I don't quite figure out why I'm getting different results when:
> db.reference.find({"metadata.values": {address: {location: "barcelona"} } }).count();
0
> db.reference.find({"metadata.values.address.location": "barcelona"}).count();
1
Which is the difference?
The document contained into reference collection is:
{
"_id" : "Doc1Ref2",
"document" : "doc1",
"metadata" : [
{
"_id" : "Doc1Ref2Mdt1",
"user" : "user2",
"creationTimestamp" : ISODate("2018-09-24T12:20:56.169Z"),
"values" : {
"date" : ISODate("2018-09-24T12:20:56.171Z"),
"number" : 16,
"address" : {
"street" : "Av. Diagonal",
"location" : "barcelona"
},
"credentials" : [
{
"password" : "pwd",
"login" : "main"
},
{
"password" : "pwd",
"login" : "other",
"creation" : ISODate("2018-09-24T12:20:56.171Z")
}
],
"contact" : "contact name",
"tags" : [
"tag1",
"tag2"
]
}
}
],
"timestampCreation" : ISODate("2018-09-24T12:20:56.169Z")
}
The first query matches documents where metadata.values is an exact object {address: {location: "barcelona"} }, the second is where metadata.values has an object with address.location equal to "barcelona".
The equivalent tests in javascript:
if ((document.metadata || {}).values == {address: {location: "barcelona"} })
and
if ((((document.metadata || {}).values || {}).address || {}).location == "barcelona")
Related
everyone. I need your help. For a script I have to search for users by their ldap id, but I have the problem that I get no output when searching.
a user has the following output.
db.users.find({"name" : "John Sample"} ).toArray()
[
{
"_id" : "testid",
"createdAt" : ISODate("2017-05-11T13:49:35.125Z"),
"services" : {
"password" : {
"bcrypt" : ""
},
"ldap" : {
"id" : "12345678",
"idAttribute" : "uid"
},
"resume" : {
"loginTokens" : [ ]
}
},
"username" : "john",
"emails" : [
{
"address" : "john.sample#test.com",
"verified" : true
}
],
"type" : "user",
"status" : "offline",
"active" : true,
"name" : "John Sample",
"_updatedAt" : ISODate("2018-07-05T18:44:22.061Z"),
"roles" : [
"user"
],
"ldap" : true,
"lastLogin" : ISODate("2018-07-05T10:33:00.712Z"),
"statusConnection" : "offline",
"utcOffset" : 2,
"statusDefault" : "offline"
}
]
I used this command but without success.
db.users.find({"services" : {"$elemMatch": {"ldap" : {"$elemMatch": {"id" : "12345678"}}}}}} ).toArray();
[ ]
$elemMatch is used to find elements that match criteria in an array. But services is an document (sub document), not an array. Just use dot notation to query :
db.users.find({"services.ldap.id":"12345678"})
I am trying to port an existing SQL schema into Mongo.
We have document tables, with sometimes several times the same document, with a different revision but the same reference. I want to get only the latest revisions of the documents.
