I have a use case where I am working with objects that appear as such:
{
"data": {
"uuid": 0001-1234-5678-9101
},
"organizationId": 10192432,
"lastCheckin": 2022-03-19T08:23:02.435+00:00
}
Due to some old bugs in our application, we've accumulated many duplicates for these items in the database. The origin of the duplicates has been resolved in an upcoming release, but I need to ensure that prior to the release there are no such duplicates because the release includes a unique constraint on the "data.uuid" property.
I am trying to delete records based on the following criteria:
Any duplicate record based on "data.uuid" WHERE lastCheckin is NOT the most recent OR organizationId is missing.
Unfortunately, I am rather new to using MongoDB and do not know how to express this in a query. I have tried aggregated to obtain the duplicate records and, while I've been able to do so, I have so far been unable to exclude the records in each duplicate group containing the most recent "lastCheckin" value or even include "organizationId" as a part of the aggregation. Here's what I came up with:
db.collection.aggregate([
{ $match: {
"_id": { "$ne": null },
"count": { "$gt": 1 }
}},
{ $group: {
_id: "$data.uuid",
"count": {
"$sum": 1
}
}},
{ $project: {
"uuid": "$_id",
"_id": 0
}}
])
The above was mangled together based on various other stackoverflow posts describing the aggregation of duplicates. I am not sure whether this is the right way to approach this problem. One immediate problem that I can identify is that simply getting the "data.uuid" property without any additional criteria allowing me to identify the invalid duplicates makes it hard to envision a single query that can delete the invalid records without taking the valid records.
Thanks for any help.
I am not sure if this is possible via a single query, but this is how I would approach it, first sort the documents by lastCheckIn and then group the documents by data.uuid, like this:
db.collection.aggregate([
{
$sort: {
lastCheckIn: -1
}
},
{
$group: {
_id: "$data.uuid",
"docs": {
"$push": "$$ROOT"
}
}
},
]);
Playground link.
Once you have these results, you can filter out the documents, according to your criteria, which you want to delete and collect their _id. The documents per group will be sorted by lastCheckIn in descending order, so filtering should be easy.
Finally, delete the documents, using this query:
db.collection.remove({_id: { $in: [\\ array of _ids collected above] }});
So, I tried to query
db.collection('collection_name').aggregate([
{
$match: { owner_id: '5be9b2f03ef77262c2bd49e6' }
},
{
$sort: { _id: -1 }
}])
the query above takes up 20s
but If I tried to query
db.collection('collection_name').aggregate([{$sort : {_id : -1}}])
it's only take 0.7s
Why does it the one without $match is actually faster than without match ?
update :
when I try this query
db.getCollection('callbackvirtualaccounts').aggregate([
{
$match: { owner_id: '5860457640b4fe652bd9c3eb' }
},
{
$sort: { created: -1 }
}
])
it's only takes 0.781s
Why sort by _id is slower than by created field ?
note : I'm using mongodb v3.0.0
db.collection('collection_name').aggregate([
{
$match: { owner_id: '5be9b2f03ef77262c2bd49e6' }
},
{
$sort: { _id: -1 }
}])
This collection probably won't be having and index on owner_id; Try using below mentioned index creation query and rerun your previous code.
db.collection('collection_name').createIndexes({ owner_id:1}) //Simple Index
or
db.collection('collection_name').createIndexes({ owner_id:1,_id:-1}) //Compound Index
**Note:: If you don't know how to compound index yet, you can create simple indexes individually on all keys which are used either in match or sort and that should be making query efficient as well.
The query speed depends upon a lot of factors. The size of collection, size of the document, indexes defined on the collection (and used in the queries and properly), the hardware components (like CPU, RAM, network) and other processes running at the time the query is running.
You have to tell what indexes are defined on the collection being discussed for further analysis. The command will retrieve them: db.collection.getIndexes()
Note the unique index on the _id field is created by default, and cannot be modified or deleted.
