Mongo projection field that field not same - mongodb

there
My question may be confuse. Let's me explain further more.
I have document for aggregation like this.
{
"metric" : "user_act",
"stream_id" : "f00001",
"values" : {
"likes" : 57,
"comments" : 0,
"shares" : 0
}
}
{
"metric" : "user_act",
"stream_id" : "f00002",
"values" : {
"likes" : 28,
"comments" : 0,
"shares" : 1
}
}
{
"metric" : "user_act",
"stream_id" : "t00001",
"values" : {
"favorites" : 5,
"retweets" : 15
}
}
I would like to calculate engagement by sum likes, comments and shares together. So before calculating, I have to projection data before grouping. I would like to mapping values.favorites to likes, values.retweets to shares and comments if don't have any data set default to 0.
I try projection like below but does not work because value of second line of $ifNull override the first line.
{
$project: {
"stream_id" : 1,
"shares": {
$ifNull: ["$values.retweets",0],
$ifNull: ["$values.shares", 0]
} ,
"likes": {
$ifNull: ["$values.favorites",0],
$ifNull: ["$values.likes", 0]
} ,
"comments": {
$ifNull: ["$values.replys",0],
$ifNull: ["$values.comments", 0]
}
}
}
Anyone any idea? Thank you in advanced.
[Update]
I try to projection like this but not work in case: how can I check the field exists?
{
$project: {
"stream_id" : 1,
"shares": {
$switch: {
branches: [
{ case: {$ne: ["$values.retweets", 0]},
then: {$ifNull: ["$values.retweets", "$values.retweets"]}
},
{ case: {$ne: ["$values.shares", 0]},
then: {$ifNull: ["$values.shares", "$values.shares"]}
}
],
default: 0
}
}
}
}

You can try $cond projection.
db.collection.aggregate({
$project: {
"stream_id" : 1,
"shares": { $cond: [ { $eq:[ { $ifNull: [ "$values.shares", 0 ] }, 0 ] },{ $ifNull: [ "$values.retweets", 0 ] }, "$values.shares" ] },
"likes": { $cond: [ { $eq:[ { $ifNull: [ "$values.likes", 0 ] }, 0 ] }, { $ifNull: [ "$values.favorites", 0 ] }, "$values.likes" ] },
"comments": { $cond: [ { $eq:[ { $ifNull: [ "$values.comments", 0] }, 0 ] }, { $ifNull: [ "$values.replys", 0 ] }, "$values.comments" ] }
}})
Using $switch
db.collection.aggregate([{
$project: {
"stream_id" : 1,
"shares": {
$switch: {
branches: [
{ case: { $ifNull: [ "$values.shares", false ] },
then: "$values.shares"
},
{ case: { $ifNull: [ "$values.retweets", false ] },
then: "$values.retweets"
}],
default: 0
}
}
}
}])