A sample input data:
{
"Uid" : "xxx",
"status" : "ACCEPTED",
"reference" : "DOC305",
"code" : "305-D",
"title" : "Document 305",
"creationdate" : ISODate("2011-11-24T15:13:28.887Z"),
"creator" : "X"
},
{
"Uid" : "xxx",
"status" : "COMMENTED",
"reference" : "DOC306",
"code" : "306-A",
"title" : "Document 306",
"creationdate" : ISODate("2011-11-28T07:23:18.807Z"),
"creator" : "X"
},
{
"Uid" : "xxx",
"status" : "COMMENTED",
"reference" : "DOC306",
"code" : "306-B",
"title" : "Document 306",
"creationdate" : ISODate("2011-11-28T07:26:49.447Z"),
"creator" : "X"
},
{
"Uid" : "xxx",
"status" : "ACCEPTED",
"reference" : "DOC501",
"code" : "501-A",
"title" : "Document 501",
"creationdate" : ISODate("2011-11-19T06:30:35.757Z"),
"creator" : "X"
},
{
"Uid" : "xxx",
"status" : "ACCEPTED",
"reference" : "DOC501",
"code" : "501-B",
"title" : "Document 501",
"creationdate" : ISODate("2011-11-19T06:40:32.957Z"),
"creator" : "X"
}
Given this data, I want this result set (sometimes I want only the last revision, sometimes I want all revisions with an attribute telling me whether it's the latest):
{
"Uid" : "xxx",
"status" : "ACCEPTED",
"reference" : "DOC305",
"code" : "305-D",
"title" : "Document 305",
"creationdate" : ISODate("2011-11-24T15:13:28.887Z"),
"creator" : "X",
"lastrev" : true
},
{
"Uid" : "xxx",
"status" : "COMMENTED",
"reference" : "DOC306",
"code" : "306-B",
"title" : "Document 306",
"creationdate" : ISODate("2011-11-28T07:26:49.447Z"),
"creator" : "X",
"lastrev" : true
},
{
"Uid" : "xxx",
"status" : "ACCEPTED",
"reference" : "DOC501",
"code" : "501-B",
"title" : "Document 501",
"creationdate" : ISODate("2011-11-19T06:40:32.957Z"),
"creator" : "X",
"lastrev" : true
}
I already have a bunch of filters, sorting, and skip/limit (for pagination of data), so the final result set should be mindful of these constraints.
The current "find" query (built with the .Net driver), which filters fine but gives me all revisions of each document:
coll.find(
{ "$and" : [
{ "$or" : [
{ "deletedid" : { "$exists" : false } },
{ "deletedid" : null }
] },
{ "$or" : [
{ "taskid" : { "$exists" : false } },
{ "taskid" : null }
] },
{ "objecttypeuid" : { "$in" : ["xxxxx"] } }
] },
{ "_id" : 0, "Uid" : 1, "lastrev" : 1, "title" : 1, "code" : 1, "creator" : 1, "owner" : 1, "modificator" : 1, "status" : 1, "reference": 1, "creationdate": 1 }
).sort({ "creationdate" : 1 }).skip(0).limit(10);
Using another question, I have been able to build this aggregation, which gives me the latest revision of each document, but with not enough attributes in the result:
coll.aggregate([
{ $sort: { "creationdate": 1 } },
{
$group: {
"_id": "$reference",
result: { $last: "$creationdate" },
creationdate: { $last: "$creationdate" }
}
}
]);
I would like to integrating the aggregate with the find query.
I have found the way to mix aggregation and filtering:
coll.aggregate(
[
{ $match: {
"$and" : [
{ "$or" : [
{ "deletedid" : { "$exists" : false } },
{ "deletedid" : null }
] },
{ "$or" : [
{ "taskid" : { "$exists" : false } },
{ "taskid" : null }
] },
{ "objecttypeuid" : { "$in" : ["xxx"] } }
]
}
},
{ $sort: { "creationdate": 1 } },
{ $group: {
"_id": "$reference",
"doc": { "$last": "$$ROOT" }
}
},
{ $sort: { "doc.creationdate": 1 } },
{ $skip: skip },
{ $limit: limit }
],
{ allowDiskUse: true }
);
For each result node, this gives me a "doc" node with the document data. It has too much data still (it's missing projections), but it's a start.
Translated in .Net:
FilterDefinitionBuilder<BsonDocument> filterBuilder = Builders<BsonDocument>.Filter;
FilterDefinition<BsonDocument> filters = filterBuilder.Empty;
filters = filters & (filterBuilder.Not(filterBuilder.Exists("deletedid")) | filterBuilder.Eq("deletedid", BsonNull.Value));
filters = filters & (filterBuilder.Not(filterBuilder.Exists("taskid")) | filterBuilder.Eq("taskid", BsonNull.Value));
foreach (var f in fieldFilters) {
filters = filters & filterBuilder.In(f.Key, f.Value);
}
var sort = Builders<BsonDocument>.Sort.Ascending(orderby);
var group = new BsonDocument {
{ "_id", "$reference" },
{ "doc", new BsonDocument("$last", "$$ROOT") }
};
var aggregate = coll.Aggregate(new AggregateOptions { AllowDiskUse = true })
.Match(filters)
.Sort(sort)
.Group(group)
.Sort(sort)
.Skip(skip)
.Limit(rows);
return aggregate.ToList();
I'm pretty sure there are better ways to do this, though.
