I would like to retrieve a sub document from a document in MongoDB. I have the following document:
{
"_id" : "10000",
"password" : "password1",
"name" : "customer1",
"enabled" : true,
"channels" : [
{
"id" : "10000-1",
"name" : "cust1chan1",
"enabled" : true
},
{
"id" : "10000-2",
"name" : "cust1chan2",
"enabled" : true
}
]
}
The result I would like is:
{
"id" : "10000-1",
"name" : "cust1chan1",
"enabled" : true
}
However, the best I can do so far is using the following query:
db.customer.find({"channels.id" : "10000-1"}, {"channels.$" : 1, "_id" : 0})
But this gives me the following result:
{
"channels" : [
{
"id" : "10000-1",
"name" : "cust1chan1",
"enabled" : true
}
]
}
Does anyone know if it is possible to write a query that will give me my desired result? Any help would be much appreciated.
You can do it with Aggregation Framework. Query will be something like :
db.customer.aggregate([
{$unwind : "$channels"},
{$match : {"channels.id" : "10000-1"}},
{$project : {_id : 0,
id : "$channels.id",
name : "$channels.name",
enabled : "$channels.enabled"}}
])
Using MongoDB 3.4.4 and newer, the aggregation framework offers a number of operators that you can use to return the desired subdocument.
Consider running an aggregate pipeline that uses a single $replaceRoot stage to promote the filtered subdocument to the top-level and replace all other fields.
Filtering the subdocument requires the $filter operator which selects a subset of an array to return based on the specified condition i.e. returns an array with only those elements that match the condition. You can then convert the single array element to a document by using the $arrayElemAt operator
Overall running this aggregate operation will yield the desired result:
db.customer.aggregate([
{ "$replaceRoot": {
"newRoot": {
"$arrayElemAt": [
{ "$filter": {
"input": "$channels",
"as": "channel",
"cond": { /* resolve to a boolean value and determine if an element should be included in the output array. */
"$eq": ["$$channel.id", "10000-1"]
}
} },
0 /* the element at the specified array index */
]
}
} }
])
Output
{
"id" : "10000-1",
"name" : "cust1chan1",
"enabled" : true
}
Related
I have collection in which documents are like:
{
_id: ObjectId(),
user: ObjectId(),
studentName: String,
createdAt: Date,
isAbondoned: boolean
}
example of documents are:
1-
{
"_id" : ObjectId("56cd2d36a489a5b875902f0e"),
"user" : ObjectId("56c4cafabd5f92cd78ae49d4"),
"studentName" : "Aman",
"createdAt" : ISODate("2016-02-24T04:10:30.486+0000"),
"isAbandoned" : true
}
2-
{
"_id" : ObjectId("56cd2dcda489a5b875902fcd"),
"user" : ObjectId("56c4cafabd5f92cd78ae49d4"),
"studentName" : "Aman",
"createdAt" : ISODate("2016-02-24T04:13:01.932+0000"),
"isAbandoned" : false
}
3-
{
"_id" : ObjectId("56cee51503b7cb7b0eda9c4c"),
"user" : ObjectId("56c85244bd5f92cd78ae4bc1"),
"studentName" : "Rajeev",
"createdAt" : ISODate("2016-02-25T11:27:17.281+0000"),
"isAbandoned" : true,
}
Now I want to find the list of students for which their 'isAbandoned' is true for their last 'createdAt' document.
Required output for above example is:
{
"user" : ObjectId("56c85244bd5f92cd78ae4bc1"),
"studentName" : "Rajeev"
}
because for studentName "Aman" max(createdAt) is 2nd document and 'isAbandoned' is false for that.
The best way to do this is using the aggregation framework. You need to $group your documents by "user" and return the last document for each user using the $last accumulator operator but for this to work, you need a preliminary sorting stage using the $sort aggregation pipeline operator. To sort your documents, you need to consider both the "createdAt" field and the "user" field.