Related

Compare 2 count aggregations

I have a collection in MongoDB that looks something like the following:
{ "_id" : 1, "type" : "start", userid: "101", placementid: 1 }
{ "_id" : 2, "type" : "start", userid: "101", placementid: 2 }
{ "_id" : 3, "type" : "start", userid: "101", placementid: 3 }
{ "_id" : 4, "type" : "end", userid: "101", placementid: 1 }
{ "_id" : 5, "type" : "end", userid: "101", placementid: 2 }
and I want to group results by userid then placementid and then count the types of "start" and "end", but only when the two counts are different. In this particular example I would want to get placementid: 3 because when grouped and counted this is the only case where the counts don't match.
I've written a query that gets the 2 counts and the grouping but I can't do the filtering when counts don't match. This is my query:
db.getCollection('mycollection').aggregate([
{
$project: {
userid: 1,
placementid: 1,
isStart: {
$cond: [ { $eq: ["$type", "start"] }, 1, 0]
},
isEnd: {
$cond: [ { $eq: ["$type", "end"] }, 1, 0]
}
}
},
{
$group: {
_id: { userid:"$userid", placementid:"$placementid" },
countStart:{ $sum: "$isStart" },
countEnd: { $sum: "$isEnd" }
}
},
{
$match: {
countStart: {$ne: "$countEnd"}
}
}
])
It seems like I'm using the match aggregation incorrectly because I'm seeing results where countStart and countEnd are the same.
{ "_id" : {"userid" : "101", "placementid" : "1"}, "countStart" : 1.0, "countEnd" : 1.0 }
{ "_id" : {"userid" : "101", "placementid" : "2"}, "countStart" : 1.0, "countEnd" : 1.0 }
{ "_id" : {"userid" : "101", "placementid" : "3"}, "countStart" : 1.0, "countEnd" : 0 }
Can anybody point into the right direction please?
To compare two fields inside $match stage you need $expr which is available in MongoDB 3.6:
db.myCollection.aggregate([
{
$project: {
userid: 1,
placementid: 1,
isStart: {
$cond: [ { $eq: ["$type", "start"] }, 1, 0]
},
isEnd: {
$cond: [ { $eq: ["$type", "end"] }, 1, 0]
}
}
},
{
$group: {
_id: { userid:"$userid", placementid:"$placementid" },
countStart:{ $sum: "$isStart" },
countEnd: { $sum: "$isEnd" }
}
},
{
$match: {
$expr: { $ne: [ "$countStart", "$countEnd" ] }
}
}
])
If you're using older version of MongoDB you can use $redact:
db.myCollection.aggregate([
{
$project: {
userid: 1,
placementid: 1,
isStart: {
$cond: [ { $eq: ["$type", "start"] }, 1, 0]
},
isEnd: {
$cond: [ { $eq: ["$type", "end"] }, 1, 0]
}
}
},
{
$group: {
_id: { userid:"$userid", placementid:"$placementid" },
countStart:{ $sum: "$isStart" },
countEnd: { $sum: "$isEnd" }
}
},
{
$redact: {
$cond: { if: { $ne: [ "$countStart", "$countEnd" ] }, then: "$$KEEP", else: "$$PRUNE" }
}
}
])
You run do the following pipeline to get this - no need to use $expr or $redact or anything special really:
db.mycollection.aggregate({
$group: {
_id: {
"userid": "$userid",
"placementid": "$placementid"
},
"sum": {
$sum: {
$cond: {
if: { $eq: [ "$type", "start" ] },
then: 1, // +1 for start
else: -1 // -1 for anything else
}
}
}
}
}, {
$match: {
"sum": { $ne: 0 } // only return the non matching-up ones
}
})

MongoDb - Pop array element based on if condition

I am trying to update my mongo database which has following structure.
{
"_id" : ObjectId("5a64d076bfd103df081967ae"),
"values" : [
{
"date" : "2018-01-22",
"Price" : "1289.4075"
},
{
"date" : "2018-01-22",
"Price" : "1289.4075"
},
{
"date" : "2015-05-18",
"Price" : 1289.41
}
],
"Code" : 123456,
"schemeStatus" : "Inactive"
}
I want to compare first 2 array element's date value i.e values[0].date and values[1].date. If both matches then I want to delete values[0] so that there will be only 1 entry with that date.
You can use aggregation framework's pipeline with $out as a last stage to update your collection
db.collection.aggregate([
{
$addFields: {
sameDate: {
$let: {
vars: {
fst: { $arrayElemAt: [ "$values", 0 ] },
snd: { $arrayElemAt: [ "$values", 1 ] }
},
in: { $cond: { if: { $eq: [ "$$fst.date", "$$snd.date" ] }, then: 1, else: 0 } }
}
}
}
},
{
$project: {
_id: 1,
values : { $cond: { if: { $eq: [ "$sameDate", 0 ] }, then: "$values", else: { $slice: [ "$values", 1, { $size: "$values" } ] } } },
Code: 1,
schemeStatus: 1
}
},
{ $out: "collection" }
])
Some more important operators used here:
$cond to handle if-else logic
$let to define some helper variables
$arrayElemAt to get first and second element
$slice to pop first element

