i have a mongodb collection "result" with data like
{ "_id" : {
"user" : "Howard",
"friend" : "Sita"
},
"value" : {
"mutualFriend" :[ "Hanks", "Bikash", "Shyam", "Bakshi" ]
}
}
{ "_id" : {
"user" : "Shiva",
"friend" : "Tom"
},
"value" : {
"friendList" :[ "Hanks", " Tom", " Karma", " Hari", " Dinesh" ]
}
}
{ "_id" : {
"user" : "Hari",
"friend" : "Shiva"
},
"value" : {
"mutualFriend" :[ "Tom", "Karma", "Dinesh" ]
}
}
Now, here i want to query whole Document having value.mutualFriend. how can i get the result?
Expected Output
{ "_id" : {
"user" : "Howard",
"friend" : "Sita"
},
"value" : {
"mutualFriend" :[ "Hanks", "Bikash", "Shyam", "Bakshi" ]
}
}
{ "_id" : {
"user" : "Hari",
"friend" : "Shiva"
},
"value" : {
"mutualFriend" :[ "Tom", "Karma", "Dinesh" ]
}
}
i have large number of document in MongoDB collection, containing value.friendList and value.mutualFriend and then i want to find only documents with value.mutualFriend
db.collection.find({"value.mutualFriend.0" : { $exists : true }})
Its just make sure that the 0th element exists. you can customize your query over various array length.
Related
Assuming the following structure:
Assets
{
"_id" : LUUID("d34a3fed"),
"name" : "A",
"records" : [
LUUID("3627f3ac"),
LUUID("80e9d125"),
LUUID("4d5e8af5"),
LUUID("17593a39"),
}
Records
{
"_id" : LUUID("3627f3ac"),
"Fields" : [
{
"Name" : "foo",
"Value" : "bar",
}
],
}
My goal is to use a find() or aggregate() to cross-reference the two collections above. The two collections share the LUUID values.
{"records": "LUUID("3627f3ac")"}
{"_id": "LUUID("3627f3ac")"}
Ultimately retrieving the:
{"Fields.Name": "foo"}
name of the Records collection
Maybe something like this:
mongos> db.records.find()
{ "_id" : ObjectId("5ff8ccf9e0f1b975b90d7a86"), "fields" : [ { "name" : "foo", "value" : "bar" } ] }
{ "_id" : ObjectId("5ff8ccf9e0f1b975b90d7a87"), "fields" : [ { "name" : "foo2", "value" : "bar2" } ] }
{ "_id" : ObjectId("5ff8ccf9e0f1b975b90d7a88"), "fields" : [ { "name" : "foo3", "value" : "bar3" } ] }
mongos> db.assest.find()
{ "_id" : ObjectId("5ff8cd72e0f1b975b90d7a87"), "name" : "A", "records" : [ ObjectId("5ff8ccf9e0f1b975b90d7a86"), ObjectId("5ff8ccf9e0f1b975b90d7a87") ] }
mongos> db.assest.aggregate([ { $lookup:{ from:"records" , localField:"records" , foreignField:"_id" , as:"match" } } , {$unwind:"$match"} , {$unwind:"$match.fields"} ,{$project:{ "Fields_name":"$match.fields.name" ,_id:0}} ])
{ "Fields_name" : "foo" }
{ "Fields_name" : "foo2" }
mongos>
Playground
In Mysql I can do a Select from another Select.
So I would ask if I can do the same in Mongodb.
For more explanation, I need to retreive the transaction of the a specific userOwner with just the last dateTransaction in the history object of this collection.So if this userOwner isn't in the last history we shoudn't retreive this transaction.
I used at first this query:
#Query(value = "{'history':{'$elemMatch':{'userOwner': ?0}}}")
but it returns all the elements even those where this userOwner isn't with the last "dateTransaction".
So I aim to de a query that it returns for each transaction just the last dateTransaction with userOwner of the "history" array :
.find({},{dateTransaction: {$slice: 1} }).limit(1)
and after do another query from this one.
Anyone has an idea or examples.