(i)
But If I tried to query: db.collection.aggregate( [ { $sort : { _id : -1 } } ] ) it's
only take 0.7s.
The query is faster because there is an index on the _id field and it is used in sort process. Aggregation queries use indexes with sort stage and when this sort happens early in the pipeline. You can verify if the index is used or not by generating a query plan (use explain with executionStats mode). There will be an index scan (IXSCAN) in the generated query plan.
(ii)
db.collection.aggregate([
{
$match: { owner_id: '5be9b2f03ef77262c2bd49e6' }
},
{
$sort: { _id: -1 }
}
])
The query above takes up 20s.
When I try this query it's only takes 0.781s.
db.collection.aggregate([
{
$match: { owner_id: '5860457640b4fe652bd9c3eb' }
},
{
$sort: { created: -1 }
}
])
Why sort by _id is slower than by created field ?
Cannot come to any conclusions with the available information. In general, the $match and $sort stages present early in the aggregation query can use any indexes created on the fields used in the operations.
Generating a query plan will reveal what the issues are.
Please run the explain with executionStats mode and post the query plan details for all queries in question. There is documentation for Mongodb v3.0.0 version on generation query plans using explain: db.collection.explain()
I have a Mongo document which holds an array of elements.
I'd like to reset the .handled attribute of all objects in the array where .profile = XX.
The document is in the following form:
{
"_id": ObjectId("4d2d8deff4e6c1d71fc29a07"),
"user_id": "714638ba-2e08-2168-2b99-00002f3d43c0",
"events": [{
"handled": 1,
"profile": 10,
"data": "....."
} {
"handled": 1,
"profile": 10,
"data": "....."
} {
"handled": 1,
"profile": 20,
"data": "....."
}
...
]
}
so, I tried the following:
.update({"events.profile":10},{$set:{"events.$.handled":0}},false,true)
However it updates only the first matched array element in each document. (That's the defined behaviour for $ - the positional operator.)
How can I update all matched array elements?
With the release of MongoDB 3.6 ( and available in the development branch from MongoDB 3.5.12 ) you can now update multiple array elements in a single request.
This uses the filtered positional $[<identifier>] update operator syntax introduced in this version:
db.collection.update(
{ "events.profile":10 },
{ "$set": { "events.$[elem].handled": 0 } },
{ "arrayFilters": [{ "elem.profile": 10 }], "multi": true }
)
The "arrayFilters" as passed to the options for .update() or even
.updateOne(), .updateMany(), .findOneAndUpdate() or .bulkWrite() method specifies the conditions to match on the identifier given in the update statement. Any elements that match the condition given will be updated.
Noting that the "multi" as given in the context of the question was used in the expectation that this would "update multiple elements" but this was not and still is not the case. It's usage here applies to "multiple documents" as has always been the case or now otherwise specified as the mandatory setting of .updateMany() in modern API versions.
NOTE Somewhat ironically, since this is specified in the "options" argument for .update() and like methods, the syntax is generally compatible with all recent release driver versions.
However this is not true of the mongo shell, since the way the method is implemented there ( "ironically for backward compatibility" ) the arrayFilters argument is not recognized and removed by an internal method that parses the options in order to deliver "backward compatibility" with prior MongoDB server versions and a "legacy" .update() API call syntax.
So if you want to use the command in the mongo shell or other "shell based" products ( notably Robo 3T ) you need a latest version from either the development branch or production release as of 3.6 or greater.
See also positional all $[] which also updates "multiple array elements" but without applying to specified conditions and applies to all elements in the array where that is the desired action.
Also see Updating a Nested Array with MongoDB for how these new positional operators apply to "nested" array structures, where "arrays are within other arrays".
IMPORTANT - Upgraded installations from previous versions "may" have not enabled MongoDB features, which can also cause statements to fail. You should ensure your upgrade procedure is complete with details such as index upgrades and then run
db.adminCommand( { setFeatureCompatibilityVersion: "3.6" } )
Or higher version as is applicable to your installed version. i.e "4.0" for version 4 and onwards at present. This enabled such features as the new positional update operators and others. You can also check with:
db.adminCommand( { getParameter: 1, featureCompatibilityVersion: 1 } )
To return the current setting
UPDATE:
As of Mongo version 3.6, this answer is no longer valid as the mentioned issue was fixed and there are ways to achieve this. Please check other answers.
