I have a document in my Mongo collection which has a field with the following structure:
"_id" : "F7WNvjwnFZZ7HoKSF",
"process" : [
{
"process_id" : "wTGqVk5By32mpXadZ",
"stages" : [
{
"stage_id" : "D6Huk89DGFsd29ds7",
"completed" : "N"
},
{
"stage_id" : "Msd390vekn09nvL23",
"completed" : "N"
}
]
}
]
I need to update the value of completed where the stage_id is equal to 'D6Huk89DGFsd29ds7' - the update query will not know which object in the stages array this value of stage_id will be in.
How do I do this?
Since you have nested arrays in your object, this is bit tricky and I'm not sure if this problem can be solved with help of just one update query.
However, if you happen to know index of your matching object in first array, in your case process[0] you can write your update query like.
db.collection.update(
{"process.stages.stage_id":"D6Huk89DGFsd29ds7"},
{$set:{"process.0.stages.$.completed":"Y"}}
);
Query above will work perfect with your test case. Again, there is still possibility of having multiple objects at root level and there is no guarantee that matching object will always be at 0 index.
Solution I proposed above will fail if you have multiple children of process and if matching index of object is not zero.
However, you can achieve your goal with help of client side programming. That is find matching document, modify on client side and replace whole document with new content.
Since this approach is very in efficient, I'll suggest that you should consider altering your document structure to avoid nesting. Create another collection and move content of process array there.
In the end, I removed the outer process block, so that the process_id and stages were in the root of the document - made the process of updating easier using:
MyColl.update(
{
_id: 'F7WNvjwnFZZ7HoKSF',
"stages.stage_id": 'D6Huk89DGFsd29ds7'
},
{
$set: {"stages.$.completed": 'Y'}
}
);
Related
we have a collection with big amount of documents, lets say around 100k. We now want to count the number of documents which has the key x set.
If I try it with Collection.countDocuments({ x: { $exists: true }}) I get the result, but it creates instantly a warning in the console: Query Targeting: Scanned Objects / Returned has gone above 1000.
So, is there a better way to count the documents? There is a Index on the field, is it possible to get the length of the index?
Thanks
Theres no real way of viewing the index trees in Mongo, what other people have linked you just returns the size of the tree, I'm not sure how useful that information is in this context.
Now to your question is this the best way to count?.
The answer is Yes ... -ish.
countDocuments is a wrapper function, it just simulates the following pipeline:
db.collection.aggregate([
{ $match: <query> },
{ $group: { _id: null, n: { $sum: 1 } } } )
])
This pipeline is the most efficient way to go, but the difference between running this aggregation and using the wrapper function is about 100-200 milliseconds, depending on your machine spec.
Meaning if you're looking for "way" better performance you're not going to find it.
With that said this warning is stupid, it just means you have more than 1000 documents with that field. The true purpose of it is to alert you in the case you're trying to query 1-20 documents without a proper index.
You can use the indexSizes field returned by the stats() method.
The stats() method "Returns statistics about the collection".
See example here :
https://docs.mongodb.com/manual/reference/method/db.collection.stats/#basic-stats-lookup
{
...,
"indexSizes" : {
"_id_" : 237568,
"cuisine_1" : 143360,
"borough_1_cuisine_1" : 151552,
"borough_1_address.zipcode_1" : 151552
},
...
}
indexSize key return size as in space used in storing not count
Check With Explain if index getting used or not . (Update in question Also)
can use hint option to check the performance after specifying index
Or precalculate count by $inc operator might good option if possible in you use case
try cursor.count if its faster countDocument should been faster but no harm in checking
https://docs.mongodb.com/manual/reference/method/cursor.count/
I'm struggling with a seemingly simple query in mongodb.
I have a job collection that has objects like:
{
"_id" : ObjectId("5995c1fc3c2a353a782ee51b"),
"stages" : [
{
"start" : ISODate("2017-02-02T22:06:26Z"),
"end" : ISODate("2017-02-03T22:06:26Z"),
"name" : "stage_one"
},
{
"start" : ISODate("2017-02-03T22:06:26Z"),
"end" : ISODate("2017-02-07T20:34:01Z"),
"name" : "stage_two"
}
]
}
I want to get a job whose second stage does not have an end time, i.e. end is null or not defined.
