I am using a MongoDB cursor to find a large number of documents, which takes quite some time. What happens if during this time, there are documents added to the database that match the search criteria of the cursor.
Will the cursor return the documents?
Or does the cursor take some kind of snapshot if it begins, and thus omits the later added results?
Will the cursor return the documents?
Yes. This also happens when you update some documents which you received from the cursor, causing them to grow out of their current disk bounds and move to a bigger slot in the data files. In this case, you may see such documents twice (or more).
We are troubled by eventually occurring cursor not found exceptions for some Morphia Queries asList and I've found a hint on SO, that this might be quite memory consumptive.
Now I'd like to know a bit more about the background: can sombody explain (in English), what a Cursor (in MongoDB) actually is? Why can it kept open or be not found?
The documentation defines a cursor as:
A pointer to the result set of a query. Clients can iterate through a cursor to retrieve results. By default, cursors timeout after 10 minutes of inactivity
But this is not very telling. Maybe it could be helpful to define a batch for query results, because the documentation also states:
The MongoDB server returns the query results in batches. Batch size will not exceed the maximum BSON document size. For most queries, the first batch returns 101 documents or just enough documents to exceed 1 megabyte. Subsequent batch size is 4 megabytes. [...] For queries that include a sort operation without an index, the server must load all the documents in memory to perform the sort before returning any results.
Note: in our queries in question we don't use sort statements at all, but also no limit and offset.
Here's a comparison between toArray() and cursors after a find() in the Node.js MongoDB driver. Common code:
var MongoClient = require('mongodb').MongoClient,
assert = require('assert');
MongoClient.connect('mongodb://localhost:27017/crunchbase', function (err, db) {
assert.equal(err, null);
console.log('Successfully connected to MongoDB.');
const query = { category_code: "biotech" };
// toArray() vs. cursor code goes here
});
Here's the toArray() code that goes in the section above.
db.collection('companies').find(query).toArray(function (err, docs) {
assert.equal(err, null);
assert.notEqual(docs.length, 0);
docs.forEach(doc => {
console.log(`${doc.name} is a ${doc.category_code} company.`);
});
db.close();
});
Per the documentation,
The caller is responsible for making sure that there
is enough memory to store the results.
Here's the cursor-based approach, using the cursor.forEach() method:
const cursor = db.collection('companies').find(query);
cursor.forEach(
function (doc) {
console.log(`${doc.name} is a ${doc.category_code} company.`);
},
function (err) {
assert.equal(err, null);
return db.close();
}
);
});
With the forEach() approach, instead of fetching all data in memory, we're streaming the data to our application. find() creates a cursor immediately because it doesn't actually make a request to the database until we try to use some of the documents it will provide. The point of cursor is to describe our query. The second parameter to cursor.forEach shows what to do when an error occurs.
In the initial version of the above code, it was toArray() which forced the database call. It meant we needed ALL the documents and wanted them to be in an array.
Note that MongoDB returns data in batches. The image below shows requests from cursors (from application) to MongoDB:
forEach scales better than toArray because we can process documents as they come in until we reach the end. Contrast it with toArray - where we wait for ALL the documents to be retrieved and the entire array is built. This means we're not getting any advantage from the fact that the driver and the database system are working together to batch results to your application. Batching is meant to provide efficiency in terms of memory overhead and the execution time. Take advantage of it in your application, if you can.
I am by no mean a mongodb expert but I just want to add some observations from working in a medium sized mongo system for the last year. Also thanks to #xameeramir for the excellent walkthough about how cursors work in general.
The causes of a "cursor lost" exception may be several. One that I have noticed is explained in this answer.
The cursor lives server side. It is not distributed over a replica set but exists on the instance that is primary at the time of creation. This means that if another instance takes over as primary the cursor will be lost to the client. If the old primary is still up and around it may still be there but for no use. I guess it is garbaged collected away after a while. So if your mongo replica set is unstable or you have a shaky network in front of it you are out of luck when doing any long running queries.
If the full content of what the cursor wants to return does not fit in memory on the server the query may be very slow. RAM on your servers needs to be larger than the largest query you run.
All this can partly be avoided by designing better. For a use case with large long running queries you may be better of with several smaller database collections instead of a big one.
The collection's find method returns a cursor - this points to the set of documents (called as result set) that are matched to the query filter. The result set is the actual documents that are returned by the query, but this is on the database server.
To the client program, for example the mongo shell, you get a cursor. You can think the cursor is like an API or a program to work with the result set. The cursor has many methods which can be run to perform some actions on the result set. Some of the methods affect the result set data and some provide the status or info about the result set.
As the cursor maintains information about the result set, some information can change as you use the result set data by applying other cursor methods. You use these methods and information to suit your application, i.e., how and what you want to do with the queried data.
Working on the result set using the cursor and some of its commonly used methods and features from mongo shell:
The count() method returns the count of the number of documents in the result set, initially - as the result of the query. It is always constant at any point in the life of the cursor. This is information. This information remains same even after the cursor is closed or exhausted.
As you read documents from the result set, the result set gets exhausted. Once completely exhausted you cannot read any more. The hasNext() tells if there are any documents available to be read - returns a boolean true or false. The next() returns a document if available (you first check with hasNext, and then do a next). These two methods are commonly used to iterate over the result set data. Another iteration method is the forEach().