The last stage in the pipeline is the $match stage where you select only those last documents where "isAbandoned" equals true.
db.students.aggregate([
{ "$sort": { "user": 1, "createdAt": 1 } },
{ "$group": {
"_id": "$user",
"last": { "$last": "$$ROOT" }
}},
{ "$match": { "last.isAbandoned": true } }
])
which returns something like this:
{
"_id" : ObjectId("56c85244bd5f92cd78ae4bc1"),
"last" : {
"_id" : ObjectId("56cee51503b7cb7b0eda9c4c"),
"user" : ObjectId("56c85244bd5f92cd78ae4bc1"),
"studentName" : "Rajeev",
"createdAt" : ISODate("2016-02-25T11:27:17.281Z"),
"isAbandoned" : true
}
}
To get the expected result, we need to use the $replaceRoot pipeline operator starting from verion 3.4 to promote the embedded document to the top level
{
$replaceRoot: { newRoot: "$last" }
}
In older version, you need to use the $project aggregation pipeline operation to reshape our documents. So if we extend our pipeline with the following stage:
{
"$project": {
"_id": "$last._id",
"user": "$last.user",
"studentName": "$last.studentName",
"createdAt": "$last.createdAt",
"isAbandoned": "$last.isAbandoned"
}}
it produces the expected output:
{
"_id" : ObjectId("56cee51503b7cb7b0eda9c4c"),
"user" : ObjectId("56c85244bd5f92cd78ae4bc1"),
"studentName" : "Rajeev",
"createdAt" : ISODate("2016-02-25T11:27:17.281Z"),
"isAbandoned" : true
}
This is a good example of need to group data by specific filed (createdAt) and then compare result set match criteria.
find max by student id,
match only entries by max entry = createdAt
check if they are passing criteria
reshape document
Code:
db.student.aggregate([{
$group : {
_id : "$user",
created : {
$max : "$createdAt"
},
documents : {
$push : "$$ROOT"
}
}
}, {
$project : {
_id : 0,
documents : {
$filter : {
input : "$documents",
as : "item",
cond : {
$eq : ["$$item.createdAt", "$created"]
}
}
}}
}, {
$match : {
"documents.isAbandoned" : true
}},
{ $unwind : "$documents" },
{
$project : {
_id : "$documents._id",
user : "$documents.user",
studentName : "$documents.studentName",
createdAt : "$documents.createdAt",
isAbandoned : "$documents.isAbandoned",
}}
])
I have collection in which documents are like:
{
_id: ObjectId(),
user: ObjectId(),
studentName: String,
createdAt: Date,
isAbondoned: boolean
}
example of documents are:
1-
{
"_id" : ObjectId("56cd2d36a489a5b875902f0e"),
"user" : ObjectId("56c4cafabd5f92cd78ae49d4"),
"studentName" : "Aman",
"createdAt" : ISODate("2016-02-24T04:10:30.486+0000"),
"isAbandoned" : true
}
2-
{
"_id" : ObjectId("56cd2dcda489a5b875902fcd"),
"user" : ObjectId("56c4cafabd5f92cd78ae49d4"),
"studentName" : "Aman",
"createdAt" : ISODate("2016-02-24T04:13:01.932+0000"),
"isAbandoned" : false
}
3-
{
"_id" : ObjectId("56cee51503b7cb7b0eda9c4c"),
"user" : ObjectId("56c85244bd5f92cd78ae4bc1"),
"studentName" : "Rajeev",
"createdAt" : ISODate("2016-02-25T11:27:17.281+0000"),
"isAbandoned" : true,
}
Now I want to find the list of students for which their 'isAbandoned' is true for their last 'createdAt' document.
Required output for above example is:
{
"user" : ObjectId("56c85244bd5f92cd78ae4bc1"),
"studentName" : "Rajeev"
}
because for studentName "Aman" max(createdAt) is 2nd document and 'isAbandoned' is false for that.
The best way to do this is using the aggregation framework. You need to $group your documents by "user" and return the last document for each user using the $last accumulator operator but for this to work, you need a preliminary sorting stage using the $sort aggregation pipeline operator. To sort your documents, you need to consider both the "createdAt" field and the "user" field.