According to the mongo docs on querying for null and querying an array of embedded documents, it would seem the correct query should be:
db.job.findOne({'stages.1.end': null})
However, running that query returns me the job above which does have a non-null end date. In fact, if I run the query with count instead of findOne, I see that all jobs are returned - no filtering is done at all.
For completeness, here is the output from an example on a fresh mongo instance:
So in this example, I would expect db.job.findOne({'stages.1.end': null}) to return nothing since there is only one document and its second stage has a non-null end date.
This feels like the sort of issue where it's just me being an idiot and if so, I apologise profusely.
Thanks in advance for your help and let me know if you need any more details!
EDIT:
After some more experimentation, I think I can achieve what I want with the following:
db.job.find({$or: [{'stages.1.end': { $type: 10 }}, {'stages.1.end': {$exists: false}}]})
While this gets the job done, it doesn't feel like the simplest way and I still don't understand why the original query doesn't work. If anyone could shed some light on this it'd be much appreciated.
What's a good way to store a set of documents in MongoDB where order is important? I need to easily insert documents at an arbitrary position and possibly reorder them later.
I could assign each item an increasing number and sort by that, or I could sort by _id, but I don't know how I could then insert another document in between other documents. Say I want to insert something between an element with a sequence of 5 and an element with a sequence of 6?
My first guess would be to increment the sequence of all of the following elements so that there would be space for the new element using a query something like db.items.update({"sequence":{$gte:6}}, {$inc:{"sequence":1}}). My limited understanding of Database Administration tells me that a query like that would be slow and generally a bad idea, but I'm happy to be corrected.
I guess I could set the new element's sequence to 5.5, but I think that would get messy rather quickly. (Again, correct me if I'm wrong.)
I could use a capped collection, which has a guaranteed order, but then I'd run into issues if I needed to grow the collection. (Yet again, I might be wrong about that one too.)
I could have each document contain a reference to the next document, but that would require a query for each item in the list. (You'd get an item, push it onto the results array, and get another item based on the next field of the current item.) Aside from the obvious performance issues, I would also not be able to pass a sorted mongo cursor to my {#each} spacebars block expression and let it live update as the database changed. (I'm using the Meteor full-stack javascript framework.)
I know that everything has it's advantages and disadvantages, and I might just have to use one of the options listed above, but I'd like to know if there is a better way to do things.
Based on your requirement, one of the approaches could be to design your schema, in such a way that each document has the capability to hold more than one document and in itself act as a capped container.
{
"_id":Number,
"doc":Array
}
Each document in the collection will act as a capped container, and the documents will be stored as array in the doc field. The doc field being an array, will maintain the order of insertion.
You can limit the number of documents to n. So the _id field of each container document will be incremental by n, indicating the number of documents a container document can hold.
By doing these you avoid adding extra fields to the document, extra indices, unnecessary sorts.
Inserting the very first record
i.e when the collection is empty.
var record = {"name" : "first"};
db.col.insert({"_id":0,"doc":[record]});
Inserting subsequent records
Identify the last container document's _id, and the number of
documents it holds.
If the number of documents it holds is less than n, then update the
container document with the new document, else create a new container
document.
Say, that each container document can hold 5 documents at most,and we want to insert a new document.
var record = {"name" : "newlyAdded"};
// using aggregation, get the _id of the last inserted container, and the
// number of record it currently holds.
db.col.aggregate( [ {
$group : {
"_id" : null,
"max" : {
$max : "$_id"
},
"lastDocSize" : {
$last : "$doc"
}
}
}, {
$project : {
"currentMaxId" : "$max",
"capSize" : {
$size : "$lastDocSize"
},
"_id" : 0
}
// once obtained, check if you need to update the last container or
// create a new container and insert the document in it.
} ]).forEach( function(check) {
if (check.capSize < 5) {
print("updating");
// UPDATE
db.col.update( {
"_id" : check.currentMaxId
}, {
$push : {
"doc" : record
}
});
} else {
print("inserting");
//insert
db.col.insert( {
"_id" : check.currentMaxId + 5,
"doc" : [ record ]
});
}
})
Note that the aggregation, runs on the server side and is very efficient, also note that the aggregation would return you a document rather than a cursor in versions previous to 2.6. So you would need to modify the above code to just select from a single document rather than iterating a cursor.
