Consider the following document that is output of an aggregation pipeline:
{ "_id" : 1, "results" : [
{ "status" : "HOLD", "footage" : 43.01, "pieces" : 1 },
{ "status" : "ACCEPTED", "footage" : 80.90, "pieces" : 2 },
{ "status" : "REJECTED", "footage" : 40.00, "pieces" : 1 }
]}
I am trying to create custom keys that concatenate the status with the footage and piece fields resulting in:
{ "_id" : 1, "results" :
{
"HOLD_footage": 43.01,
"HOLD_pieces":1,
"ACCEPTED_footage": 80.90,
"ACCEPTED_pieces": 2,
"REJECTED_footage":40.00,
"REJECTED_pieces":1
}
}
You can do following:
use $map to build the k-v tuples with key you want(i.e. HOLD_footage...)
use $concatArrays to group back the arrays of k-v tuples
use $objectToArray to get back the array form you expected
Here is the Mongo playground for your reference.
Related
I have a collection setup with documents that look like :
{
"_id" : ObjectId("5c786d9486c1140b1452d777"),
"code" : "TEST-123",
"owner" : "John",
"cars" : [
{
"carPlate" : "QPZ-756",
"carColor" : "blue"
},
{
"carPlate" : "REF-473",
"carColor" : "red"
}
],
}
I'm looking for an mongo aggregate query that grabs each carPlate and outputs the following for every document in the collection
{
"carPlate" : "QPZ-756",
"owner" : "John",
"code" : "TEST-123",
},
{
"carPlate" : "REF-473",
"owner" : "John",
"code" : "TEST-123",
},
I had a look at the $map operator, would this be a good place to start?
I would use $unwind to flatten the array followed by $mergeObjects to combine keys along with $replaceRoot to promote the merge documents to the top.
Something like
db.colname.aggregate([
{$unwind:"$cars"},
{$replaceRoot:{newRoot:{$mergeObjects:[{owner:"$owner"}, "$cars"]}}}
])
i have some collections for our project.
Casts collection contains movie casts
Contents collection contains movie contents
i want to run aggregate lookup for get information about movie casts with position type.
i removed collections details unnecessary fields.
Casts details:
{
"_id" : ObjectId("5a6cf47415621604942386cd"),
"fa_name" : "",
"en_name" : "Ehsan",
"fa_bio" : "",
"en_bio" : ""
}
Contents details:
{
"_id" : ObjectId("5a6b8b734f1408137f79e2cc"),
"casts" : [
{
"_id" : ObjectId("5a6cf47415621604942386cd"),
"fa_fictionName" : "",
"en_fictionName" : "Ehsan2",
"positionType" : {
"id" : 3,
"fa_name" : "",
"en_name" : "Director"
}
},
{
"_id" : ObjectId("5a6cf47415621604942386cd"),
"fa_fictionName" : "",
"en_fictionName" : "Ehsan1",
"positionType" : {
"id" : 3,
"fa_name" : "",
"en_name" : "Writers"
}
}
],
"status" : 0,
"created" : Timestamp(1516997542, 4),
"updated" : Timestamp(1516997542, 5)
}
when i run aggregate lookup with bellow query, in new generated lookup array only one casts contents If in accordance with above casts array value aggregate lookup should return two casts content with two type. in casts array value exists two type of casts, 1) writers and directors. but returned director casts content. _casts should contains two object not one object!
aggregate lookup query:
{$lookup:{from:"casts",localField:"casts._id",foreignField:"_id",as:"_casts"}}
result:
{
"_id" : ObjectId("5a6b8b734f1408137f79e2cc"),
"casts" : [
{
"_id" : ObjectId("5a6cf47415621604942386cd"),
"fa_fictionName" : "",
"en_fictionName" : "Ehsan2",
"positionType" : {
"id" : 3,
"fa_name" : "",
"en_name" : "Director"
}
},
{
"_id" : ObjectId("5a6cf47415621604942386cd"),
"fa_fictionName" : "",
"en_fictionName" : "Ehsan1",
"positionType" : {
"id" : 3,
"fa_name" : "",
"en_name" : "Writers"
}
}
],
"_casts" : [
{
"_id" : ObjectId("5a6cf47415621604942386cd"),
"fa_name" : "",
"en_name" : "Ehsan",
"fa_bio" : "",
"en_bio" : ""
}
],
"status" : 0,
"created" : Timestamp(1516997542, 4),
"updated" : Timestamp(1516997542, 5)
}
EDIT-1
finally my problem is solved. i have only one problem with this query, this query doesn't show root document fields. finally solve this problem. finally query exists in EDIT-2.