At this moment it is not possible to use the positional operator to update all items in an array. See JIRA http://jira.mongodb.org/browse/SERVER-1243
As a work around you can:
Update each item individually
(events.0.handled events.1.handled
...) or...
Read the document, do the edits
manually and save it replacing the
older one (check "Update if
Current" if you want to ensure
atomic updates)
What worked for me was this:
db.collection.find({ _id: ObjectId('4d2d8deff4e6c1d71fc29a07') })
.forEach(function (doc) {
doc.events.forEach(function (event) {
if (event.profile === 10) {
event.handled=0;
}
});
db.collection.save(doc);
});
I think it's clearer for mongo newbies and anyone familiar with JQuery & friends.
This can also be accomplished with a while loop which checks to see if any documents remain that still have subdocuments that have not been updated. This method preserves the atomicity of your updates (which many of the other solutions here do not).
var query = {
events: {
$elemMatch: {
profile: 10,
handled: { $ne: 0 }
}
}
};
while (db.yourCollection.find(query).count() > 0) {
db.yourCollection.update(
query,
{ $set: { "events.$.handled": 0 } },
{ multi: true }
);
}
The number of times the loop is executed will equal the maximum number of times subdocuments with profile equal to 10 and handled not equal to 0 occur in any of the documents in your collection. So if you have 100 documents in your collection and one of them has three subdocuments that match query and all the other documents have fewer matching subdocuments, the loop will execute three times.
This method avoids the danger of clobbering other data that may be updated by another process while this script executes. It also minimizes the amount of data being transferred between client and server.
This does in fact relate to the long standing issue at http://jira.mongodb.org/browse/SERVER-1243 where there are in fact a number of challenges to a clear syntax that supports "all cases" where mutiple array matches are found. There are in fact methods already in place that "aid" in solutions to this problem, such as Bulk Operations which have been implemented after this original post.
It is still not possible to update more than a single matched array element in a single update statement, so even with a "multi" update all you will ever be able to update is just one mathed element in the array for each document in that single statement.
The best possible solution at present is to find and loop all matched documents and process Bulk updates which will at least allow many operations to be sent in a single request with a singular response. You can optionally use .aggregate() to reduce the array content returned in the search result to just those that match the conditions for the update selection:
db.collection.aggregate([
{ "$match": { "events.handled": 1 } },
{ "$project": {
"events": {
"$setDifference": [
{ "$map": {
"input": "$events",
"as": "event",
"in": {
"$cond": [
{ "$eq": [ "$$event.handled", 1 ] },
"$$el",
false
]
}
}},
[false]
]
}
}}
]).forEach(function(doc) {
doc.events.forEach(function(event) {
bulk.find({ "_id": doc._id, "events.handled": 1 }).updateOne({
"$set": { "events.$.handled": 0 }
});
count++;
if ( count % 1000 == 0 ) {
bulk.execute();
bulk = db.collection.initializeOrderedBulkOp();
}
});
});
if ( count % 1000 != 0 )
bulk.execute();
The .aggregate() portion there will work when there is a "unique" identifier for the array or all content for each element forms a "unique" element itself. This is due to the "set" operator in $setDifference used to filter any false values returned from the $map operation used to process the array for matches.
If your array content does not have unique elements you can try an alternate approach with $redact:
db.collection.aggregate([
{ "$match": { "events.handled": 1 } },
{ "$redact": {
"$cond": {
"if": {
"$eq": [ { "$ifNull": [ "$handled", 1 ] }, 1 ]
},
"then": "$$DESCEND",
"else": "$$PRUNE"
}
}}
])
Where it's limitation is that if "handled" was in fact a field meant to be present at other document levels then you are likely going to get unexepected results, but is fine where that field appears only in one document position and is an equality match.