The data is retrieved from the server in batches - which has a default size. With the first batch you read the documents and when all it's documents are read, the following next() method retrieves the next batch of documents, etc., until all documents are read from the result set. This batch size can be configured and you can also get its status.
If you apply the toArray() method on the cursor, then all the remaining documents in the result set are loaded into the memory of your client computer and are available as a JavaScript array. And, the result set data is exhausted. The following hasNext method will return false, and the next will throw an error (once you exhaust the cursor, you cannot read data from it). This method loads all the result set data into your client's memory (the array). This can be memory consuming in case of large result sets.
The itcount() returns the count of remaining documents in the result set and exhausts the cursor.
There are cursor methods like isClosed(), isExhausted(), size() which give status information about the cursor and its underlying result set as you work with your data.
Those are the basic features of cursor and result set. There are many cursor methods, and you can try and see how they work and get a better understanding.
Reference:
mongo shell's cursor
methods
Cursor behavior with Aggregate
method
(the collection's aggregate method also returns a cursor)
Example usage in mongo shell:
Assume the test collection has 200 documents (run the commands in the same sequence).
var cur = db.test.find( { } ).limit(25) creates a result set with 25
documents only.
But, cur.count() will show 200, which is the actual count of
documents by the query's filter.
hasNext() will return true.
next() will return a document.
itcount() will return 24 (and exhausts the cursor).
itcount() again will return 0.
cur.count() will still show 200.
This error also comes when you have a large set of data and are doing batch processing on that data and each batch takes more time, totalling that time be exceeded the default cursor live time.
Then you need to change that default time to tell mongo that will not expire this cursor until processing is done.
Do check No TimeOut Documentation
A cursor is an object returned by calling db.collection.find() and which enables iterating through documents (NoSQL equivalent of a SQL "row") of a MongoDB collection (NoSQL equivalent of "table").
In case your cluster is stable and no members where down or changing state, the most posible reason for not finding the cursor is this:
Default idle cursor timeout is 10min , but in the versions >= 3.6 the cursor is also associated with session which is having default session timeout 30min , so even you set the cursor to not expire with the option noCursorTimeout() you are still limited by the session timeout of 30min. To avoid your cursor to be killed by the session timeout you will need to perioducally check in your code and execute sessionRefresh command:
db.adminCommand({"refreshSessions" : [sessionId]})
to extend the session with another 30min so your cursor to not be killed if you do something with the data before fetching the next batch...
check the docs here for detail how to do it:
https://docs.mongodb.com/manual/reference/method/cursor.noCursorTimeout/
Mongo docs talk about queries yielding locks to avoid blocking other operations. Will Mongo yield the lock from a read to a write that changes the read result?
Say I've got docs {x:1}, {x:2}, {x:2}, {x:1} and I'm reading find({x:2}). Assume the fourth doc isn't in the working set, so Mongo page faults, yielding the lock to an update({x:1}, {x:2}, {multi: true}), which completes and returns the lock to the find. The find would now include the fourth doc but omit the first doc. Does Monogo work like this?
In MongoDB there is no guarantee of query isolation - in fact, across multiple documents, you are not guaranteed to be looking at the same point in time.
What you describe can absolutely happen, and it does. The same is true of multi-document queries that fetch a large number of documents in batches (when you use a cursor). When you issue getmore for the next batch, the state of the data is not guaranteed to be the same as when you got the previous batch of results.
I am using MongoDB to save data about products. After writing the initial large data-set (24mio items) I would like to change all the items in the collection.
Therefore I use a cursor to iterate over the whole collection. Then I want to add a "row" or field to every item in the collection. With large data-sets this is not working. There were only 180000 items updated. On a small scale it is working. Is that normal behavior?
Is MongoDB not supposed to support writes while iterating with a cursor over the whole collection?
What would be a good practice to do that instead?
For larger collections, you might run into snapshotting problems. When you add data to the object and save it, it will grow, forcing mongodb to move the document around. Then you might find the object twice.
You can either use $snapshot in your query, or use a stable order such as sort({"_id":1}). Note that you can't use both.
Also make sure to use at least acknowledged write concern.
When we had a similar problem, we fetched data in 100k(with some test) chunks. It's a quick and simple solution.
In MongoDB, read operation on the collection returns cursor.
If the read operation is accessing most of the documents in the collection and it may be possible that it may interleave with other update operation.
In that case, may it be possible that cursor will have duplicate documents ?
How to make sure that cursor will avoid duplicates ?
The distinct method will not be of much help here. This is not a problem that the function can solve, not only that but it is a fraction of the speed of a normal cursor.
If the read operation is accessing most of the documents in the collection and it may be possible that it may interleave with other update operation.
It is possible if the documents move in such a manner that with the sort of the cursor they get read again.
Whether this is a problem or not depends, if you are sorting by something that won't be updated, for example _id, then you don't really need to worry, however, if you are sorting by something that will be updated and could shift then yes; you will have a problem.
One method of solving this is to look at the last _id in that iteration of the cursor, filling the cursor into batchs of 1000 in an array or something. After you have the last _id in that batch you range, taking everything greater than that _id.
Another method could be to do snapshot queries: http://docs.mongodb.org/manual/reference/operator/snapshot/ however this function has quite a few limitations, for example it cannot be used with sharded collections.