I create players the following way.
Players.insert({
name: name,
score: 0,
items: [{'name': 0}, {'name2': 0}...]
});
How do I increment the score in a specific player and specific item name (upserting if necessary)?
Sorry for the terrible wording :p
Well, the answer is - as in life - to simplify the problem by breaking it up.
And to avoid arrays in mongoDB - after all, objects can have as many keys as you like. So, my structure became:
{
"_id": <id>,
"name": <name>,
"score": <score>,
"items": {}
}
And to increment the a dynamic key in items:
// create your update skeleton first
var ud = { $inc: {} };
// fill it in
ud.$inc['item.' + key] = value;
// call it
db.Players.update(player, ud, true);
Works a charm :)
Lets say you have:
{
"_id" : ObjectId("5465332e6c3e2eeb66ef3683"),
"name" : "Alex",
"score" : 0,
"items" : [
{
"food" : 0
}
]
}
To update you can do:
db.Players.update({name: "Alex", "items.food": {$exists : true}},
{$inc: {score: 1, "items.$.food": 5}})
Result:
{
"_id" : ObjectId("5465332e6c3e2eeb66ef3683"),
"name" : "Alex",
"score" : 1,
"items" : [
{
"food" : 5
}
]
}
I am not sure you can upsert if the document doesn't exist because of the positional operator needed to update the array.
Related
and think you in advance for the help. I have recently started using mongoDB for some personal project and I'm interested in finding a better way to query my data.
My question is: I have the following collection:
{
"_id" : ObjectId("5dbd77f7a204d21119cfc758"),
"Toyota" : {
"Founder" : "Kiichiro Toyoda",
"Founded" : "28 August 1937",
"Subsidiaries" : [
"Lexus",
"Daihatsu",
"Subaru",
"Hino"
]
}
}
{
"_id" : ObjectId("5dbd78d3a204d21119cfc759"),
"Volkswagen" : {
"Founder" : "German Labour Front",
"Founded" : "28 May 1937",
"Subsidiaries" : [
"Audi",
"Volkswagen",
"Skoda",
"SEAT"
]
}
}
I want to get the object name for example here I want to return
[Toyota, Volkswagen]
I have use this method
var names = {}
db.cars.find().forEach(function(doc){Object.keys(doc).forEach(function(key){names[key]=1})});
names;
which gave me the following result:
{ "_id" : 1, "Toyota" : 1, "Volkswagen" : 1 }
however, is there a better way to get the same result and also to just return the names of the objects. Thank you.
I would suggest you to change the schema design to be something like:
{
_id: ...,
company: {
name: 'Volkswagen',
founder: ...,
subsidiaries: ...,
...<other fields>...
}
You can then use the aggregation framework to achieve a similar result:
> db.test.find()
{ "_id" : 0, "company" : { "name" : "Volkswagen", "founder" : "German Labour Front" } }
{ "_id" : 1, "company" : { "name" : "Toyota", "founder" : "Kiichiro Toyoda" } }
> db.test.aggregate([ {$group: {_id: null, companies: {$push: '$company.name'}}} ])
{ "_id" : null, "companies" : [ "Volkswagen", "Toyota" ] }
For more details, see:
Aggregation framework
$group
Accumulator operators
As a bonus, you can create an index on the company.name field, whereas you cannot create an index on varying field names like in your example.
I have an entry stored on my collection like this:
{
"_id" : ObjectId("5d416c595f19962ff0680dbc"),
"data" : {
"a" : 6,
"b" : [
"5c35f04c4e92b8337885d9a6"
]
},
"image" : "123.jpg",
"hyperlinks" : "google.com",
"expirydate" : ISODate("2019-08-27T06:10:35.074Z"),
"createdate" : ISODate("2019-07-31T10:24:25.311Z"),
"lastmodified" : ISODate("2019-07-31T10:24:25.311Z"),
"__v" : 0
},
{
"_id" : ObjectId("5d416c595f19962ff0680dbd"),
"data" : {
"a" : 90,
"b" : [
"5c35f04c4e92b8337885d9a7"
]
},
"image" : "456.jpg",
"hyperlinks" : "google.com",
"expirydate" : ISODate("2019-08-27T06:10:35.074Z"),
"createdate" : ISODate("2019-07-31T10:24:25.311Z"),
"lastmodified" : ISODate("2019-07-31T10:24:25.311Z"),
"__v" : 0
}
I have to write the query for push userid on b array which is under data object and increment the a counter which is also under data object.
For that, I wrote the Code i.e
db.collection.updateOne({_id: ObjectId("5d416c595f19962ff0680dbd")},
{$inc: {'data.a': 1}, $push: {'data.b': '124sdff54f5s4fg5'}}
)
I also want to check that if that id exist on array then return the response that following id exist, so for that I wrote extra query which will check and if id exist then return the error response that following id exist,
My question is that any single query will do this? Like I don't want to write Two Queries for single task.