query:
db.contents.aggregate([
{"$unwind":"$casts"},
{"$lookup":{"from":"casts","localField":"casts._id","foreignField":"_id","as":"casts.info"}},
{"$unwind":"$casts.info"},
{"$group":{"_id":"$_id", "casts":{"$push":"$casts"}}},
])
EDIT-2
db.contents.aggregate([
{"$unwind":"$casts"},
{"$lookup":{"from":"casts","localField":"casts._id","foreignField":"_id","as":"casts.info"}},
{"$unwind":"$casts.info"},
{$group:{"_id":"$_id", "data":{"$first":"$$ROOT"}, "casts":{"$push":"$casts"}}},
{$replaceRoot:{"newRoot":{"$mergeObjects":["$data",{"casts":"$casts"}]}}},
{$project:{"casts":0}}
]).pretty()
This is expected behavior.
From the docs,
If your localField is an array, you may want to add an $unwind stage
to your pipeline. Otherwise, the equality condition between the
localField and foreignField is foreignField: { $in: [
localField.elem1, localField.elem2, ... ] }.
So to join each local field array element with foreign field element you have to $unwind the local array.
db.content.aggregate([
{"$unwind":"$casts"},
{"$lookup":{"from":"casts","localField":"casts._id","foreignField":"_id","as":"_casts"}}
])
Vendor Collection
Items Collection
db.items.aggregate([
{ $match:
{"item_id":{$eq:"I001"}}
},
{
$lookup:{
from:"vendor",
localField:"vendor_id",
foreignField:"vendor_id",
as:"vendor_details"
}
},
{
$unwind:"$vendor_details"
},
{
$project:{
"_id":0,
"vendor_id":0,
"vendor_details.vendor_company_description":0,
"vendor_details._id":0,
"vendor_details.country":0,
"vendor_details.city":0,
"vendor_details.website":0
}
}
]);
Output
Your Casts collection shows only 1 document. Your Contents collection, likewise, shows only 1 document.
This is 1 to 1 - not 1 to 2. Aggregate is working as designed.
The Contents document has 2 "casts." These 2 casts are sub-documents. Work with those as sub-documents, or re-design your collections. I don't like using sub-documents unless I know I will not need to use them as look-ups or join on them.
I would suggest you re-design your collection.
Your Contents collection (it makes me think of "Movies") could look like this:
_id
title
releaseDate
genre
etc.
You can create a MovieCasts collection like this:
_id
movieId (this is _id from Contents collection, above)
castId (this is _id from Casts collection, below)
Casts
_id
name
age
etc.
I have a document schema in a test collection like this:
{
"_id" : NumberLong("A unique number"),
"text" : {
"characters_map" : {
"a" : 4,
"f" : 3,
"b" : 6,
...
"o" : 3
}
...
}
...
}
I want to count the sum of each character in the whole collection. I tried using the aggregation framework, but it doesn't seem I do it correct.
I began by calculating each character separately ( i.e the 'a'), but with no luck. My best approach is:
> db.test.aggregate([
{ "$group" : {
_id : { a_count : "$text.characters_map.a" },
counter : { "$sum" : "$text.characters_map.a" }
}
}
])
with a_count representing the name of the id.
which results to:
{ "_id" : { "a_map" : 8 }, "counter" : 8 }
{ "_id" : { "a_map" : 5 }, "counter" : 5 }
{ "_id" : { "a_map" : 7 }, "counter" : 21 }
...
Not false entirely, but not what I want. These results mean I have 1 document with a field of: { "a" : 8, ... }, another 1 document with: { "a" : 5, ... } and 3 documents with: { "a" : 7, ... }.
Is there any way to group these fields together at "a" level? Is my approach completely wrong?
You have to change your structure to something like below.(Preferred)
[{
"text" : { "characters_map" : [{"k":"a", "v":4}, {"k":"b", "v":8}, {"k":"c", "v":5}, {"k":"d", "v":4 }] }
}]
You can use aggregation the way you tried in your post.
db.test.aggregate([
{$unwind:"$text.characters_map"},
{$group:{_id:"$text.characters_map.k", counter:{$sum:"$text.characters_map.v"}}}
])
This is the solution if you can't change your structure.
You can use 3.4.4 version and use $objectToArray & $arrayToObject to switch between dynamic keys and label value pair.
