The idea is to go from a collection of documents like this:
{
"_id" : ObjectId("58ff4fa372ac97344d5672c2"),
"direction" : 1,
"post" : ObjectId("58ff4ea572ac97344d5672c1"),
"user" : ObjectId("586b84239ae9590ab66bd3ad")
}
{
"_id" : ObjectId("58ff4c9f2952d7341d4afc0c"),
"direction" : -1,
"post" : ObjectId("58fc15a3fb3bed0fd54bfd95"),
"user" : ObjectId("586b84239ae9590ab66bd3ad")
}
To this:
[
//post: direction
"58ff4ea572ac97344d5672c1": 1,
"58fc15a3fb3bed0fd54bfd95": -1
]
I can't seem to find anything in the MongoDB Aggregation docs that allows you to set the key name using the value of another field.
I'm expecting this code to work, but I can see why it doesn't. It thinks that "$post" refers to a MongoDB expression.
db.votes.aggregate([
{$group: {
_id: null,
entries: {
$addToSet: {
"$post": "$direction"
}
}
}}
])
Related
and think you in advance for the help. I have recently started using mongoDB for some personal project and I'm interested in finding a better way to query my data.
My question is: I have the following collection:
{
"_id" : ObjectId("5dbd77f7a204d21119cfc758"),
"Toyota" : {
"Founder" : "Kiichiro Toyoda",
"Founded" : "28 August 1937",
"Subsidiaries" : [
"Lexus",
"Daihatsu",
"Subaru",
"Hino"
]
}
}
{
"_id" : ObjectId("5dbd78d3a204d21119cfc759"),
"Volkswagen" : {
"Founder" : "German Labour Front",
"Founded" : "28 May 1937",
"Subsidiaries" : [
"Audi",
"Volkswagen",
"Skoda",
"SEAT"
]
}
}
I want to get the object name for example here I want to return
[Toyota, Volkswagen]
I have use this method
var names = {}
db.cars.find().forEach(function(doc){Object.keys(doc).forEach(function(key){names[key]=1})});
names;
which gave me the following result:
{ "_id" : 1, "Toyota" : 1, "Volkswagen" : 1 }
however, is there a better way to get the same result and also to just return the names of the objects. Thank you.
I would suggest you to change the schema design to be something like:
{
_id: ...,
company: {
name: 'Volkswagen',
founder: ...,
subsidiaries: ...,
...<other fields>...
}
You can then use the aggregation framework to achieve a similar result:
> db.test.find()
{ "_id" : 0, "company" : { "name" : "Volkswagen", "founder" : "German Labour Front" } }
{ "_id" : 1, "company" : { "name" : "Toyota", "founder" : "Kiichiro Toyoda" } }
> db.test.aggregate([ {$group: {_id: null, companies: {$push: '$company.name'}}} ])
{ "_id" : null, "companies" : [ "Volkswagen", "Toyota" ] }
For more details, see:
Aggregation framework
$group
Accumulator operators
As a bonus, you can create an index on the company.name field, whereas you cannot create an index on varying field names like in your example.
It's one of my data as JSON format:
{
"_id" : ObjectId("5bfdb412a80939b6ed682090"),
"accounts" : [
{
"_id" : ObjectId("5bf106eee639bd0df4bd8e05"),
"accountType" : "DDA",
"productName" : "DDA1"
},
{
"_id" : ObjectId("5bf106eee639bd0df4bd8df8"),
"accountType" : "VSA",
"productName" : "VSA1"
},
{
"_id" : ObjectId("5bf106eee639bd0df4bd8df9"),
"accountType" : "VSA",
"productName" : "VSA2"
}
]
}
I want to make a query to get all productName(no duplicate) of accountType = VSA.
I write a mongo query:
db.Collection.distinct("accounts.productName", {"accounts.accountType": "VSA" })
I expect: ['VSA1', 'VSA2']
I get: ['DDA','VSA1', 'VSA2']
Anybody knows why the query doesn't work in distinct?
Second parameter of distinct method represents:
A query that specifies the documents from which to retrieve the distinct values.
But the thing is that you showed only one document with nested array of elements so whole document will be returned for your condition "accounts.accountType": "VSA".