The last stage in the pipeline is the $match stage where you select only those last documents where "isAbandoned" equals true.
db.students.aggregate([
{ "$sort": { "user": 1, "createdAt": 1 } },
{ "$group": {
"_id": "$user",
"last": { "$last": "$$ROOT" }
}},
{ "$match": { "last.isAbandoned": true } }
])
which returns something like this:
{
"_id" : ObjectId("56c85244bd5f92cd78ae4bc1"),
"last" : {
"_id" : ObjectId("56cee51503b7cb7b0eda9c4c"),
"user" : ObjectId("56c85244bd5f92cd78ae4bc1"),
"studentName" : "Rajeev",
"createdAt" : ISODate("2016-02-25T11:27:17.281Z"),
"isAbandoned" : true
}
}
To get the expected result, we need to use the $replaceRoot pipeline operator starting from verion 3.4 to promote the embedded document to the top level
{
$replaceRoot: { newRoot: "$last" }
}
In older version, you need to use the $project aggregation pipeline operation to reshape our documents. So if we extend our pipeline with the following stage:
{
"$project": {
"_id": "$last._id",
"user": "$last.user",
"studentName": "$last.studentName",
"createdAt": "$last.createdAt",
"isAbandoned": "$last.isAbandoned"
}}
it produces the expected output:
{
"_id" : ObjectId("56cee51503b7cb7b0eda9c4c"),
"user" : ObjectId("56c85244bd5f92cd78ae4bc1"),
"studentName" : "Rajeev",
"createdAt" : ISODate("2016-02-25T11:27:17.281Z"),
"isAbandoned" : true
}
This is a good example of need to group data by specific filed (createdAt) and then compare result set match criteria.
find max by student id,
match only entries by max entry = createdAt
check if they are passing criteria
reshape document
Code:
db.student.aggregate([{
$group : {
_id : "$user",
created : {
$max : "$createdAt"
},
documents : {
$push : "$$ROOT"
}
}
}, {
$project : {
_id : 0,
documents : {
$filter : {
input : "$documents",
as : "item",
cond : {
$eq : ["$$item.createdAt", "$created"]
}
}
}}
}, {
$match : {
"documents.isAbandoned" : true
}},
{ $unwind : "$documents" },
{
$project : {
_id : "$documents._id",
user : "$documents.user",
studentName : "$documents.studentName",
createdAt : "$documents.createdAt",
isAbandoned : "$documents.isAbandoned",
}}
])
I have one collection named 'ctrlcharts'.
e.g.
{
"_id" : ObjectId("57fc695492af567031246736"),
"deviceId" : "A001",
"sensorId" : "S003",
"time" : "2016/10/11 12:23:50",
"charts" : [
{
"sensor" : "ch_11",
"value" : 120
},
{
"sensor" : "ch_12",
"value" : 150
}
]
}
How to filter "sensor" : "ch_11" and aggregate data from one collection into another format using MongoDB
e.g.
{
"time" : "2016/10/11 12:23:50",
"sensor" : "ch_12",
"value" : 150
}
I tried below code
db.ctrlcharts.aggregate([
{ $match: {"deviceId" : "A001", "sensorId" : "S003", "time" : "2016/10/11 12:23:50"}},
{ $project: {
_id: 0,
time : 1 ,
sensor : "$charts.sensor"
value : "$charts.value"
}
}
])
But I got the result as
{
"time" : "2016/10/11 12:23:50",
"sensor" : ["ch_11","ch_12"],
"value" : [120,150]
}
Thanks
You tried best....just use $unwind
db.ctrlcharts.aggregate(
{$unwind:"$charts"},
{$match: {"deviceId" :"A001", "charts.sensor":"ch_12", "time" : "2016/10/11 12:23:50"}},
{$project:{_id:0,time:1, sensor : "$charts.sensor", value :"$charts.value"}}).pretty()
You can use $unwind (aggregation) to separate charts array.