Stage 1: Convert the dynamic characters_map keys into label value pair.
Stage 2 & 3: $unwind & $group on the characters and sum their counts.
Stage 4 & 5: Group back the output from last grouping into array of key value pairs followed by $arrayToObject to convert the key value pairs into dynamic keys.
db.test.aggregate([
{$addFields: {"text.characters_map": {$objectToArray: "$text.characters_map"}}},
{$unwind:"$text.characters_map"},
{$group:{_id:"$text.characters_map.k", counter:{$sum:"$text.characters_map.v"}}},
{$group:{_id:null, arraykeyval:{$push:{k:"$_id", v:"$counter"}}}},
{$project:{result: {$arrayToObject:"$arraykeyval"}}}
])
I have a mongo document like
{ "_id" : 12, "location" : [ "Kannur","Hyderabad","Chennai","Bengaluru"] }
{ "_id" : 13, "location" : [ "Hyderabad","Chennai","Mysore","Ballary"] }
From this how can I get the location aggregation (distinct area count).
some thing like
Hyderabad 2,
Kannur 1,
Chennai 2,
Bengaluru 1,
Mysore 1,
Ballary 1
Using aggregation you cannot get the exact output that you want. One of the limitations of aggregation pipeline is its inability to transform values to keys in the output document.
For example, Kannur is one of the values of the location field, in the input document. In your desired output structure it needs to be the key("kannur":1). This is not possible using aggregation. While, this can be used achieving map-reduce, you can however get a very closely related and useful structure using aggregation.
Unwind the location array.
Group by the location fields, get the count of individual locations
using the $sum operator.
Group again all the documents once again to get a consolidated array
of results.
Code:
db.collection.aggregate([
{$unwind:"$location"},
{$group:{"_id":"$location","count":{$sum:1}}},
{$group:{"_id":null,"location_details":{$push:{"location":"$_id",
"count":"$count"}}}},
{$project:{"_id":0,"location_details":1}}
])
Sample o/p:
{
"location_details" : [
{
"location" : "Ballary",
"count" : 1
},
{
"location" : "Mysore",
"count" : 1
},
{
"location" : "Bengaluru",
"count" : 1
},
{
"location" : "Chennai",
"count" : 2
},
{
"location" : "Hyderabad",
"count" : 2
},
{
"location" : "Kannur",
"count" : 1
}
]
}
I have a number of Mongodb documents of the following form:
{
"auditedId" : "53d0f648e4b064e8d746b31c",
"modifications" : [
{
"auditRecordId" : ObjectId("53d0f648e4b064e8d746b31d"),
"modified" : "2014-07-22 18:33:05"
},
{
"auditRecordId" : ObjectId("53d0f648e4b064e8d746b31e"),
"modified" : "2014-07-24 14:15:27"
},
{
"auditRecordId" : ObjectId("53d0f648e4b064e8d746b31f"),
"modified" : "2014-07-24 12:04:24"
}
]
}
For each of these documents I want to find "auditRecordId" value which corresponds to the latest modification. In the given example I want to retrieve
"auditRecordId" : ObjectId("53d0f648e4b064e8d746b31e")
Or, even better:
{
"auditRecordId" : ObjectId("53d0f648e4b064e8d746b31e"),
"modified" : "2014-07-24 14:15:27"
}
Is there any way how I can do this without writing map-reduce functions?
Whenever you have an array in your document, the aggregate method is your friend :)
db.foo.aggregate([
// De-normalize the 'modifications' array
{"$unwind":"$modifications"},
// Sort by 'modifications.modified' descending
{"$sort":{"modifications.modified":-1}},
// Pick the first one i.e., the max
{"$limit":1}
])
Output:
{
"result" : [
{
"_id" : ObjectId("53d12be57a462c7459b6f1c7"),
"auditedId" : "53d0f648e4b064e8d746b31c",
"modifications" : {
"auditRecordId" : ObjectId("53d0f648e4b064e8d746b31e"),
"modified" : "2014-07-24 14:15:27"
}
}
],
"ok" : 1
}
Just to illustrate the $unwind operator, I used the above query with $limit. If you have multiple documents of the above format, and you want to retrieve the latest modification in each, you'll have to add another $group phase in your aggregation pipeline and use the $first operator:
db.foo.aggregate([
{"$unwind":"$modifications"},
{"$sort":{"modifications.modified":-1}},
{"$group":{
"_id" : "$auditedId",
"modifications" : {$first:"$modifications"}}}
])