bafebe"),
"rank" : 2379,
},
{
"timeCheck" : ISODate("2017-11-07T13:37:51.012Z"),
"_id" : ObjectId("5a0065af0f3c330012baff34"),
"rank" : 2379,
}]
}
How can I aggregate by day and after delete last value duplicate?
I need to keep the values per day even if they are identical with another day.
The aggregation framework cannot update data at this stage. However, you can use the following aggregation pipeline in order to get the desired output and then use e.g. a bulk replace to update all your documents:
db.collection.aggregate({
$unwind: "$tracking" // flatten the "tracking" array into separate documents
}, {
$sort: {
"tracking.timeCheck": 1 // sort by timeCheck to allow us to use the $first operator in the next stage reliably
}
}, {
$group: {
_id: { // group by
"_id": "$_id", // "_id" and
"rank": "$tracking.rank", // "rank" and
"date": { // the "date" part of the "timeCheck" field
$dateFromParts : {
year: { $year: "$tracking.timeCheck" },
month: { $month: "$tracking.timeCheck" },
day: { $dayOfWeek: "$tracking.timeCheck" }
}
}
},
"doc": { $first: "$$ROOT" } // only keep the first document per group
}
}, {
$sort: {
"doc.tracking.timeCheck": 1 // restore ascending sort order - may or may not be needed...
}
}, {
$group: {
_id: "$_id._id", // merge everything again per "_id"
"addedAt": { $first: "$doc.addedAt" },
"__v": { $first: "$doc.__v" },
"check": { $first: "$doc.check" },
"lastCheck": { $first: "$doc.lastCheck" },
"tracking": { $push: "$doc.tracking" } // in order to join the tracking values into an array again
}
})