Tnx
This is my Collection called "piece":
{
"_id" : ObjectId("1"),
"history" : [{
"userOwner" : "3",
"dateTransaction" : ISODate("2016-05-30T00:00:00.000+0000"),
}, {
"userOwner" : "1",
"dateTransaction" : ISODate("2016-05-26T00:00:00.000+0000"),
}, {
"userOwner" : "2",
"dateTransaction" : ISODate("2016-05-23T00:00:00.000+0000"),
}
]
}{
"_id" : ObjectId("2"),
"transactions" : [{
"userOwner" : "2",
"dateTransaction" : ISODate("2016-05-26T00:00:00.000+0000"),
}, {
"userOwner" : "3",
"dateTransaction" : ISODate("2016-05-15T00:00:00.000+0000"),
}
]
}{
"_id" : ObjectId("3"),
"transactions" : [{
"userOwner" : "2",
"dateTransaction" : ISODate("2016-05-26T00:00:00.000+0000"),
}, {
"userOwner" : "1",
"dateTransaction" : ISODate("2016-05-15T00:00:00.000+0000"),
}
]
}
As example the result for the userOwner 2 should be :
{
"_id" : ObjectId("2"),
"transactions" : [{
"userOwner" : "2",
"dateTransaction" : ISODate("2016-05-26T00:00:00.000+0000"),
}, {
"userOwner" : "3",
"dateTransaction" : ISODate("2016-05-15T00:00:00.000+0000"),
}
]
}{
"_id" : ObjectId("3"),
"transactions" : [{
"userOwner" : "2",
"dateTransaction" : ISODate("2016-05-26T00:00:00.000+0000"),
}, {
"userOwner" : "1",
"dateTransaction" : ISODate("2016-05-15T00:00:00.000+0000"),
}
]
}
it looks like your data is stored in one collection - so this is a kind of bad design as it needs more overhead to work with....
below aggregation query which has a lookup to the same collection to match data for user:2
var unwind = {
$unwind : "$history"
}
var matchUser = {
$match : {
"history.userOwner" : "2"
}
}
var lookUp = {
$lookup : {
from : "shm",
localField : "userOwner",
foreignField : "userOwner",
as : "t"
}
}
var unwindTransactions = {
$unwind : "$t"
}
var unwindTransactions2 = {
$unwind : "$t.transactions"
}
var match2 = {
$match : {
"t.transactions.userOwner" : "2"
}
}
var project = {
$project : {
_id : 0,
recordId : "$_id",
transactionId : "$t._id",
dateOfTransaction : "$history.dateTransaction",
userOwner : "$history.userOwner",
}
}
db.shm.aggregate([unwind,
matchUser,
lookUp,
unwindTransactions,
unwindTransactions2,
match2,
project
])
and as a result we have two records of user transactions
{
"recordId" : ObjectId("575e7e8b852cb76369c9e446"),
"transactionId" : ObjectId("575e7e8b852cb76369c9e447"),
"dateOfTransaction" : ISODate("2016-05-23T00:00:00.000Z"),
"userOwner" : "2"
},{
"recordId" : ObjectId("575e7e8b852cb76369c9e446"),
"transactionId" : ObjectId("575e7e8b852cb76369c9e448"),
"dateOfTransaction" : ISODate("2016-05-23T00:00:00.000Z"),
"userOwner" : "2"
}
Please consider split of that collection as in current form will give you a lot of headache when processing more complex queries
I've seen this question all over google/SO/mongo docs, and I've tried to implement the solution, but it's not working for me. I have the following test database:
> db.test.find().pretty()
{
"_id" : ObjectId("56b4ab167db9acd913ce6e07"),
"state" : "HelloWorld",
"items" : [
{
"guid" : "123"
},
{
"guid" : "124"
},
{
"guid" : "123"
}
]
}
And I want to sort by the "guid" element of items. Running the sort commands yields:
> db.test.find().sort( {"items.guid" : 1}).pretty()
{
"_id" : ObjectId("56b4ab167db9acd913ce6e07"),
"state" : "HelloWorld",
"items" : [
{
"guid" : "123"
},
{
"guid" : "124"
},
{
"guid" : "123"
}
]
}
How can I sort by the "guid" element, so that the returned output of "items" is the 123, 123, and 124 guids (essentially move the child elements of "items" so that they're sorted by "guid")?