MongoDB. Aggregate the sum of two arrays sizes

With MongoDB 3.4.10 and mongoose 4.13.6 I'm able to count sizes of two arrays on the User model:
User.aggregate()
.project({
'_id': 1,
'leftVotesCount': { '$size': '$leftVoted' },
'rightVotesCount': { '$size': '$rightVoted' }
})
where my Users are (per db.users.find())
{ "_id" : ObjectId("5a2b21e63023c6117085c240"), "rightVoted" : [ 2 ],
"leftVoted" : [ 1, 6 ] }
{ "_id" : ObjectId("5a2c0d68efde3416bc8b7020"), "rightVoted" : [ 2 ],
"leftVoted" : [ 1 ] }
Here I'm getting expected result:
[ { _id: '5a2b21e63023c6117085c240', leftVotesCount: 2, rightVotesCount: 1 },
{ _id: '5a2c0d68efde3416bc8b7020', leftVotesCount: 1, rightVotesCount: 1 } ]
Question. How can I get a cumulative value of leftVotesCount and rightVotesCount data? I tried folowing:
User.aggregate()
.project({
'_id': 1,
'leftVotesCount': { '$size': '$leftVoted' },
'rightVotesCount': { '$size': '$rightVoted' },
'votesCount': { '$add': [ '$leftVotesCount', '$rightVotesCount' ] },
'votesCount2': { '$sum': [ '$leftVotesCount', '$rightVotesCount' ] }
})
But votesCount is null and votesCount2 is 0 for both users. I'm expecting votesCount = 3 for User 1 and votesCount = 2 for User 2.
$leftVotesCount, $rightVotesCount become available only on the next stage. Try something like:
User.aggregate()
.project({
'_id': 1,
'leftVotesCount': { '$size': '$leftVoted' },
'rightVotesCount': { '$size': '$rightVoted' }
})
.project({
'_id': 1,
'leftVotesCount': 1,
'rightVotesCount': 1
'votesCount': { '$add': [ '$leftVotesCount', '$rightVotesCount' ] },
'votesCount2': { '$sum': [ '$leftVotesCount', '$rightVotesCount' ] }
})
You can't reference the project variables created in the same project stage.
You can wrap the variables in a $let expression.
User.aggregate().project({
"$let": {
"vars": {
"leftVotesCount": {
"$size": "$leftVoted"
},
"rightVotesCount": {
"$size": "$rightVoted"
}
},
"in": {
"votesCount": {
"$add": [
"$$leftVotesCount",
"$$rightVotesCount"
]
},
"leftVotesCount": "$$leftVotesCount",
"rightVotesCount": "$$rightVotesCount"
}
}
})
It turned out that $add supports nested expressions, so I was able to solve the issue by excluding intermediate variables:
User.aggregate().project({
'_id': 1,
'votesCount': { '$add': [ { '$size': '$leftVoted' }, { '$size': '$rightVoted' } ] }
});
// [ {_id: '...', votesCount: 3}, {_id: '...', votesCount: 2} ]