Future releases ( post 3.1 MongoDB ) as of writing will have a $filter operation that is simpler:
db.collection.aggregate([
{ "$match": { "events.handled": 1 } },
{ "$project": {
"events": {
"$filter": {
"input": "$events",
"as": "event",
"cond": { "$eq": [ "$$event.handled", 1 ] }
}
}
}}
])
And all releases that support .aggregate() can use the following approach with $unwind, but the usage of that operator makes it the least efficient approach due to the array expansion in the pipeline:
db.collection.aggregate([
{ "$match": { "events.handled": 1 } },
{ "$unwind": "$events" },
{ "$match": { "events.handled": 1 } },
{ "$group": {
"_id": "$_id",
"events": { "$push": "$events" }
}}
])
In all cases where the MongoDB version supports a "cursor" from aggregate output, then this is just a matter of choosing an approach and iterating the results with the same block of code shown to process the Bulk update statements. Bulk Operations and "cursors" from aggregate output are introduced in the same version ( MongoDB 2.6 ) and therefore usually work hand in hand for processing.
In even earlier versions then it is probably best to just use .find() to return the cursor, and filter out the execution of statements to just the number of times the array element is matched for the .update() iterations:
db.collection.find({ "events.handled": 1 }).forEach(function(doc){
doc.events.filter(function(event){ return event.handled == 1 }).forEach(function(event){
db.collection.update({ "_id": doc._id },{ "$set": { "events.$.handled": 0 }});
});
});
If you are aboslutely determined to do "multi" updates or deem that to be ultimately more efficient than processing multiple updates for each matched document, then you can always determine the maximum number of possible array matches and just execute a "multi" update that many times, until basically there are no more documents to update.
A valid approach for MongoDB 2.4 and 2.2 versions could also use .aggregate() to find this value:
var result = db.collection.aggregate([
{ "$match": { "events.handled": 1 } },
{ "$unwind": "$events" },
{ "$match": { "events.handled": 1 } },
{ "$group": {
"_id": "$_id",
"count": { "$sum": 1 }
}},
{ "$group": {
"_id": null,
"count": { "$max": "$count" }
}}
]);
var max = result.result[0].count;
while ( max-- ) {
db.collection.update({ "events.handled": 1},{ "$set": { "events.$.handled": 0 }},{ "multi": true })
}
Whatever the case, there are certain things you do not want to do within the update:
Do not "one shot" update the array: Where if you think it might be more efficient to update the whole array content in code and then just $set the whole array in each document. This might seem faster to process, but there is no guarantee that the array content has not changed since it was read and the update is performed. Though $set is still an atomic operator, it will only update the array with what it "thinks" is the correct data, and thus is likely to overwrite any changes occurring between read and write.
Do not calculate index values to update: Where similar to the "one shot" approach you just work out that position 0 and position 2 ( and so on ) are the elements to update and code these in with and eventual statement like:
{ "$set": {
"events.0.handled": 0,
"events.2.handled": 0
}}
Again the problem here is the "presumption" that those index values found when the document was read are the same index values in th array at the time of update. If new items are added to the array in a way that changes the order then those positions are not longer valid and the wrong items are in fact updated.
So until there is a reasonable syntax determined for allowing multiple matched array elements to be processed in single update statement then the basic approach is to either update each matched array element in an indvidual statement ( ideally in Bulk ) or essentially work out the maximum array elements to update or keep updating until no more modified results are returned. At any rate, you should "always" be processing positional $ updates on the matched array element, even if that is only updating one element per statement.
Bulk Operations are in fact the "generalized" solution to processing any operations that work out to be "multiple operations", and since there are more applications for this than merely updating mutiple array elements with the same value, then it has of course been implemented already, and it is presently the best approach to solve this problem.
First: your code did not work because you were using the positional operator $ which only identifies an element to update in an array but does not even explicitly specify its position in the array.
