Let's say i want to return the latest inserted document from the subdocument. I want to be able to return the second record within the tags array w/ the _id of 54a1845def7572cd0e3fe288
So I far I have this query but it returns all values in the tags array.
db.modules.findOne({_id:"ui","svn_branches.branch":"Rocky"},{"svn_branches.$":1})
Mongodb array:
{
"_id" : "ui",
"svn_branches" : [
{
"updated_at" : ISODate("2013-06-12T20:48:17.297Z"),
"branch" : "Rocky",
"revision" : 0,
"tags" : [
{
"_id" : ObjectId("54a178b8ef7572d30e3fe288"),
"commit_message" : "r277 | ssmith | 2015-02-11 17:43:23 -0400 (Wed, 11 Feb 2015)",
"latest_tag" : "20150218r1_6.32_abc",
"revision" : 1,
"tag_revision_number" : "280",
"updated_at" : ISODate("2015-02-18T19:54:54.062Z")
},
{
"_id" : ObjectId("54a1845def7572cd0e3fe288"),
"commit_message" : "r271 | sam | 2dskjh\n",
"latest_tag" : "20150218r2_6.32_abc",
"revision" : 2,
"tag_revision_number" : "281",
"updated_at" : ISODate("2015-02-19T19:54:54.062Z")
}
]
}
]
}
Simple Solution
Let say we have a category as a document and items as a subdocument.
// find document from collection
const category = await Category.findOne({ _id:'$hec453d235xhHe4Y' });
// fetch last index of sub-document
const lastItemIndex = category.items.length - 1;
// here is the last item of sub-document
console.log(category.items[lastItemIndex]);
as mongodb inserted the latest sub-document at last index, so we need to find the last index for the latest sub-doc.
Queries in MongoDB do not return subdocuments (or, as in your case, subdocuments of subdocuments). They match and return the the documents in the collection. The documents' shape can be changed a bit by projection, but it's limited. If you want to find the latest tag commonly, you probably want to make your documents represent tags. Having an array in an array is generally a bad idea in MongoDB, too.
If this is an uncommon operation, and one that doesn't need to be particularly fast, you can use an aggregation:
db.modules.aggregate([
{ "$unwind" : "$svn_branches" },
{ "$unwind" : "$svn_branches.tags" },
{ "$sort" : { "svn_branches.tags.updated_at" : -1 } },
{ "$group" : { "_id" : "$_id", "latest_tag" : { "$first" : "$svn_branches.tags" } } }
])
I needed to find the last entry of subdocuments and I managed to make it to work with the $slice projection operator: mondodb.com > $slice (projection)
db.modules.find({_id:'ui', 'svn_branches.branch':'Rocky'},
{ 'svn_branches.tags': {$slice:-1} } )
I had only one level, if this doesn't work, please let me know.
Related
I have a collection with the documents like this with 25 documents
{
"_id" : ObjectId("<some id>"),
"code" : "1111",
"myArray" : ["Choocolate"]
},
{
"_id" : ObjectId("<some id>"),
"code" : "2222"
"myArray" : ["Choocolate"]
},
{
"_id" : ObjectId("<some id>"),
"code" : "3333",
"myArray" : ["Choocolate"]
},
{
"_id" : ObjectId("<some id>"),
"code" : "4444",
"myArray" : ["Choocolate"]
}
and so on
I want to add an item to an myArray only fore certain documents based on a condition. so I tried this
db.mycollection.update
({ "code":
{
"$nin": ["1111","2222"]
},
{
$push: { "myArray": "Coffee" }
}
)
I expect 'Coffee' to be added to myArray in all documents except the ones with code 1111 or 2222. But only it is added to an array only in one document.
How to I add an item to anArray in multiple documents based on a condition against a field in a document?
Based on the documentation update updates only a single element:
By default, the db.collection.update() method updates a single document. Include the option multi: true to update all documents that match the query criteria.
https://docs.mongodb.com/manual/reference/method/db.collection.update/
To update more use updateMany:
https://docs.mongodb.com/manual/reference/method/db.collection.updateMany/
I have documents like this in a collection called 'variants':
{
"_id" : "An_FM000900_Var_10_100042505_100042505_G_A",
"analysisId" : "FM000900",
"chromosome" : 10,
"start" : 100042505,
"end" : 100042505,
"size" : 1,
"reference" : "G",
"alternative" : "A",
"effects" : [
{
"_id" : "Analysis:FM000900-Variant:An_FM000900_Var_10_100042505_100042505_G_A-Effect:0",
"biotype" : "protein_coding",
"impact" : "LOW",
},
{
"_id" : "Analysis:FM000900-Variant:An_FM000900_Var_10_100042505_100042505_G_A-Effect:1",
"biotype" : "protein_coding",
"impact" : "MODERATE",
}
]
}
I want to find documents in that collection that meet some criteria ("analysisId":"FM000900"), and after that I want to project over 'effects' array field to bring just the first element in 'effects' array that meet some criteria ("biotype" : "protein_coding" and "impact" : "MODERATE").