You answer is pretty close. Instead of $last, $max is better.
About $last operator:
Returns the value that results from applying an expression to the last document in a group of documents that share the same group by a field. Only meaningful when documents are in a defined order.
Get the last revision in each group, see code below in mongo shell:
db.collection.aggregate([
{
$group: {
_id: '$reference',
doc: {
$max: {
"creationdate" : "$creationdate",
"code" : "$code",
"Uid" : "$Uid",
"status" : "$status",
"title" : "$title",
"creator" : "$creator"
}
}
}
},
{
$project: {
_id: 0,
Uid: "$doc.Uid",
status: "$doc.status",
reference: "$_id",
code: "$doc.code",
title: "$doc.title",
creationdate: "$doc.creationdate",
creator: "$doc.creator"
}
}
]).pretty()
The output as your expect:
{
"Uid" : "xxx",
"status" : "ACCEPTED",
"reference" : "DOC501",
"code" : "501-B",
"title" : "Document 501",
"creationdate" : ISODate("2011-11-19T06:40:32.957Z"),
"creator" : "X"
}
{
"Uid" : "xxx",
"status" : "COMMENTED",
"reference" : "DOC306",
"code" : "306-B",
"title" : "Document 306",
"creationdate" : ISODate("2011-11-28T07:26:49.447Z"),
"creator" : "X"
}
{
"Uid" : "xxx",
"status" : "ACCEPTED",
"reference" : "DOC305",
"code" : "305-D",
"title" : "Document 305",
"creationdate" : ISODate("2011-11-24T15:13:28.887Z"),
"creator" : "X"
}
I have data with multiple documents :
{
"_id" : ObjectId("57b68dbbc19c0bd86d62e486"),
"empId" : "1"
"type" : "WebUser",
"city" : "Pune"
}
{
"_id" : ObjectId("57b68dbbc19c0bd86d62e487"),
"empId" : "2"
"type" : "Admin",
"city" : "Mumbai"
}
{
"_id" : ObjectId("57b68dbbc19c0bd86d62e488"),
"empId" : "3"
"type" : "Admin",
"city" : "Pune"
}
{
"_id" : ObjectId("57b68dbbc19c0bd86d62e489"),
"empId" : "4"
"type" : "User",
"city" : "Mumbai"
}
I want to get data according to my multiple conditions :
condition 1:- {"type" : "WebUser", "city" : "Pune"}
condition 2:- {"type" : "WebUser", "city" : "Pune"} & {"type" : "User", "city" : "Mumbai"}
I want below result when run condition 1 :
{
"_id" : ObjectId("57b68dbbc19c0bd86d62e486"),
"empId" : "1"
"type" : "WebUser",
"city" : "Pune"
}
When I run second condition :
{
"_id" : ObjectId("57b68dbbc19c0bd86d62e486"),
"empId" : "1"
"type" : "WebUser",
"city" : "Pune"
}
{
"_id" : ObjectId("57b68dbbc19c0bd86d62e489"),
"empId" : "4"
"type" : "User",
"city" : "Mumbai"
}
I want above result by one query,
Currently I am using below aggregate query,
db.emp.aggregate([
{ $match: { '$and': [
{"type" : "WebUser", "city" : "Pune"},
{"type" : "User", "city" : "Mumbai"}
] } },
{ $group: { _id: 1, ids: { $push: "$empId" } } }
])
Above query work for first condition & fails for other. Please help me.