Inserting a new document in between documents
Now, if you would like to insert a new document between documents 1 and 2, we know that the document should fall inside the container with _id=0 and should be placed in the second position in the doc array of that container.
so, we make use of the $each and $position operators for inserting into specific positions.
var record = {"name" : "insertInMiddle"};
db.col.update(
{
"_id" : 0
}, {
$push : {
"doc" : {
$each : [record],
$position : 1
}
}
}
);
Handling Over Flow
Now, we need to take care of documents overflowing in each container, say we insert a new document in between, in container with _id=0. If the container already has 5 documents, we need to move the last document to the next container and do so till all the containers hold documents within their capacity, if required at last we need to create a container to hold the overflowing documents.
This complex operation should be done on the server side. To handle this, we can create a script such as the one below and register it with mongodb.
db.system.js.save( {
"_id" : "handleOverFlow",
"value" : function handleOverFlow(id) {
var currDocArr = db.col.find( {
"_id" : id
})[0].doc;
print(currDocArr);
var count = currDocArr.length;
var nextColId = id + 5;
// check if the collection size has exceeded
if (count <= 5)
return;
else {
// need to take the last doc and push it to the next capped
// container's array
print("updating collection: " + id);
var record = currDocArr.splice(currDocArr.length - 1, 1);
// update the next collection
db.col.update( {
"_id" : nextColId
}, {
$push : {
"doc" : {
$each : record,
$position : 0
}
}
});
// remove from original collection
db.col.update( {
"_id" : id
}, {
"doc" : currDocArr
});
// check overflow for the subsequent containers, recursively.
handleOverFlow(nextColId);
}
}
So that after every insertion in between , we can invoke this function by passing the container id, handleOverFlow(containerId).
Fetching all the records in order
Just use the $unwind operator in the aggregate pipeline.
db.col.aggregate([{$unwind:"$doc"},{$project:{"_id":0,"doc":1}}]);
Re-Ordering Documents
You can store each document in a capped container with an "_id" field:
.."doc":[{"_id":0,","name":"xyz",...}..]..
Get hold of the "doc" array of the capped container of which you want
to reorder items.
var docArray = db.col.find({"_id":0})[0];
Update their ids so that after sorting the order of the item will change.
Sort the array based on their _ids.
docArray.sort( function(a, b) {
return a._id - b._id;
});
update the capped container back, with the new doc array.
But then again, everything boils down to which approach is feasible and suits your requirement best.
Coming to your questions:
What's a good way to store a set of documents in MongoDB where order is important?I need to easily insert documents at an arbitrary
position and possibly reorder them later.
Documents as Arrays.
Say I want to insert something between an element with a sequence of 5 and an element with a sequence of 6?
use the $each and $position operators in the db.collection.update() function as depicted in my answer.
My limited understanding of Database Administration tells me that a
query like that would be slow and generally a bad idea, but I'm happy
to be corrected.
Yes. It would impact the performance, unless the collection has very less data.
I could use a capped collection, which has a guaranteed order, but then I'd run into issues if I needed to grow the collection. (Yet
again, I might be wrong about that one too.)
Yes. With Capped Collections, you may lose data.
An _id field in MongoDB is a unique, indexed key similar to a primary key in relational databases. If there is an inherent order in your documents, ideally you should be able to associate a unique key to each document, with the key value reflecting the order. So while preparing your document for insertion, explicitly add an _id field as this key (if you do not, mongo creates it automatically with a BSON objectid).
As far as retrieving the results are concerned, MongoDB does not guarantee the order of return documents unless you explicitly use .sort() . If you do not use .sort(), the results are usually returned in natural order (order of insertion).Again, there is no guarantee on this behavior.
I'd advise you to override _id with your order while inserting, and use a sort while retrieving. Since _id is a necessary and auto-indexed entity, you will not be wasting any space defining a sort key, and storing the index for it.
For abitrary sorting of any collection, you'll need a field to sort it on. I call mine "sequence".
schema:
{
_id: ObjectID,
sequence: Number,
...