What you need is the filtered positional operator $[<identifier>]. It would update all elements that match an array filter condition.
Solution:
db.collection.update({"events.profile":10}, { $set: { "events.$[elem].handled" : 0 } },
{
multi: true,
arrayFilters: [ { "elem.profile": 10 } ]
})
Visit mongodb doc here
What the code does:
{"events.profile":10} filters your collection and return the documents matching the filter
The $set update operator: modifies matching fields of documents it acts on.
{multi:true} It makes .update() modifies all documents matching the filter hence behaving like updateMany()
{ "events.$[elem].handled" : 0 } and arrayFilters: [ { "elem.profile": 10 } ]
This technique involves the use of the filtered positional array with arrayFilters. the filtered positional array here $[elem] acts as a placeholder for all elements in the array fields that match the conditions specified in the array filter.
Array filters
You can update all elements in MongoDB
db.collectioname.updateOne(
{ "key": /vikas/i },
{ $set: {
"arr.$[].status" : "completed"
} }
)
It will update all the "status" value to "completed" in the "arr" Array
If Only one document
db.collectioname.updateOne(
{ key:"someunique", "arr.key": "myuniq" },
{ $set: {
"arr.$.status" : "completed",
"arr.$.msgs": {
"result" : ""
}
} }
)
But if not one and also you don't want all the documents in the array to update then you need to loop through the element and inside the if block
db.collectioname.find({findCriteria })
.forEach(function (doc) {
doc.arr.forEach(function (singlearr) {
if (singlearr check) {
singlearr.handled =0
}
});
db.collection.save(doc);
});
I'm amazed this still hasn't been addressed in mongo. Overall mongo doesn't seem to be great when dealing with sub-arrays. You can't count sub-arrays simply for example.
I used Javier's first solution. Read the array into events then loop through and build the set exp:
var set = {}, i, l;
for(i=0,l=events.length;i<l;i++) {
if(events[i].profile == 10) {
set['events.' + i + '.handled'] = 0;
}
}
.update(objId, {$set:set});
This can be abstracted into a function using a callback for the conditional test
The thread is very old, but I came looking for answer here hence providing new solution.
With MongoDB version 3.6+, it is now possible to use the positional operator to update all items in an array. See official documentation here.
Following query would work for the question asked here. I have also verified with Java-MongoDB driver and it works successfully.
.update( // or updateMany directly, removing the flag for 'multi'
{"events.profile":10},
{$set:{"events.$[].handled":0}}, // notice the empty brackets after '$' opearor
false,
true
)
Hope this helps someone like me.
I've been looking for a solution to this using the newest driver for C# 3.6 and here's the fix I eventually settled on. The key here is using "$[]" which according to MongoDB is new as of version 3.6. See https://docs.mongodb.com/manual/reference/operator/update/positional-all/#up.S[] for more information.
Here's the code:
{
var filter = Builders<Scene>.Filter.Where(i => i.ID != null);
var update = Builders<Scene>.Update.Unset("area.$[].discoveredBy");
var result = collection.UpdateMany(filter, update, new UpdateOptions { IsUpsert = true});
}
For more context see my original post here:
Remove array element from ALL documents using MongoDB C# driver
$[] operator selects all nested array ..You can update all array items with '$[]'
.update({"events.profile":10},{$set:{"events.$[].handled":0}},false,true)
Reference
Please be aware that some answers in this thread suggesting use $[] is WRONG.
db.collection.update(
{"events.profile":10},
{$set:{"events.$[].handled":0}},
{multi:true}
)
The above code will update "handled" to 0 for all elements in "events" array, regardless of its "profile" value. The query {"events.profile":10} is only to filter the whole document, not the documents in the array. In this situation it is a must to use $[elem] with arrayFilters to specify the condition of array items so Neil Lunn's answer is correct.
Actually, The save command is only on instance of Document class.
That have a lot of methods and attribute. So you can use lean() function to reduce work load.
