I have the following document structure
{
"timestamp" : 13512493603565120,<br>
"value" : 1,<br>
"y" : 42,<br>
"M" : 513,<br>
"w" : 2234,<br>
"d" : 15639,<br>
"S" : 46918,<br>
"h" : 375347,<br>
"m" : 22520822,<br>
"s" : 1351249360,<br>
"_id" : ObjectId("508aa61100b5457c04000001"),<br>
"__v" : 0<br>
}
I have a mongodb aggregate as follows to sum up values grouping by field y:
aggregate({
$group : {_id : "$y", value:{$sum:4}}
})
This will give me
[
{
"_id": 42,
"value": 16
}
]
What I want now is to format this output so that it looks like this:
[
[13512493603565100, 2],
[13512493605167900, 1]
]
ie:
[
[<timestamp>,<sum of value grouped by field y>],
[<timestamp>,<sum of value grouped by field y>]
]
I looked at $project but I still cant figure out how I can use it to get the desired output
Not possible as of now apparently (using mapreduce or aggregate).
Hope this will be added soon.
Related
I wanted to update a collection to set a new Field with other inner field
it looks like to generate a person's full name .
MongoDB Enterprise > db.name.find()
{ "_id" : ObjectId("5d7ca743c45316e35251a49e"), "first" : "Don", "middle" : "Jhon", "last" : "Trump" }
{ "_id" : ObjectId("5d7ca75bc45316e35251a49f"), "first" : "Dila", "last" : "Tp" }
{ "_id" : ObjectId("5d7ca76dc45316e35251a4a0"), "first" : "Li", "last" : "Wei" }
I want to set the full name with $first +$middle + $last in One
update
I try to use update with an aggregation pipeline. this is a new feature in mongodb 4.2
db.name.updateMany({},[{$set:{full:{$concat: [ "$first", "$middle","$last" ] }}}])
but this result return a lot of null value when some field is missing .
db.name.find()
{ "_id" : ObjectId("5d7ca743c45316e35251a49e"), "first" : "Don", "middle" : "Jhon", "last" : "Trump", "full" : "DonJhonTrump" }
{ "_id" : ObjectId("5d7ca75bc45316e35251a49f"), "first" : "Dila", "last" : "Tp", "full" : null }
{ "_id" : ObjectId("5d7ca76dc45316e35251a4a0"), "first" : "Li", "last" : "Wei", "full" : null }
What you are looking for is ifNull function. Rewrite your query like this
db.name.updateMany({},[{$set:{full:{$concat: [ {$ifNull:["$first", ""]}, {$ifNull:["$middle", ""]},{$ifNull:["$last", ""]} ] }}}])
I also try use with $cond it also worked but more complicated
db.name.updateMany({},[{$set:{full:{$concat: [ "$first", {"$cond" :{if :{$gt:["$middle", null]},then :"$middle" ,else :""}},"$last" ] }}}])
put it here to help others if needed .
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 mongo document which has structure like
{
"_id" : "THIS_IS_A_DHP_USER_ID+2014-11-26",
"_class" : "weight",
"items" : [
{
"dateTime" : ISODate("2014-11-26T08:08:38.716Z"),
"value" : 98.5
},
{
"dateTime" : ISODate("2014-11-26T08:18:38.716Z"),
"value" : 95.5
},
{
"dateTime" : ISODate("2014-11-26T08:28:38.663Z"),
"value" : 90.5
}
],
"source" : "MANUAL",
"to" : ISODate("2014-11-26T08:08:38.716Z"),
"from" : ISODate("2014-11-26T08:08:38.716Z"),
"userId" : "THIS_IS_A_DHP_USER_ID",
"createdDate" : ISODate("2014-11-26T08:38:38.776Z")
}
{
"_id" : "THIS_IS_A_DHP_USER_ID+2014-11-25",
"_class" : "weight",
"items" : [
{
"dateTime" : ISODate("2014-11-25T08:08:38.716Z"),
"value" : 198.5
},
{
"dateTime" : ISODate("2014-11-25T08:18:38.716Z"),
"value" : 195.5
},
{
"dateTime" : ISODate("2014-11-25T08:28:38.716Z"),
"value" : 190.5
}
],
"source" : "MANUAL",
"to" : ISODate("2014-11-25T08:08:38.716Z"),
"from" : ISODate("2014-11-25T08:08:38.716Z"),
"userId" : "THIS_IS_A_DHP_USER_ID",
"createdDate" : ISODate("2014-11-26T08:38:38.893Z")
}
The query that want to fire on this document structure,
finding documents for a particular user id
unwinding the embedded array
Grouping the documents based over _id with -
summing the items.value of the embedded array
getting the minimum of the items.dateTime of the embedded array
Note. The sum and min, I want to get as a object i.e. { value : sum , dateTime : min of the items.dateTime} inside an array of items
Can this be achieved in an single aggregation call using push or some other technique.
When you group over a particular _id, and apply aggregation operators such as $min and $sum, there exists only one record per group(_id), that holds the sum and the minimum date for that group. So there is no way to obtain a different sum and a different minimum date for the same _id, which also logically makes no sense.