MongoDB aggregate multiple group by top fields and array fields

My collection will look like this,
{
"_id" : ObjectId("591c5971240033283736860a"),
"status" : "Done",
"createdDate" : ISODate("2017-05-17T14:09:20.653Z")
"communications" : [
{
"communicationUUID" : "df07948e-4a14-468e-beb1-db55ff72b215",
"communicationType" : "CALL",
"recipientId" : 12345,
"createdDate" : ISODate("2017-05-18T14:09:20.653Z")
"callResponse" : {
"Status" : "completed",
"id" : "dsd45554545ds92a9bd2c12e0e6436d",
}
}
]}
{
"_id" : ObjectId("45sdsd59124003345121450a"),
"status" : "ToDo",
"createdDate" : ISODate("2017-05-17T14:09:20.653Z")
"communications" : [
{
"communicationUUID" : "45sds55-4a14-468e-beb1-db55ff72b215",
"communicationType" : "CALL",
"recipientId" : 1234,
"createdDate" : ISODate("2017-05-18T14:09:20.653Z")
"callResponse" : {
"Status" : "completed",
"id" : "84fe862f1924455dsds5556436d",
}
}
]}
Currently I am writing two aggregate query to achieve my requirement and my query will be below
db.collection.aggregate(
{ $project: {
dayMonthYear: { $dateToString: { format: "%d/%m/%Y", date: "$createdDate" } },
status: 1,
}},
{ $group: {
_id: "$dayMonthYear",
Pending: { $sum: { $cond : [{ $eq : ["$status", "ToDo"]}, 1, 0]} },
InProgress: { $sum: { $cond : [{ $eq : ["$status", "InProgress"]}, 1, 0]} },
Done: { $sum: { $cond : [{ $eq : ["$status", "Done"]}, 1, 0]} },
Total: { $sum: 1 }
}}
My output will be,
{"_id" : "17/05/2017", "Pending" : 1.0, "InProgress" : 0.0, "Done" : 1.0, "Total" : 2.0 }
Using above query I can able to get count but I need to find the count based on communication Status too so I am writing one more query to achieve,
db.collection.aggregate(
{"$unwind":"$communications"},
{ $project: {
dayMonthYear: { $dateToString: { format: "%d/%m/%Y", date: "$createdDate" } },
communications: 1
}},
{ "$group": {
_id: "$dayMonthYear",
"total_call": { $sum: { $cond : [{ $or : [ { $eq: [ "$communications.callResponse.Status", "failed"] },
{ $eq: [ "$communications.callResponse.Status", "busy"] },
{ $eq: [ "$communications.callResponse.Status", "completed"] },
{ $eq: [ "$communications.callResponse.Status", "no-answer"] }
]}, 1, 0 ] }},
"engaged": { $addToSet: { $cond : [{ $eq : ["$communications.callResponse.Status", "completed"]},
"$communications.recipientId", "null" ]} },
"not_engaged": { $addToSet: { $cond: [{ $or : [ { $eq: [ "$communications.callResponse.Status", "failed"] },
{ $eq: [ "$communications.callResponse.Status", "busy"] },
{ $eq: [ "$communications.callResponse.Status", "no-answer"] } ]},
"$communications.recipientId", "null" ] }}
}},
{ "$project": {
"_id": 1,
"total_call": 1,
"engaged": { "$setDifference": [ "$ngaged", ["null"] ] },
"not_engaged": { "$setDifference": [ "$not_engaged", ["null"] ] },
}},
{ "$project": {
"total_call": 1,
"engaged": { "$size": "$engaged" },
"not_engaged": { "$size": { "$setDifference": [ "$not_engaged", "$engaged" ] }},
}})
My output will be,
{"_id" : "18/05/2017", "total_call" : 2.0, "engaged" : 2, "not_engaged" : 0}
Using above query I can able to get count but I want to achieve it in single query
I am looking for output like
{"_id":"17/05/2017", "Pending" : 1.0, "InProgress" : 0.0, "Done" : 1.0, "total_call" : 0, "engaged" : 0, "not_engaged" : 0}
{"_id":"18/05/2017", "Pending" : 0.0, "InProgress" : 0.0, "Done" : 0.0, "total_call" : 2, "engaged" : 2, "not_engaged" : 0}
Can anyone suggest or provide me good way to get above result.
You can use $concatArrays to merge the status& createdDate documents followed by $group to count the occurrences.
db.collection.aggregate([
{
"$project": {
"statusandcreateddate": {
"$concatArrays": [
[
{
"status": "$status",
"createdDate": "$createdDate"
}
],
{
"$map": {
"input": "$communications",
"as": "l",
"in": {
"status": "$$l.callResponse.Status",
"createdDate": "$$l.createdDate"
}
}
}
]
}
}
},
{
"$unwind": "$statusandcreateddate"
},
{
"$group": {
"_id": {
"$dateToString": {
"format": "%d/%m/%Y",
"date": "$statusandcreateddate.createdDate"
}
},
"total_call": {
"$sum": {
"$cond": [
{
"$or": [
{
"$eq": [
"$statusandcreateddate.status",
"failed"
]
},
{
"$eq": [
"$statusandcreateddate.status",
"busy"
]
},
{
"$eq": [
"$statusandcreateddate.status",
"completed"
]
},
{
"$eq": [
"$statusandcreateddate.status",
"no-answer"
]
}
]
},
1,
0
]
}
},
"engaged": {
"$sum": {
"$cond": [
{
"$eq": [
"$statusandcreateddate.status",
"completed"
]
},
1,
0
]
}
},
"not_engaged": {
"$sum": {
"$cond": [
{
"$or": [
{
"$eq": [
"$statusandcreateddate.status",
"failed"
]
},
{
"$eq": [
"$statusandcreateddate.status",
"busy"
]
},
{
"$eq": [
"$statusandcreateddate.status",
"no-answer"
]
}
]
},
1,
0
]
}
},
"Pending": {
"$sum": {
"$cond": [
{
"$eq": [
"$statusandcreateddate.status",
"ToDo"
]
},
1,
0
]
}
},
"InProgress": {
"$sum": {
"$cond": [
{
"$eq": [
"$statusandcreateddate.status",
"InProgress"
]
},
1,
0
]
}
},
"Done": {
"$sum": {
"$cond": [
{
"$eq": [
"$statusandcreateddate.status",
"Done"
]
},
1,
0
]
}
}
}
}
])