db.ctrlcharts.aggregate( [ { $unwind : "$charts" } ] )
This will produce result like -
{ "_id" : ObjectId("57ff397a007c43ecacf10512"), "deviceId" : "A001", "sensorId" : "S003", "time" : "2016/10/11 12:23:50", "charts" : { "sensor" : "ch_11", "value" : 120 } }
{ "_id" : ObjectId("57ff397a007c43ecacf10512"), "deviceId" : "A001", "sensorId" : "S003", "time" : "2016/10/11 12:23:50", "charts" : { "sensor" : "ch_12", "value" : 150 } }
and then use your match query
Use the $arrayElemAt and $filter operators to query the array more efficiently without the need to $unwind. The reason why $unwind is not as efficient is that it produces a cartesian product of the documents i.e. a copy of each document per array entry, which uses more memory (possible memory cap on aggregation pipelines of 10% total memory) and therefore takes time to produce as well processing the documents during the flattening process.
The $filter will return a subset of the array that only contains the elements that match the filter condition. The $arrayElemAt operator then returns the element from the filtered array at the specified array index to give you the subdocument you need.
A further $project is necessary to flatten the fields to give you the desired result:
db.ctrlcharts.aggregate([
{ "$match": {
"deviceId": "A001",
"sensorId": "S003",
"time": "2016/10/11 12:23:50",
"charts.sensor": "ch_11"
} },
{
"$project": {
"time": 1,
"chart": {
"$arrayElemAt": [
"$filter": {
"input": "$charts",
"as": "item",
"cond": { "$eq": ["$$item.sensor", "ch_11"] }
}, 0
]
}
}
},
{
"$project": {
"_id": 0,
"time": 1,
"sensor": "$chart.sensor"
"value": "$chart.value"
}
}
])
I have joined two collections on one field using '$lookup', while actually I needed two fields to have a unique match. My next step would be to unwind the array containing different values of the second field I need for a unique match and then compare these to the value of the second field it needs to match higher up. However, the second line in the snippet below returns no results.
// Request only the page that has been viewed
{ '$unwind' : '$DSpub.PublicationPages'},
{ '$match' : {'pageId' : '$DSpub.PublicationPages.PublicationPageId' } }
Is there a more appropriate way to do this? Or can I avoid doing this altogether by unwinding the "from" collection before performing the '$lookup', and then match both fields?
This is not as easy at it looks.
$match does not operate on dynamic data (that means we are comparing static value against data set). To overcome that - we can use $project phase to add a bool static flag, that can be utilized by $match
Please see example below:
Having input collection like this:
[{
"_id" : ObjectId("56be1b51a0f4c8591f37f62b"),
"name" : "Alice",
"sub_users" : [{
"_id" : ObjectId("56be1b51a0f4c8591f37f62a")
}
]
}, {
"_id" : ObjectId("56be1b51a0f4c8591f37f62a"),
"name" : "Bob",
"sub_users" : [{
"_id" : ObjectId("56be1b51a0f4c8591f37f62a")
}
]
}
]
We want to get only fields where _id and $docs.sub_users._id" are same, where docs are $lookup output.