What you would want to do is:
db.collection.aggregate([
{$match:{"userId":"THIS_IS_A_DHP_USER_ID"}},
{$unwind:"$items"},
{$group:{"_id":"$_id",
"values":{$sum:"$items.value"},
"dateTime":{$min:"$items.dateTime"}}}
])
But in case when you do not query for a particular userId, then you would have multiple groups, each group having its own sum and min date. Then it makes sense to accumulate all these results together in an array using the $push operator.
db.collection.aggregate([
{$unwind:"$items"},
{$group:{"_id":"$_id",
"result":{$sum:"$items.value"},
"dateTime":{$min:"$items.dateTime"}}},
{$group:{"_id":null,"result":{$push:{"value":"$result",
"dateTime":"$dateTime",
"id":"$_id"}}}},
{$project:{"_id":0,"result":1}}
])
you should use following aggregation may it works
db.collectionName.aggregate(
{"$unwind":"$items"},
{"$match":{"userId":"THIS_IS_A_DHP_USER_ID"}},
{"$group":{"_id":"$_id","sum":{"$sum":"$items.value"},
"minDate":{"$min":"$items.dateTime"}}}
)
I'm preparing a descriptive "schema" (quelle horreur) for a MongoDB I've been working with.
I used the excellent variety.js to create a list of all keys and show coverage of each key. However, in cases where the values corresponding to the keys have a small set of values, I'd like to be able to list the entire set as "available values." In R, I'd be thinking of these as the "factors" for the categorical variable, ie, gender : ["M", "F"].
I know I could just use R + RMongo, query each variable, and basically do the same procedure I would to create a histogram, but I'd like to know the proper Mongo.query()/javascript/Map,Reduce way to approach this. I understand the db.collection.aggregate() functions are designed for exactly this.
Before asking this, I referenced:
http://docs.mongodb.org/manual/reference/aggregation/
http://docs.mongodb.org/manual/reference/method/db.collection.distinct/
How to query for distinct results in mongodb with python?
Get a list of all unique tags in mongodb
http://cookbook.mongodb.org/patterns/count_tags/
But can't quite get the pipeline order right. So, for example, if I have documents like these:
{_id : 1, "key1" : "value1", "key2": "value3"}
{_id : 2, "key1" : "value2", "key2": "value3"}
I'd like to return something like:
{"key1" : ["value1", "value2"]}
{"key2" : ["value3"]}
Or better, with counts:
{"key1" : ["value1" : 1, "value2" : 1]}
{"key2" : ["value3" : 2]}
I recognize one problem with doing this will be any values that have a wide range of different values---so, text fields, or continuous variables. Ideally, if there were more than x different possible values, it would be nice to truncate, say to no more than 20 unique values. If I find it's actually more, I'd query that variable directly.
Is this something like:
db.collection.aggregate(
{$limit: 20,
$group: {
_id: "$??varname",
count: {$sum: 1}
}})
First, how can I reference ??varname? for the name of each key?
I saw this link which had 95% of it:
Binning and tabulate (unique/count) in Mongo
with...
input data:
{ "_id" : 1, "age" : 22.34, "gender" : "f" }
{ "_id" : 2, "age" : 23.9, "gender" : "f" }
{ "_id" : 3, "age" : 27.4, "gender" : "f" }
{ "_id" : 4, "age" : 26.9, "gender" : "m" }
{ "_id" : 5, "age" : 26, "gender" : "m" }
This script:
db.collection.aggregate(
{$project: {gender:1}},
{$group: {
_id: "$gender",
count: {$sum: 1}
}})
Produces:
{"result" :
[
{"_id" : "m", "count" : 2},
{"_id" : "f", "count" : 3}
],
"ok" : 1
}
But what I don't understand is how could I do this generically for an unknown number/name of keys with a potentially large number of return values? This sample knows the key name is gender, and that the response set will be small (2 values).
If you already ran a script that outputs the names of all keys in the collection, you can generate your aggregation framework pipeline dynamically. What that means is either extending the variety.js type script or just writing your own.
Here is what it might look like in JS if passed an array called "keys" which has several non-"_id" named fields (I'm assuming top level fields and that you don't care about arrays, embedded documents, etc).
keys = ["key1", "key2"];
group = { "$group" : { "_id" : null } } ;
keys.forEach( function(f) {
group["$group"][f+"List"] = { "$addToSet" : "$" + f }; } );
db.collection.aggregate(group);
{
"result" : [
{
"_id" : null,
"key1List" : [
"value2",
"value1"
],
"key2List" : [
"value3"
]
}
],
"ok" : 1
}
I have mongo documents in this format.
{"_id" : 1,"Summary" : {...},"Examples" : [{"_id" : 353,"CategoryId" : 4},{"_id" : 239,"CategoryId" : 28}, ... ]}
{"_id" : 2,"Summary" : {...},"Examples" : [{"_id" : 312,"CategoryId" : 2},{"_id" : 121,"CategoryId" : 12}, ... ]}
How can I map/reduce them to get a hash like:
{ [ result[categoryId] : count_of_examples , .....] }
I.e. count of examples of each category.
I have 30 categories at all, all specified in Categories collection.
If you can use 2.1 (dev version of upcoming release 2.2) then you can use Aggregation Framework and it would look something like this:
db.collection.aggregate( [
{$project:{"CatId":"$Examples.CategoryId","_id":0}},
{$unwind:"$CatId"},
{$group:{_id:"$CatId","num":{$sum:1} } },
{$project:{CategoryId:"$_id",NumberOfExamples:"$num",_id:0 }}
] );
The first step projects the subfield of Examples (CategoryId) into a top level field of a document (not necessary but helps with readability), then we unwind the array of examples which creates a separate document for each array value of CatId, we do a "group by" and count them (I assume each instance of CategoryId is one example, right?) and last we use projection again to relabel the fields and make the result look like this:
"result" : [
{
"CategoryId" : 12,
"NumberOfExamples" : 1
},
{
"CategoryId" : 2,
"NumberOfExamples" : 1
},
{
"CategoryId" : 28,
"NumberOfExamples" : 1
},
{
"CategoryId" : 4,
"NumberOfExamples" : 1
}
],
"ok" : 1