}
db.items.ensureIndex({sequence:1});
db.items.find().sort({sequence:1})
Here is a link to some general sorting database answers that may be relevant:
https://softwareengineering.stackexchange.com/questions/195308/storing-a-re-orderable-list-in-a-database/369754
I suggest going with Floating point solution - adding a position column:
Use a floating-point number for the position column.
You can then reorder the list changing only the position column in the "moved" row.
If your user wants to position "red" after "blue" but before "yellow" Then you just need to calculate
red.position = ((yellow.position - blue.position) / 2) + blue.position
After a few re-positions in the same place (Cuttin in half every time) - you might reach a wall - it's better that if you reach a certain threshold - to resort the list.
When retrieving it you can simply say col.sort() to get it sorted and no need for any client-side code (Like in the case of a Linked list solution)
I'm considering bundling time-sequence data together in session documents. Inside each session, there would be an array of events. Each event would have a timestamp. I know that I can create a multikey index on the timestamp of those events, but I'm curious what mechanism MongoDB uses to prevent the same document from showing up twice in one query.
To clarify, imagine a collection of sessions with the following documents:
{
_id: 'A',
events: [
{time: '10:00'},
{time: '15:00'}
]
}
{
_id: 'B',
events: [
{time: '12:00'}
]
}
If I add a multikey index with db.sessions.ensureIndex({'events.time' : 1}), I would expect the b-tree of that index to look like this:
'10:00' => 'A'
'12:00' => 'B'
'15:00' => 'A'
If I query the collection with {'events.time': {$gte: '10:00'}}, MongoDB scans the b-tree and returns:
{ "_id" : "A", "events" : [ { "time" : "10:00" }, { "time" : "15:00" } ] }
{ "_id" : "B", "events" : [ { "time" : "12:00" } ] }
How does Mongo prevent document A from showing up a second time as the third result in the cursor? For small index scans, it could just keep track of which documents had already been seen, but what happens if the index is enormous? Is there ever a case where the same document would show up more than once in a singe cursor?
My assumption is that it would not. Mongo could look at the document it is scanning and detect that it already would have matched earlier in the scan by inspecting earlier entries in the indexed array. However, I cannot find any mention of this behavior in the MongoDB documentation, and it is important to actually know what to expect.
(NOTE: I do know that it is possible for a document to show up in a single query more than once if the document is modified while the cursor is being scanned. That shouldn't pose a problem for queries on time-sequence data where timestamps are never edited. Even if a new event is added to a session during a scan, if Mongo uses something like the detection mechanism I mentioned above, it should be able to omit the moved document from query results.)
I cannot find any mention of this behavior in the MongoDB
documentation, and it is important to actually know what to expect.
Internals of implementation are seldom mentioned in the documentation, and after all, what you describe is the expected behavior.
There is code to deduplicate a result set and there are tests to make sure that it's working correctly. After all, a multi-key index isn't the primary use case for such functionality - if you have an $or clause in your query, the results must be de-duplicated as well.
I need help incrementing value of all keys in participants without having to know name of the keys inside of it.
> db.conversations.findOne()
{
"_id" : ObjectId("4faf74b238ba278704000000"),
"participants" : {
"4f81eab338ba27c011000001" : NumberLong(2),
"4f78497938ba27bf11000002" : NumberLong(2)
}
}
I've tried with something like
$mongodb->conversations->update(array('_id' => new \MongoId($objectId)), array('$inc' => array('participants' => 1)));
to no avail...
You need to redesign your schema. It is never a good idea to have "random key names". Even though MongoDB is schemaless, it still means you need to have defined key names. You should change your schema to:
{
"_id" : ObjectId("4faf74b238ba278704000000"),
"participants" : [
{ _id: "4f81eab338ba27c011000001", count: NumberLong(2) },
{ _id: "4f78497938ba27bf11000002", count: NumberLong(2) }
]
}
Sadly, even with that, you can't update all embedded counts in one command. There is currently an open feature request for that: https://jira.mongodb.org/browse/SERVER-1243
In order to still update everything, you should:
query the document
update all the counts on the client side
store the document again
In order to prevent race conditions with that, have a look at "Compare and Swap" and following paragraphs.
It is not possible to update all nested elements in one single move in current version of MongoDB. So I can advice to use "foreach {}".
Read realted topic: How to Update Multiple Array Elements in mongodb
I hope this feature will be implemented in next version.