To fix that you have to use Aggregation Framework and $unwind nested array before you apply the filtering and then you can use $group with $addToSet to get unique values. Try:
db.col.aggregate([
{
$unwind: "$accounts"
},
{
$match: {
"accounts.accountType": "VSA"
}
},
{
$group: {
_id: null,
uniqueProductNames: { $addToSet: "$accounts.productName" }
}
}
])
which prints:
{ "_id" : null, "uniqueProductNames" : [ "VSA2", "VSA1" ] }
I have a MongoDB document like this example doc:
{
"_id" : "A",
"articleNumber" : "0123456",
"shopDependentProperties" :
{
"shop" : "DE",
"foo" : "foo",
"bar" : "bar"
}
}
and want to pull out the properties of shopDependentProperties, to have the following result
{
"_id" : "A",
"articleNumber" : "0123456",
"foo" : "foo",
"bar" : "bar"
}
In MongoDB Shell i can solve it this way:
db.test.aggregate(
[
{
$project:
{
_id : "$_id",
articleNumber : "$articleNumber",
foo:"$shopDependentProperties.foo",
bar:"$shopDependentProperties.bar"
}
}
]
)
But: In Spring Data MongoDB i can't extract the embedded document contents.
I tried many combinations, nothing worked. For example:
ProjectionOperation projection = Aggregation.project("_id");
projection.andExpression("shopDependentProperties.foo").as("foo");
projection.andExpression("shopDependentProperties.bar").as("bar");
System.out.println(projection.toDBObject(Aggregation.DEFAULT_CONTEXT));
will ignore the shopDependentProperties.shop stuff and just print out
{ "$project" : { "_id" : 1}}
Any suggestions?
Thx
Haven't tested this, but as of
http://docs.mongodb.org/manual/reference/operator/aggregation/project/
you specify included / excluded fields like this:
db.test.aggregate(
[
{
$project:
{
_id : "$_id",
articleNumber : 1,
"shopDependentProperties.foo": 1,
"shopDependentProperties.bar": 1
}
}
]
)
Further down they explain, how to include embedded documents in the projection result.
I know how to do it in MongoDB, the problem was about doing the same thing in Spring Data.
But it works the same way, why didn't I try that before?
Solution:
ProjectionOperation projection = Aggregation.project(
"brandName",
"$shopDependentProperties.foo",
"$shopDependentProperties.bar" );
I'm attempting to store pre-aggregated performance metrics in a sharded mongodb according to this document.
I'm trying to update the minute sub-documents in a record that may or may not exist with an upsert like so (self.collection is a pymongo collection instance):
self.collection.update(query, data, upsert=True)
query:
{ '_id': u'12345CHA-2RU020130304',
'metadata': { 'adaptor_id': 'CHA-2RU',
'array_serial': 12345,
'date': datetime.datetime(2013, 3, 4, 0, 0, tzinfo=<UTC>),
'processor_id': 0}
}
data:
{ 'minute': { '16': { '45': 1.6693091}}}
The problem is that in this case the 'minute' subdocument always only has the last hour: { minute: metric} entry, the minute subdocument does not create new entries for other hours, it's always overwriting the one entry.
I've also tried this with a $set style data entry:
{ '$set': { 'minute': { '16': { '45': 1.6693091}}}}
but it ends up being the same.
What am I doing wrong?
In both of the examples listed you are simply setting a field ('minute')to a particular value, the only reason it is an addition the first time you update is because the field itself does not exist and so must be created.
It's hard to determine exactly what you are shooting for here, but I think what you could do is alter your schema a little so that 'minute' is an array. Then you could use $push to add values regardless of whether they are already present or $addToSet if you don't want duplicates.