The thing is that I just want to show the main 'variant' document if and only if at least one element in the 'effects' array has meet the criteria.
With the following query I get the expected result except that I get 'variant' documents with 'effects' array field empty.
db.getCollection('variants').find(
{
"analysisId":"FM000900"
}
,
{
"effects":{
"$elemMatch" : {
"biotype" : "protein_coding",
"impact" : "MODERATE"
}
}
}
).skip(0).limit(200)
Can somebody transform this query to only get 'variant' documents with some element in 'effect' array after the projection if possible?
Can it be done in another way, without using aggregation framework if possible? as the collection has millions of documents and it has to be performant.
Thanks a lot, guys!!!
Simply use $elemMatch as query operator in addition of your projection, it will filter variants that have at least one effects array element that match all conditions.
So your query will be :
db.getCollection('variants').find(
{
"analysisId":"FM000900",
"effects":{
"$elemMatch" : {
"biotype" : "protein_coding",
"impact" : "MODERATE"
}
}
}
,
{
"effects":{
"$elemMatch" : {
"biotype" : "protein_coding",
"impact" : "MODERATE"
}
}
}
).skip(0).limit(200)
In addition, a compound multikey index that covers both query and projection can improve reading performance, but use it carefully as it can drastically reduce writing performances.
Since every collection in mongodb has a default index on the _id column, I wanted to leverage it for my scenario as below.
I have my collection as below,
{
"_id":{
"timestamp" : ISODate("2016-08-24T23:22:20.201Z"),
"departmentname" : "sales",
"city":"NJ"
}
//Other fields in my collection
}
With this structure I am able to query as below,
db.getCollection('test').find(
{
"_id" : {
"timestamp" : ISODate("2016-08-21T23:22:20.201Z"),
"departmentname" : "sales",
"city":"NJ"
}
}
)
But, when I query by one or more fields in which are part of _id column as below,
db.getCollection('test').find(
{
"_id" : {
"timestamp" : ISODate("2016-08-21T23:22:20.201Z")
}
}
)
(OR)
db.getCollection('test').find(
{
"_id" : {
"departmentname" : "sales"
}
}
)
(OR)
db.getCollection('test').find(
{
"_id" : {
"departmentname" : "sales",
"city":"NJ"
}
}
)
I do not see any documents returned
When I checked with .explain() I see that it has used Index but did not find any documents.
Also, I would like to do date range queries on timestamp field along with query on one or more fields in the _id column like below,
db.getCollection('test').find(
{
"_id.timestamp" : {
"$gte": ISODate("2011-08-21T23:22:20.201Z")
},
"_id.departmentname" : "sales"
}
)
But, I do not see any documents returned. When I run .explain() I see it has used colscan and not index.
Can someone help me on the right way to query by one or more fields on my _id column.
Thanks,
Sri
You can try following query, in first case:-
db.getCollection('test').find(
{
"_id.timestamp" : ISODate("2016-08-21T23:22:20.201Z")
})
And this for multiple fields:
db.getCollection('test').find(
{
"_id.timestamp" : ISODate("2016-08-21T23:22:20.201Z"),
"_id.departmentname" : "sales",
})
I have a number of Mongodb documents of the following form:
{
"auditedId" : "53d0f648e4b064e8d746b31c",
"modifications" : [
{
"auditRecordId" : ObjectId("53d0f648e4b064e8d746b31d"),
"modified" : "2014-07-22 18:33:05"
},
{
"auditRecordId" : ObjectId("53d0f648e4b064e8d746b31e"),
"modified" : "2014-07-24 14:15:27"
},
{
"auditRecordId" : ObjectId("53d0f648e4b064e8d746b31f"),
"modified" : "2014-07-24 12:04:24"
}
]
}
For each of these documents I want to find "auditRecordId" value which corresponds to the latest modification. In the given example I want to retrieve
"auditRecordId" : ObjectId("53d0f648e4b064e8d746b31e")
Or, even better:
{
"auditRecordId" : ObjectId("53d0f648e4b064e8d746b31e"),
"modified" : "2014-07-24 14:15:27"
}
Is there any way how I can do this without writing map-reduce functions?
