Count of MongoDB aggregation match results - mongodb

I'm working with a MongoDB collection that has a lot of duplicate keys. I regularly do aggregation queries to find out what those duplicates are, so that I can dig in and find out what is and isn't different about them.
Unfortunately the database is huge and duplicates are often intentional. What I'd like to do is to find the count of keys that have duplicates, instead of printing a result with thousands of lines of output. Is this possible?
(Side Note: I do all of my querying through the shell, so solutions that don't require external tools or a lot of code would be preferred, but I understand that's not always possible.)
Example Records:
{ "_id" : 1, "type" : "example", "key" : "111111", "value" : "abc" }
{ "_id" : 2, "type" : "example", "key" : "222222", "value" : "def" }
{ "_id" : 3, "type" : "example", "key" : "222222", "value" : "ghi" }
{ "_id" : 4, "type" : "example", "key" : "333333", "value" : "jkl" }
{ "_id" : 5, "type" : "example", "key" : "333333", "value" : "mno" }
{ "_id" : 6, "type" : "example", "key" : "333333", "value" : "pqr" }
{ "_id" : 7, "type" : "example", "key" : "444444", "value" : "stu" }
{ "_id" : 8, "type" : "example", "key" : "444444", "value" : "vwx" }
{ "_id" : 9, "type" : "example", "key" : "444444", "value" : "yz1" }
{ "_id" : 10, "type" : "example", "key" : "444444", "value" : "234" }
Here is the query that I've been using to find duplicates based on key:
db.collection.aggregate([
{
$match: {
type: "example"
}
},
{
$group: {
_id: "$key",
count: {
$sum: 1
}
}
},
{
$match: {
count: {
$gt: 1
}
}
}
])
Which gives me an output of:
{
"_id": "222222",
"count": 2
},
{
"_id": "333333",
"count": 3
},
{
"_id": "444444",
"count": 4
}
The result I want to get instead:
3

You are almost there, just missing the last $count:
db.collection.aggregate([
{
$match: {
type: "example"
}
},
{
$group: {
_id: "$key",
count: {
$sum: 1
}
}
},
{
$match: {
count: {
$gt: 1
}
}
},
{
$count: "count"
}
])

Akrion's answer seems to be correct, but I can't test it because we're on an older version of MongoDB. A coworker gave me an alternative solution that works on 3.2 (not sure about other versions).
Adding .toArray() will convert the results to an array, and you can then get the size of the array using .length.
db.collection.aggregate([
{
$match: {
type: "example"
}
},
{
$group: {
_id: "$key",
count: {
$sum: 1
}
}
},
{
$match: {
count: {
$gt: 1
}
}
}
]).toArray().length

Related

How to find duplicate entries in collection using aggregation

{ "_id" : ObjectId("4f127fa55e7242718200002d"), "id":1, "name" : "foo"}
{ "_id" : ObjectId("4f127fa55e7242718200002d"), "id":2, "name" : "bar"}
{ "_id" : ObjectId("4f127fa55e7242718200002d"), "id":3, "name" : "baz"}
{ "_id" : ObjectId("4f127fa55e7242718200002d"), "id":4, "name" : "foo"}
{ "_id" : ObjectId("4f127fa55e7242718200002d"), "id":5, "name" : "bar"}
{ "_id" : ObjectId("4f127fa55e7242718200002d"), "id":6, "name" : "bar"}
I want to find all the duplicated entries in this collection by the "name" field using aggregation. E.g. "foo" appears twice and "bar" appears 3 times.
You can use group stage in aggrgation
db.collection.aggregate([{
$group: {
_id: "$name",
count: { $sum: 1 },
name: { $first: "$name" }
}
}])
You can group by name and count. And then filter with a count greater that 1.
db.collection.aggregate([
{
$group: {
_id: "$name",
count: { $sum: 1 }
}
},
{
$match:{count:{$gt:1}}
}
])
Output:
{ "_id" : "foo", "count":2}
{ "_id" : "bar", "count":3}