db.collecction.aggregate([{
$lookup : {
from : "collecction",
localField : "_id",
foreignField : "_id",
as : "docs"
}
}, {
$unwind : "$docs"
}, {
$unwind : "$docs.sub_users"
}, {
$project : {
_id : 0,
fields : "$$ROOT",
matched : {
$eq : ["$_id", "$docs.sub_users._id"]
}
}
}, {
$match : {
matched : true
}
}
])
that gives output:
{
"fields" : {
"_id" : ObjectId("56be1b51a0f4c8591f37f62a"),
"name" : "Bob",
"sub_users" : [
{
"_id" : ObjectId("56be1b51a0f4c8591f37f62a")
}
],
"docs" : {
"_id" : ObjectId("56be1b51a0f4c8591f37f62a"),
"name" : "Bob",
"sub_users" : {
"_id" : ObjectId("56be1b51a0f4c8591f37f62a")
}
}
},
"matched" : true
}
I have collection in which documents are like:
{
_id: ObjectId(),
user: ObjectId(),
studentName: String,
createdAt: Date,
isAbondoned: boolean
}
example of documents are:
1-
{
"_id" : ObjectId("56cd2d36a489a5b875902f0e"),
"user" : ObjectId("56c4cafabd5f92cd78ae49d4"),
"studentName" : "Aman",
"createdAt" : ISODate("2016-02-24T04:10:30.486+0000"),
"isAbandoned" : true
}
2-
{
"_id" : ObjectId("56cd2dcda489a5b875902fcd"),
"user" : ObjectId("56c4cafabd5f92cd78ae49d4"),
"studentName" : "Aman",
"createdAt" : ISODate("2016-02-24T04:13:01.932+0000"),
"isAbandoned" : false
}
3-
{
"_id" : ObjectId("56cee51503b7cb7b0eda9c4c"),
"user" : ObjectId("56c85244bd5f92cd78ae4bc1"),
"studentName" : "Rajeev",
"createdAt" : ISODate("2016-02-25T11:27:17.281+0000"),
"isAbandoned" : true,
}
Now I want to find the list of students for which their 'isAbandoned' is true for their last 'createdAt' document.
Required output for above example is:
{
"user" : ObjectId("56c85244bd5f92cd78ae4bc1"),
"studentName" : "Rajeev"
}
because for studentName "Aman" max(createdAt) is 2nd document and 'isAbandoned' is false for that.
The best way to do this is using the aggregation framework. You need to $group your documents by "user" and return the last document for each user using the $last accumulator operator but for this to work, you need a preliminary sorting stage using the $sort aggregation pipeline operator. To sort your documents, you need to consider both the "createdAt" field and the "user" field.
The last stage in the pipeline is the $match stage where you select only those last documents where "isAbandoned" equals true.
db.students.aggregate([
{ "$sort": { "user": 1, "createdAt": 1 } },
{ "$group": {
"_id": "$user",
"last": { "$last": "$$ROOT" }
}},
{ "$match": { "last.isAbandoned": true } }
])
which returns something like this:
{
"_id" : ObjectId("56c85244bd5f92cd78ae4bc1"),
"last" : {
"_id" : ObjectId("56cee51503b7cb7b0eda9c4c"),
"user" : ObjectId("56c85244bd5f92cd78ae4bc1"),
"studentName" : "Rajeev",
"createdAt" : ISODate("2016-02-25T11:27:17.281Z"),
"isAbandoned" : true
}
}
To get the expected result, we need to use the $replaceRoot pipeline operator starting from verion 3.4 to promote the embedded document to the top level
{
$replaceRoot: { newRoot: "$last" }
}
In older version, you need to use the $project aggregation pipeline operation to reshape our documents. So if we extend our pipeline with the following stage:
{
"$project": {
"_id": "$last._id",
"user": "$last.user",
"studentName": "$last.studentName",
"createdAt": "$last.createdAt",
"isAbandoned": "$last.isAbandoned"
}}
it produces the expected output:
{
"_id" : ObjectId("56cee51503b7cb7b0eda9c4c"),
"user" : ObjectId("56c85244bd5f92cd78ae4bc1"),
"studentName" : "Rajeev",
"createdAt" : ISODate("2016-02-25T11:27:17.281Z"),
"isAbandoned" : true
}
This is a good example of need to group data by specific filed (createdAt) and then compare result set match criteria.
find max by student id,
match only entries by max entry = createdAt
check if they are passing criteria
reshape document
Code:
db.student.aggregate([{
$group : {
_id : "$user",
created : {
$max : "$createdAt"
},
documents : {
$push : "$$ROOT"
}
}
}, {
$project : {
_id : 0,
documents : {
$filter : {
input : "$documents",
as : "item",
cond : {
$eq : ["$$item.createdAt", "$created"]
}
}
}}
}, {
$match : {
"documents.isAbandoned" : true
}},
{ $unwind : "$documents" },
{
$project : {
_id : "$documents._id",
user : "$documents.user",
studentName : "$documents.studentName",
createdAt : "$documents.createdAt",
isAbandoned : "$documents.isAbandoned",
}}
])