Whenever you have an array in your document, the aggregate method is your friend :)
db.foo.aggregate([
// De-normalize the 'modifications' array
{"$unwind":"$modifications"},
// Sort by 'modifications.modified' descending
{"$sort":{"modifications.modified":-1}},
// Pick the first one i.e., the max
{"$limit":1}
])
Output:
{
"result" : [
{
"_id" : ObjectId("53d12be57a462c7459b6f1c7"),
"auditedId" : "53d0f648e4b064e8d746b31c",
"modifications" : {
"auditRecordId" : ObjectId("53d0f648e4b064e8d746b31e"),
"modified" : "2014-07-24 14:15:27"
}
}
],
"ok" : 1
}
Just to illustrate the $unwind operator, I used the above query with $limit. If you have multiple documents of the above format, and you want to retrieve the latest modification in each, you'll have to add another $group phase in your aggregation pipeline and use the $first operator:
db.foo.aggregate([
{"$unwind":"$modifications"},
{"$sort":{"modifications.modified":-1}},
{"$group":{
"_id" : "$auditedId",
"modifications" : {$first:"$modifications"}}}
])
I have a document with sub-document which looks something like:
{
"name" : "some name1"
"like" : [
{ "date" : ISODate("2012-11-30T19:00:00Z") },
{ "date" : ISODate("2012-12-02T19:00:00Z") },
{ "date" : ISODate("2012-12-01T19:00:00Z") },
{ "date" : ISODate("2012-12-03T19:00:00Z") }
]
}
Is it possible to fetch documents "most liked" (average value for the last 7 days) and sort by the count?
There are a few different ways to solve this problem. The solution I will focus on uses mongodb's aggregation framework. First, here is an aggregation pipeline that will solve your problem, following it will be an explanation/breakdown of what is happening in the command.
db.testagg.aggregate(
{ $unwind : '$likes' },
{ $group : { _id : '$_id', numlikes : { $sum : 1 }}},
{ $sort : { 'numlikes' : 1}})
This pipeline has 3 main commands:
1) Unwind: this splits up the 'likes' field so that there is 1 'like' element per document
2) Group: this regroups the document using the _id field, incrementing the numLikes field for every document it finds. This will cause numLikes to be filled with a number equal to the number of elements that were in "likes" before
3) Sort: Finally, we sort the return values in ascending order based on numLikes. In a test I ran the output of this command is:
{"result" : [
{
"_id" : 1,
"numlikes" : 1
},
{
"_id" : 2,
"numlikes" : 2
},
{
"_id" : 3,
"numlikes" : 3
},
{
"_id" : 4,
"numlikes" : 4
}....
This is for data inserted via:
for (var i=0; i < 100; i++) {
db.testagg.insert({_id : i})
for (var j=0; j < i; j++) {
db.testagg.update({_id : i}, {'$push' : {'likes' : j}})
}
}
Note that this does not completely answer your question as it avoids the issue of picking the date range, but it should hopefully get you started and moving in the right direction.
Of course, there are other ways to solve this problem. One solution might be to just do all of the sorting and manipulations client-side. This is just one method for getting the information you desire.
EDIT: If you find this somewhat tedious, there is a ticket to add a $size operator to the aggregation framework, I invite you to watch and potentially upvote it to try and speed to addition of this new operator if you are interested.
https://jira.mongodb.org/browse/SERVER-4899
A better solution would be to keep a count field that will record how many likes for this document. While you can use aggregation to do this, the performance will likely be not very good. Having a index on the count field will make read operation fast, and you can use atomic operation to increment the counter when inserting new likes.
You can use this simplify the above aggregation query by the following from mongodb v3.4 onwards:
> db.test.aggregate([
{ $unwind: "$like" },
{ $sortByCount: "$_id" }
]).pretty()
{ "_id" : ObjectId("5864edbfa4d3847e80147698"), "count" : 4 }
Also as #ACE said you can now use $size within a projection instead:
db.test.aggregate([
{ $project: { count: { $size : "$like" } } }
]);
{ "_id" : ObjectId("5864edbfa4d3847e80147698"), "count" : 4 }