Aggregate query in MongoDB

I'm trying to create some daily stats from a MongoDB table. The document contains messages that have a create-date, state (Warn, Error, Complete). I'd like to product a query that results in one record per - Date,Count of Warn, Count of Error, Count of Complete. I'm a newbie with Mongo and just learning the query language. I've tried aggregation with mixed results:
db.TransactionLogs.aggregate(
{ $group : {
_id : {
category: {$substr:["$startDate",0,10]},
term: "$Status",
},
total: { $sum : 2 }
}
})
results in multiple records per date by status:
"result" : [
{
"_id" : {
"category" : "2015-02-10",
"term" : "Completed",
},
"total" : 532
},
{
"_id" : {
"category" : "2015-02-10",
"term" : "Error",
},
"total" : 616
},
Message:
{ "_id" : "2ceda481-3dd3-480d-800d-95288edce6f2", "MID" : "02de5194-7a1d-4854-922c-934902840136", "Status" : "Completed", "firstName" : "Willy", "lastName" : "Wire", "allocation" : "100", "initEvent" : "Marriage", "system" : "Oracle", "startDate" : "2015-02-06T19:03:34.237Z", "stopDate" : "2015-02-06T19:23:34.237Z", "plan" : "445-A" }
I'm sure that its a lack of understanding of aggregation on my part. Any help or direction is greatly appreciated!
I figured it out. I needed to look at how to "pivot" in Mongo. This works:
db.TransactionLogs.aggregate([ { $project: { startdate: {$substr:["$startDate",0,10]},
cnt_e1: { $cond: [ { $eq: [ "$Status", "Error" ] }, "$count", 1 ] },
cnt_e2: { $cond: [ { $eq: [ "$Status", "Warning" ] }, "$count", 1 ] },
cnt_e3: { $cond: [ { $eq: [ "$Status", "Completed" ] }, "$count", 1 ] },
} },
{ $group: { _id: "$startdate", cnt_e1: { $sum: "$cnt_e1" }, cnt_e2: { $sum: "$cnt_e2" }, cnt_e3: { $sum: "$cnt_e3" } } },
{ $sort: { _id: 1 } },
Here's the code...
db.TransactionLogs.aggregate([ { $project: { startdate: {$substr:["$startDate",0,10]},
cnt_e1: { $cond: [ { $eq: [ "$Status", "Error" ] }, "$count", 1 ] },
cnt_e2: { $cond: [ { $eq: [ "$Status", "Warning" ] }, "$count", 1 ] },
cnt_e3: { $cond: [ { $eq: [ "$Status", "Completed" ] }, "$count", 1 ] },
} },
{ $group: { _id: "$startdate", cnt_e1: { $sum: "$cnt_e1" }, cnt_e2: { $sum: "$cnt_e2" }, cnt_e3: { $sum: "$cnt_e3" } } },
{ $sort: { _id: 1 } },