EDIT: I've also tried to use the $orderby command, doesn't accomplish what I want:
> db.test.find({ $query : {}, $orderby: {'items.guid' : 1} }).pretty()
{
"_id" : ObjectId("56b4ab167db9acd913ce6e07"),
"state" : "HelloWorld",
"items" : [
{
"guid" : "123"
},
{
"guid" : "124"
},
{
"guid" : "123"
}
]
}
Here is how it can be done using aggregate
db.test.aggregate([
{
$unwind : '$items'
},
{
$sort : {'items.guid' : 1}
},
{
$group : {
_id : '$_id',
state : {$first : '$state'},
items : {
$push : {'guid' : '$items.guid'}
}
}
}
]).pretty()
This is the output from this command.
{
"_id" : ObjectId("56b4ab167db9acd913ce6e07"),
"state" : "HelloWorld",
"items" : [
{
"guid" : "123"
},
{
"guid" : "123"
},
{
"guid" : "124"
}
]
}
I have a list of documents like this.
[
{
"name" : "test",
"data" : [
{ "code" : "name", "value" : "Diego" },
{ "code" : "nick", "value" : "Darko" },
{ "code" : "special", "value" : true }
]
},
{
"name" : "another",
"data" : [
{ "code" : "name", "value" : "Antonio" },
{ "code" : "nick", "value" : "Tony" }
]
}
]
now I need to find all the documents that:
a) don't contain a "data" item with code "special"
OR
b) contains a "data" item with code "special" and value false
It's like I needed the opposite of $elemMatch or I'm missing something?
I'm assuming that you're inserting each document in your list of documents as a separate member of a collection test.
For a,
db.test.find({ "data.code" : { "$ne" : "special" } })
For b.,
db.test.find({ "data" : { "$elemMatch" : { "code" : "special", "value" : false } } })
Combining the two with $or,
db.test.find({ "$or" : [
{ "data.code" : { "$ne" : "special" } },
{ "data" : { "$elemMatch" : { "code" : "special", "value" : false } } }
] })
Hope this $nin will solve your issues.
I insertd your docs into "so" collection
db.so.find({}).pretty();
{
"_id" : ObjectId("5489cd4f4cb16307b808d4b2"),
"name" : "test",
"data" : [
{ "code" : "name",
"value" : "Diego"
},
{ "code" : "nick",
"value" : "Darko"
},
{ "code" : "special",
"value" : true
}
]
}
{
"_id" : ObjectId("5489cd674cb16307b808d4b3"),
"name" : "another",
"data" : [
{"code" : "name",
"value" : "Antonio"
},
{ "code" : "nick",
"value" : "Tony"
}
]
}
don't contain a "data" item with code "special"
> db.so.find({"data.code":{$nin:["special"]}}).pretty();
{
"_id" : ObjectId("5489cd674cb16307b808d4b3"),
"name" : "another",
"data" : [
{ "code" : "name",
"value" : "Antonio"
},
{ "code" : "nick",
"value" : "Tony"
}
]
}
contains a "data" item with code "special" and value false
db.so.find({$and:[{"data.code":"special"},{"data.value":false}]}).pretty();
My document looks like this
{
field1: somevalue,
name:xtz
nested_documents: [ // array of nested document
{ x:"1", y:"2" }, // first nested document
{ x:"2", y:"3" }, // second nested document
{ x:"-1", y:"3" }, // second nested document
// ...many more nested documents
]
}
How one can sort the data present in nested_documents?
Expected answer is shown below:
nested_documents: [ { x:"-1", y:"3" },{ x:"1", y:"2" },{ x:"2", y:"3" }]
To do this you would have to use the aggregation framework
db.test.aggregate([{$unwind:'$nested_documents'},{$sort:{'nested_documents.x':
1}}])
this returns
"result" : [
{
"_id" : ObjectId("5139ba3dcd4e11c83f4cea12"),
"field1" : "somevalue",
"name" : "xtz",
"nested_documents" : {
"x" : "-1",
"y" : "3"
}
},
{
"_id" : ObjectId("5139ba3dcd4e11c83f4cea12"),
"field1" : "somevalue",
"name" : "xtz",
"nested_documents" : {
"x" : "1",
"y" : "2"
}
},
{
"_id" : ObjectId("5139ba3dcd4e11c83f4cea12"),
"field1" : "somevalue",
"name" : "xtz",
"nested_documents" : {
"x" : "2",
"y" : "3"
}
}
],
"ok" : 1
Hope this helps