MongoDB aggregate array of objects together by object id and count occurences

I'm trying to figure out what I'm doing wrong, I have collected the following, "Subset of data", "Desired output"
This is how my data objects look
[{
"survey_answers": [
{
"id": "9ca01568e8dbb247", // As they are, this is the key to groupBy
"option_answer": 5, // Represent the index of the choosen option
"type": "OPINION_SCALE" // Opinion scales are 0-10 (meaning elleven options)
},
{
"id": "ba37125ec32b2a99",
"option_answer": 3,
"type": "LABELED_QUESTIONS" // Labeled questions are 0-x (they can change it from survey to survey)
}
],
"survey_id": "test"
},
{
"survey_answers": [
{
"id": "9ca01568e8dbb247",
"option_answer": 0,
"type": "OPINION_SCALE"
},
{
"id": "ba37125ec32b2a99",
"option_answer": 3,
"type": "LABELED_QUESTIONS"
}
],
"survey_id": "test"
}]
My desired output is:
[
{
id: '9ca01568e8dbb247'
results: [
{ _id: 5, count: 1 },
{ _id: 0, count: 1 }
]
},
{
id: 'ba37125ec32b2a99'
results: [
{ _id: 3, count: 2 }
]
}
]
Active query
Model.aggregate([
{
$match: {
'survey_id': survey_id
}
},
{
$unwind: "$survey_answers"
},
{
$group: {
_id: "$survey_answers.option_answer",
count: {
$sum: 1
}
}
}
])
Current output
[
{
"_id": 0,
"count": 1
},
{
"_id": 3,
"count": 2
},
{
"_id": 5,
"count": 1
}
]
I added your records to my db. Post that I tried your commands one by one.
$unwind results you similar to -
> db.survey.aggregate({$unwind: "$survey_answers"})
{ "_id" : ObjectId("5c3859e459875873b5e6ee3c"), "survey_answers" : { "id" : "9ca01568e8dbb247", "option_answer" : 5, "type" : "OPINION_SCALE" }, "survey_id" : "test" }
{ "_id" : ObjectId("5c3859e459875873b5e6ee3c"), "survey_answers" : { "id" : "ba37125ec32b2a99", "option_answer" : 3, "type" : "LABELED_QUESTIONS" }, "survey_id" : "test" }
{ "_id" : ObjectId("5c3859e459875873b5e6ee3d"), "survey_answers" : { "id" : "9ca01568e8dbb247", "option_answer" : 0, "type" : "OPINION_SCALE" }, "survey_id" : "test" }
{ "_id" : ObjectId("5c3859e459875873b5e6ee3d"), "survey_answers" : { "id" : "ba37125ec32b2a99", "option_answer" : 3, "type" : "LABELED_QUESTIONS" }, "survey_id" : "test" }
I am not adding code for match since that is okay in your query as well
The grouping would be -
> db.survey.aggregate({$unwind: "$survey_answers"},{$group: { _id: { 'optionAnswer': "$survey_answers.option_answer", 'id':"$survey_answers.id"}, count: { $sum: 1}}})
{ "_id" : { "optionAnswer" : 0, "id" : "9ca01568e8dbb247" }, "count" : 1 }
{ "_id" : { "optionAnswer" : 3, "id" : "ba37125ec32b2a99" }, "count" : 2 }
{ "_id" : { "optionAnswer" : 5, "id" : "9ca01568e8dbb247" }, "count" : 1 }
You can group on $survey_answers.id to bring it into projection.
The projection is what you're missing in your query -
> db.survey.aggregate({$unwind: "$survey_answers"},{$group: { _id: { 'optionAnswer': "$survey_answers.option_answer", 'id':'$survey_answers.id'}, count: { $sum: 1}}}, {$project : {answer: '$_id.optionAnswer', id: '$_id.id', count: '$count', _id:0}})
{ "answer" : 0, "id" : "9ca01568e8dbb247", "count" : 1 }
{ "answer" : 3, "id" : "ba37125ec32b2a99", "count" : 2 }
{ "answer" : 5, "id" : "9ca01568e8dbb247", "count" : 1 }
Further you can add a group on id and add results to a set. And your final query would be -
db.survey.aggregate(
{$unwind: "$survey_answers"},
{$group: {
_id: { 'optionAnswer': "$survey_answers.option_answer", 'id':'$survey_answers.id'},
count: { $sum: 1}
}},
{$project : {
answer: '$_id.optionAnswer',
id: '$_id.id',
count: '$count',
_id:0
}},
{$group: {
_id:{id:"$id"},
results: { $addToSet: {answer: "$answer", count: '$count'} }
}},
{$project : {
id: '$_id.id',
answer: '$results',
_id:0
}})
Hope this helps.

How to use $unwind and $match with MongoDB?