I had to alter your document a little to make it valid in the shell, so my _id (and some other fields) are slightly different to yours, but it should still be close enough to be illustrative:
db.foo.find({'_id': 'u12345CHA-2RU020130304'}).pretty()
{
"_id" : "u12345CHA-2RU020130304",
"metadata" : {
"adaptor_id" : "CHA-2RU",
"array_serial" : 12345,
"date" : ISODate("2013-03-18T23:28:50.660Z"),
"processor_id" : 0
}
}
Now let's add a minute field with an array of documents instead of a single document:
db.foo.update({'_id': 'u12345CHA-2RU020130304'}, { $addToSet : {'minute': { '16': {'45': 1.6693091}}}})
db.foo.find({'_id': 'u12345CHA-2RU020130304'}).pretty()
{
"_id" : "u12345CHA-2RU020130304",
"metadata" : {
"adaptor_id" : "CHA-2RU",
"array_serial" : 12345,
"date" : ISODate("2013-03-18T23:28:50.660Z"),
"processor_id" : 0
},
"minute" : [
{
"16" : {
"45" : 1.6693091
}
}
]
}
Then, to illustrate the addition, add a slightly different entry (since I am using $addToSet this is required for a new field to be added:
db.foo.update({'_id': 'u12345CHA-2RU020130304'}, { $addToSet : {'minute': { '17': {'48': 1.6693391}}}})
db.foo.find({'_id': 'u12345CHA-2RU020130304'}).pretty()
{
"_id" : "u12345CHA-2RU020130304",
"metadata" : {
"adaptor_id" : "CHA-2RU",
"array_serial" : 12345,
"date" : ISODate("2013-03-18T23:28:50.660Z"),
"processor_id" : 0
},
"minute" : [
{
"16" : {
"45" : 1.6693091
}
},
{
"17" : {
"48" : 1.6693391
}
}
]
}
I ended up setting the fields like this:
query:
{ '_id': u'12345CHA-2RU020130304',
'metadata': { 'adaptor_id': 'CHA-2RU',
'array_serial': 12345,
'date': datetime.datetime(2013, 3, 4, 0, 0, tzinfo=<UTC>),
'processor_id': 0}
}
I'm setting the metrics like this:
data = {"$set": {}}
for metric in csv:
date_utc = metric['date'].astimezone(pytz.utc)
data["$set"]["minute.%d.%d" % (date_utc.hour,
date_utc.minute)] = float(metric['metric'])
which creates data like this:
{"$set": {'minute.16.45': 1.6693091,
'minute.16.46': 1.566343,
'minute.16.47': 1.22322}}
So that when self.collection.update(query, data, upsert=True) is run it updates those fields.
I have a collection that stored information about devices like the following:
/* 1 */
{
"_id" : {
"startDate" : "2012-12-20",
"endDate" : "2012-12-30",
"dimensions" : ["manufacturer", "model"],
"metrics" : ["deviceCount"]
},
"data" : {
"results" : "1"
}
}
/* 2 */
{
"_id" : {
"startDate" : "2012-12-20",
"endDate" : "2012-12-30",
"dimensions" : ["manufacturer", "model"],
"metrics" : ["deviceCount", "noOfUsers"]
},
"data" : {
"results" : "2"
}
}
/* 3 */
{
"_id" : {
"dimensions" : ["manufacturer", "model"],
"metrics" : ["deviceCount", "noOfUsers"]
},
"data" : {
"results" : "3"
}
}
And I am trying to query the documents using the _id field which will be unique. The problem I am having is that when I query for all the different attributes as in:
db.collection.find({$and: [{"_id.dimensions":{ $all: ["manufacturer","model"], $size: 2}}, {"_id.metrics": { $all:["noOfUsers","deviceCount"], $size: 2}}]});
This matches 2 and 3 documents (I don't care about the order of the attributes values), but I would like to only get 3 back. How can I say that there should not be any other attributes to _id than those that I specify in the search query?
Please advise. Thanks.
Unfortunately, I think the closest you can get to narrowing your query results to just unordered _id.dimensions and unordered _id.metrics requires you to know the other possible fields in the _id subdocument field, eg. startDate and endDate.
db.collection.find({$and: [
{"_id.dimensions":{ $all: ["manufacturer","model"], $size: 2}},
{"_id.metrics": { $all:["noOfUsers","deviceCount"], $size: 2}},
{"_id.startDate":{$exists:false}},
{"_id.endDate":{$exists:false}}
]});
If you don't know the set of possible fields in _id, then the other possible solution would be to specify the exact _id that you want, eg.
db.collection.find({"_id" : {
"dimensions" : ["manufacturer", "model"],
"metrics" : ["deviceCount", "noOfUsers"]
}})
but this means that the order of _id.dimensions and _id.metrics is significant. This last query does a document match on exact BSON representation of _id.