Any help is really appreciated for that
You can add one more check in the update query on "data.b". Following would be the query:
db.collection.updateOne(
{
_id: ObjectId("5d416c595f19962ff0680dbd"),
"data.b":{
$ne: "124sdff54f5s4fg5"
}
},
{
$inc: {'data.a': 1},
$push: {'data.b': '124sdff54f5s4fg5'}
}
)
For duplicate entry, you would get the following response:
{ "acknowledged" : true, "matchedCount" : 0, "modifiedCount" : 0 }
If matched count is 0, you can show the error that the id already exists.
You can use the operator $addToSet to check if the element already exits in the array.
db.collection.updateOne({_id: ObjectId("5d416c595f19962ff0680dbd")},
{$inc: {'data.a': 1}, $addToSet: {'data.b': '124sdff54f5s4fg5'}}
)
I am new to MongoDB so this is probably a basic question (hopefully). I currently have 10 million records with 410 fields loaded in a mongodb collection like so:
{
"_id" : ObjectId("........"),
"AddressID" : 123455,
"IndividualId" : 1,
"personfirstname" : "FirstName",
"personmiddleinitial" : "M",
"personlastname" : "LastName",
"etc": "....."
}
I need to wrap all of this data into an embedded document like so:
{
"_id" : ObjectId("........"),
"data" : {
"AddressID" : 123455,
"IndividualId" : 1,
"personfirstname" : "FirstName",
"personmiddleinitial" : "M",
"personlastname" : "LastName",
"etc": "....."
}
I don't necessarily need to update this data in-place but that would be nice. If I need to export this data somehow specifying the new format and then re-import the new, updated data that is fine. Performing this via the MongoDB shell would be ideal.
As suggested by chridam within comments you can execute the following aggregation pipeline:
db.collectionName.aggregate([
{ $project: { _id: "$_id", data: "$$ROOT" } },
{ $out: "newCollectionName" }
]);
This way you have the _id field both at root level and in the data object. Thus, you can execute a massive update to unset the second one:
db.newCollectionName.updateMany(
{},
{ $unset: { "data._id": "" } }
);
Finally, you can drop the first collection and rename the second to restore the original name on the updated collection:
db.collectionName.drop();
db.newCollectionName.rename("collectionName");
This approach fully works within the database, avoiding fetching any of your 10 million documents.
You can simply do this in the shell with the following
db.test.find().forEach(function(doc){
doc = { _id: doc._id, data: doc };
delete doc.data._id;
db.test.save(doc);
});
For example, if we insert the following documents:
> db.test.insertMany([
... {
... _id: ObjectId("5a91af8908e17c5997e03b7e"),
... field1: false,
... field2: 0,
... field3: "No"
... },
... {
... _id: ObjectId("5a91afbc08e17c5997e03b7f"),
... field1: true,
... field2: 1,
... field3: "Yes"
... }])
{
"acknowledged" : true,
"insertedIds" : [
ObjectId("5a91af8908e17c5997e03b7e"),
ObjectId("5a91afbc08e17c5997e03b7f")
]
}
Then run:
db.test.find().forEach(function(doc){
doc = { _id: doc._id, data: doc };
delete doc.data._id;
db.test.save(doc);
});
Our documents now look like this:
> db.test.find().pretty()
{
"_id" : ObjectId("5a91af8908e17c5997e03b7e"),
"data" : {
"field1" : false,
"field2" : 0,
"field3" : "No"
}
}
{
"_id" : ObjectId("5a91afbc08e17c5997e03b7f"),
"data" : {
"field1" : true,
"field2" : 1,
"field3" : "Yes"
}
}
Unlike the other question someone asked where they wanted only one item returned. I HAVE one item returned and I need ALL of the matching objects in the array return. However the second object that matches my query is being completely ignored.
This is what one of the items in the item collection looks like:
{
name: "soda",
cost: .50,
inventory: [
{ flavor: "Grape",
amount: 8 },
{ flavor: "Orange",
amount: 4 },
{ flavor: "Root Beer",
amount: 15 }
]
}
Here is the query I typed in to mongo shell:
Items.find({"inventory.amount" : { $lte : 10} } , { name : 1, "inventory.$.flavor" : 1})
And here is the result:
"_id" : ObjectId("59dbe33094b70e0b5851724c"),
"name": "soda"
"inventory" : [
{ "flavor" : "Grape",
"amount" : 8,
}
]
And here is what I want it to return to me:
"_id" : ObjectId("59dbe33094b70e0b5851724c"),
"name": "soda"
"inventory" : [
{ "flavor" : "Grape",
"amount" : 8
},
{ "flavor" : "Orange",
"amount" : 4
}
]
I'm new to mongo and am dabbling to get familiar with it. I've read through the docs but couldn't find a solution to this though it's quite possible I overlooked it. I'd really love some help. Thanks in advance.
first u can get your result by this query
db.Items.find({"inventory.amount" : { $lte : 10} } , { name : 1, "inventory.flavor" : 1 , "inventory.amount" : 1})
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.