Refer here. https://hashnode.com/post/why-are-mongoose-mongodb-odm-lean-queries-faster-than-normal-queries-cillvawhq0062kj53asxoyn7j
Another problem with save function, that will make conflict data in with multi-save at a same time.
Model.Update will make data consistently.
So to update multi items in array of document. Use your familiar programming language and try something like this, I use mongoose in that:
User.findOne({'_id': '4d2d8deff4e6c1d71fc29a07'}).lean().exec()
.then(usr =>{
if(!usr) return
usr.events.forEach( e => {
if(e && e.profile==10 ) e.handled = 0
})
User.findOneAndUpdate(
{'_id': '4d2d8deff4e6c1d71fc29a07'},
{$set: {events: usr.events}},
{new: true}
).lean().exec().then(updatedUsr => console.log(updatedUsr))
})
Update array field in multiple documents in mongo db.
Use $pull or $push with update many query to update array elements in mongoDb.
Notification.updateMany(
{ "_id": { $in: req.body.notificationIds } },
{
$pull: { "receiversId": req.body.userId }
}, function (err) {
if (err) {
res.status(500).json({ "msg": err });
} else {
res.status(200).json({
"msg": "Notification Deleted Successfully."
});
}
});
if you want to update array inside array
await Booking.updateOne(
{
userId: req.currentUser?.id,
cart: {
$elemMatch: {
id: cartId,
date: date,
//timeSlots: {
//$elemMatch: {
//id: timeSlotId,
//},
//},
},
},
},
{
$set: {
version: booking.version + 1,
'cart.$[i].timeSlots.$[j].spots': spots,
},
},
{
arrayFilters: [
{
'i.id': cartId,
},
{
'j.id': timeSlotId,
},
],
new: true,
}
);
I tried the following and its working fine.
.update({'events.profile': 10}, { '$set': {'events.$.handled': 0 }},{ safe: true, multi:true }, callback function);
// callback function in case of nodejs
I have question about mongoDB (version:"3.4.10") index arrays as I see they don't work correctly. Maybe I am doing something wrong.
I have schedule document that has some props that aren't important for this question. But each schedule has it's plan (occurrence) period in array.
{ .... "plans": [ { "startDateTime": "2018-01-04T00:00:00Z",
"endDateTime": "2018-01-04T23:59:59Z" }, { "startDateTime":
"2018-01-11T00:00:00Z", "endDateTime": "2018-01-11T23:59:59Z" } ... ]
},
Now I need to search schedule documents by that array item and find all schedules that fit in that period.
I have created index plans.startDateTime and plans.endDateTime.
When I perform following query using compas option explain plan I get bad really bad results.
{"Plans.StartDateTime": {$lt: new Date ('2018-01-10')}, "Plans.EndDateTime": {$gte: new Date ('2018-01-15')} }
Results are (this is in test environment where number of documents are really low, in production ratio would be even higher)
Documents Returned:2823
Index Keys Examined:65708
Documents Examined:11554
When I go little bit deeper in analysis I got following (meaning that mongo is ignoring plan end date in index search):
"indexBounds": { "Plans.StartDateTime": [ "(true, new
Date(1515542400000))" ], "Plans.EndDateTime": [ "[MinKey,
MaxKey]" ] },
Can somebody please tell me how to create better indexes for following search because this one isn't working?
In order to find all scheduleDocuments having at least one plan overlapping with a given time interval (e.g. 2018-01-10 and 2018-01-14) you have to use $elemMatch MongoDB operator.
db.scheduleDocuments.find({
plans: {
$elemMatch: {
startDateTime: { $lte: ISODate("2018-01-14Z") },
endDateTime: { $gt: ISODate("2018-01-10Z") }
}
}
});
The rule used to test for overlapping intervals can be found here.
This search performs a collection scan, unless you create an index on the array.
db.scheduleDocuments.createIndex({
"plans.startDateTime": 1,
"plans.endDateTime": 1
});
Thanks to the index, unmatching documents in the collection are not scanned at all. An IXSCAN is performed and only matching documents are accessed to be fetched and returned.