For the second condition, you can use the $in operator in your query as:
db.emp.find({
"type" : { "$in": ["WebUser", "User"] },
"city" : { "$in": ["Pune", "Mumbai"] }
})
If you want to use in aggregation:
db.emp.aggregate([
{
"$match": {
"type" : { "$in": ["WebUser", "User"] },
"city" : { "$in": ["Pune", "Mumbai"] }
}
},
{ "$group": { "_id": null, "ids": { "$push": "$empId" } } }
])
or simply use the distinct() method to return an array of distinct empIds that match the above query as:
var employeeIds = db.emp.distinct("empId", {
"type" : { "$in": ["WebUser", "User"] },
"city" : { "$in": ["Pune", "Mumbai"] }
});
If you are looking for the AND operator
This example checks if a field exists AND is null
db.getCollection('TheCollection').find({
$and: [
{'the_key': { $exists: true }},
{'the_key': null}
]
})
This example checks if a field has 'value1' OR 'value2'
db.getCollection('TheCollection').find({
$or: [
{'the_key': 'value1'},
{`the_key': 'value2'}
]
})
When just checking for null, the return contains non-existing fields plus fields with value null
db.getCollection('TheCollection').find({'the_key': null})
You can use mongo db $or operator.
db.emp.find({ $or: [
{ "type": "WebUser", "city": "Pune" },
{ "type": "user", "city": "Mumbai"}
]})
You can pass conditions in the array.
For more reference see mongo docs
Display the document where in the “StudName” has value “Ajay Rathod”.
db.Student.find({name:"ajay rathod"})
{ "_id" : ObjectId("5fdd895cd2d5a20ee8cea0de"), "
Retrieve only Student Name and Grade.
db.Student.find({},{name:1,grade:1,_id:0})
{ "name" : "dhruv", "grade" : "A" }
{ "name" : "jay", "grade" : "B" }
{ "name" : "abhi", "grade" : "C" }
{ "name" : "aayush", "grade" : "A" }
{ "name" : "sukhdev", "grade" : "B" }
{ "name" : "dhruval", "grade" : "B" }
{ "name" : "ajay rathod", "grade" : "D" }
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({$and:[{"data.code":"special"},{"data.value":false}]}).pretty();
I have a real case in my project:
> db.foo.insert({a:'1',
... province: [{id:'1',name:'Yogyakarta',state:[{id:'1',name:'bantul'}]}]
... })
Then I find()...
> db.foo.find();
> { "_id" : ObjectId("5279ef4c6cfd9d5c0e19bbe0"),
"a" : "1",
"province" : [
{"id" : "1",
"name" : "Yogyakarta",
"state" : [
{"id" : "1","name" : "bantul" }
]
}
]
}
how to remove and update state with id='1'
REMOVE
To remove the documents that match a deletion criteria, call the remove() method with the <query> parameter.
db.foo.remove({'province.state.id': '1'})
Example
First, insert data Yogyakarta - Bantul
db.foo.insert({a:'1', province: [{id:'1',name:'Yogyakarta',state:[{id:'1',name:'bantul'}]}] })
Insert data Jakarta - Jakarta Selatan
db.foo.insert({a:'1', province: [{id:'2',name:'Jakarta',state:[{id:'2',name:'Jakarta Selatan'}]}] })
Now, you have two documents
db.foo.find();
Result
[
{ "a" : "1", "_id" : { "$oid" : "527b54c6cc937439340367f9" }, "province" : [ { "name" : "Yogyakarta", "id" : "1", "state" : [ { "name" : "bantul", "id" : "1" } ] } ] },
{ "a" : "1", "_id" : { "$oid" : "527b54d3cc937439340367fa" }, "province" : [ { "name" : "Jakarta", "id" : "2", "state" : [ { "name" : "Jakarta Selatan", "id" : "2" } ] } ] }
]
Now, delete document where the subdocument province contains a field state whose value 1.
db.foo.remove({'province.state.id': '1'})
Check
db.foo.find();
Now, you have one document
[
{ "a" : "1", "_id" : { "$oid" : "527b54d3cc937439340367fa" }, "province" : [ { "name" : "Jakarta", "id" : "2", "state" : [ { "name" : "Jakarta Selatan", "id" : "2" } ] } ] }
]
UPDATE
By default, the update() method updates a single document. If the multi option is set to true, the method updates all documents that match the query criteria.
db.foo.update({'province.state.id': '2'}, { $set: {'a': '2'} })
Check
db.foo.find();
Result
[
{ "a" : "2", "_id" : { "$oid" : "527b54d3cc937439340367fa" }, "province" : [ { "name" : "Jakarta", "id" : "2", "state" : [ { "name" : "Jakarta Selatan", "id" : "2" } ] } ] }
]