I have a document of the following format:
{
"P": {
"Workspaces": [
{
"Key": "Value1",
"Size": 2.27,
"Status": 'something'
},
{
"Key": "Value2",
"Size": 3.27,
"Status": 'somethingelse'
}
]
}
}
The following query returns the average correctly.
db.collection.aggregate([
{ $unwind: "$P.Workspaces" },
{ $group: { _id: "$P.Workspaces.Key", average: { $avg: "$P.Workspaces.Size" } } }
])
I am trying to add a match to filter the status as shown below. However I am not getting no result even though there are documents with matching status. I am trying to filter the results before taking the average. Am I missing something here?
db.collection.aggregate([
{ $unwind: "$P.Workspaces" },
{ $match: { "P.Workspaces.Status":'something'}},
{ $group: { _id: "$P.Workspaces.Key", average: { $avg: "$P.Workspaces.Size" } } }
])
db.articles.aggregate(
[ { $match : { author : "dave" } } ]
);
The examples use a collection named articles with the following documents:
{ "_id" : ObjectId("512bc95fe835e68f199c8686"), "author" : "dave", "score" : 80, "views" : 100 } { "_id" : ObjectId("512bc962e835e68f199c8687"), "author" : "dave", "score" : 85, "views" : 521 } { "_id" : ObjectId("55f5a192d4bede9ac365b257"), "author" : "ahn", "score" : 60, "views" : 1000 } { "_id" : ObjectId("55f5a192d4bede9ac365b258"), "author" : "li", "score" : 55, "views" : 5000 } { "_id" : ObjectId("55f5a1d3d4bede9ac365b259"), "author" : "annT", "score" : 60, "views" : 50 }

How can I do match after second level unwind in mongodb?

I am working on a software that uses MongoDB as a database. I have a collection like this (this is just one document)
{
"_id" : ObjectId("5aef51e0af42ea1b70d0c4dc"),
"EndpointId" : "89799bcc-e86f-4c8a-b340-8b5ed53caf83",
"DateTime" : ISODate("2018-05-06T19:05:04.574Z"),
"Url" : "test",
"Tags" : [
{
"Uid" : "E2:02:00:18:DA:40",
"Type" : 1,
"DateTime" : ISODate("2018-05-06T19:05:04.574Z"),
"Sensors" : [
{
"Type" : 1,
"Value" : NumberDecimal("-98")
},
{
"Type" : 2,
"Value" : NumberDecimal("-65")
}
]
},
{
"Uid" : "12:3B:6A:1A:B7:F9",
"Type" : 1,
"DateTime" : ISODate("2018-05-06T19:05:04.574Z"),
"Sensors" : [
{
"Type" : 1,
"Value" : NumberDecimal("-95")
},
{
"Type" : 2,
"Value" : NumberDecimal("-59")
},
{
"Type" : 3,
"Value" : NumberDecimal("12.939770381907275")
}
]
}
]
}
and I want to run this query on it.
db.myCollection.aggregate([
{ $unwind: "$Tags" },
{
$match: {
$and: [
{
"Tags.DateTime": {
$gte: ISODate("2018-05-06T19:05:02Z"),
$lte: ISODate("2018-05-06T19:05:09Z"),
},
},
{ "Tags.Uid": { $in: ["C1:3D:CA:D4:45:11"] } },
],
},
},
{ $unwind: "$Tags.Sensors" },
{ $match: { "$Tags.Sensors.Type": { $in: [1, 2] } } },
{
$project: {
_id: 0,
EndpointId: "$EndpointId",
TagId: "$Tags.Uid",
Url: "$Url",
TagType: "$Tags.Type",
Date: "$Tags.DateTime",
SensorType: "$Tags.Sensors.Type",
Value: "$Tags.Sensors.Value",
},
},
])
the problem is, the second match (that checks $Tags.Sensors.Type) doesn't work and doesn't affect the result of the query.
How can I solve that?
If this is not the right way, what is the right way to run these conditions?
The $match stage accepts field names without a leading $ sign. You've done that correctly in your first $match stage but in the second one you write $Tags.Sensors.Type. Simply removing the leading $ sign should make your query work.
Mind you, the whole thing can be a bit simplified (and some beautification doesn't hurt, either):
You don't need to use $and in your example since it's assumed by default if you specify more than one criterion in a filter.
The $in that you use for the Tags.Sensors.Type filter can be a simple : kind of equality operator unless you have more than one element in the list of acceptable values.
In the $project stage, instead of (kind of) duplicating identical field names you can use the <field>: 1 syntax unless the order of the fields matters.
So the final query would be something like this.
db.myCollection.aggregate([
{
"$unwind" : "$Tags"
},
{
"$match" : {
"Tags.DateTime" : { "$gte" : ISODate("2018-05-06T19:05:02Z"), "$lte" : ISODate("2018-05-06T19:05:09Z") },
"Tags.Uid" : { "$in" : ["C1:3D:CA:D4:45:11"] }
}
}, {
"$unwind" : "$Tags.Sensors"
}, {
"$match" : {
"Tags.Sensors.Type" : { "$in" : [1,2] }
}
},
{
"$project" : {
"_id" : 0,
"EndpointId" : 1,
"TagId" : "$Tags.Uid",
"Url" : 1,
"TagType" : "$Tags.Type",
"Date" : "$Tags.DateTime",
"SensorType" : "$Tags.Sensors.Type",
"Value" : "$Tags.Sensors.Value"
}
}])

Mongodb aggregate by day and delete duplicate value

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
}
})