I'm developing a stream with webflux from a mongodb collection with spring boot and spring data mongodb with tailable cursors.
The stream is working when the collection has 1 document or more due to you can get the cursor. The issue is that I want to open the stream with an empty collection, since I want to stream every document in the collection.
I've been reading the docs and it's supposed to be correct:
https://docs.spring.io/spring-data/mongodb/docs/current/reference/html/#tailable-cursors
Tailable cursors may become dead, or invalid, if either the query returns no match or the cursor returns the document at the “end” of the collection and the application then deletes that document
I'm evaluating the best way to achieve this (open the stream from an empty collection) with spring boot and flux but I would rather to know if there is some idea or workaround.
Thank you.
Indeed, even "find all" on empty capped collections is considered as no match and the cursor is dead.
reactiveMongoOperations.tail(new Query(), Event.class) returns a dead cursor, so does the annotated repository flavor.
Spring docs just duplicate mongo docs, which state
Tailable cursors may become dead, or invalid, if either:
the query returns no match.
the cursor returns the document at the “end” of the collection and then the application > deletes that document.
Only workaround seems to be an initial dummy entry inserted prior subscription.
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/
I have no knowledge of mongodb and I just want to ask if something is possible and, if possible, how it can be done. My question is how can we know when a cursor will expire. Is there any API for this purpose?
I would be grateful for any comments and recommendations.
Best regards.
From the MongoDB documentation:
By default, MongoDB will automatically close a cursor when the client has exhausted all results in the cursor. However, for capped collections you may use a Tailable Cursor that remains open after the client exhausts the results in the initial cursor.
http://docs.mongodb.org/manual/tutorial/create-tailable-cursor/
Other factors which could cause a cursor to expire are the batchSize and timeout. To sum it up factors which expire the cursor are:
result exhausation
batchSize: http://docs.mongodb.org/manual/reference/method/cursor.batchSize/
timeout: http://api.mongodb.org/java/2.6/com/mongodb/MongoOptions.html
I came across this thread looking for a solution to the following error in with pymongo: CursorNotFound: Cursor not found, cursor id. Obviously the reason is the same as this thread, but there is no solution provided for pymongo.
From the FAQ in the pymongo documentation the following links answer the question: here and here.
The quickest solution is to disable the timeout, so the server does not expire the cursor, and it's always valid.
client = MongoClient("localhost")
db = client.testdatabase
cursor = db.testcollection.find({}, no_cursor_timeout=True)
In the find() documentation you can find alternatives by changing the cursor type:
cursor_type (optional): the type of cursor to return. The valid
options are defined by CursorType:
NON_TAILABLE - the result of this find call will return a standard cursor over the result set.
TAILABLE - the result of this find call will be a tailable cursor - tailable cursors are only for use with capped collections. They are not closed when the last data is retrieved but are kept open and the
cursor location marks the final document position. If more data is
received iteration of the cursor will continue from the last document
received. For details, see the tailable cursor documentation.
TAILABLE_AWAIT - the result of this find call will be a tailable cursor with the await flag set. The server will wait for a few seconds
after returning the full result set so that it can capture and return
additional data added during the query.
EXHAUST - the result of this find call will be an exhaust cursor. MongoDB will stream batched results to the client without waiting for
the client to request each batch, reducing latency. See notes on
compatibility below.
Update: After using the no_cursor_timeout I was wondering what happeneded to the cursor when they are not executed. Here is the answer: PyMongo: What happens to cursor when no_cursor_timeout=True
Ordinarily, a cursor "dies" on the database server after a certain length of time (approximately 10 minutes) and will be closed when the client has exhausted all of the results.
Some drivers have an "immortal" option, which does the equivalent in the Java driver of setting a NoTimeout option:
dbcoll.find(...).addOption(Bytes.QUERYOPTION_NOTIMEOUT)
Set in a manner like above if you intend to keep an open cursor over this period of time.
http://api.mongodb.org/java/current/com/mongodb/Bytes.html#QUERYOPTION_NOTIMEOUT
Is there someway where if I want to read some data from the database with certain constraints that instead of waiting to get all the results at once, the database can start "streaming" it's results to me.
Think of a large list.
Instead of making users wait for the entire list, I want to start filling is data quickly, even if I only get one row at a time.
I only know of MongoDB with limit(x) and skip(y).
Any way to get the streaming result from any database? I want to know for curiosity, and for a project I'm currently thinking about.
here's example of python connection to mongodb and getting data line by line
from pymongo import MongoClient
client = MongoClient()
db = client.blog
col = db.posts
for r in col.find():
print r
raw_input("press any key to continue...")
All standard MongoDB drivers return a cursor on queries (find() command), which allows your application to stream the documents by using the cursor to pull back the results on demand. I would check out the documentation on cursors for the specific driver that you're planning to use as syntax varies between different programming languages.
There's also a special type of cursor specific for certain streaming use cases. MongoDB has a concept of a "Tailable Cursor," which will stream documents to the client as documents are inserted into a collection (also see AWAIT_DATA option). Note that Tailable cursors only work on "capped collections" as they've been optimized for this special usage. Documentation can be found on the www.mongodb.org site. Below is a link to some code samples for tailable cursors:
http://docs.mongodb.org/manual/tutorial/create-tailable-cursor/
I would like to create an endless processing loop for capped collection directly in MongoDB, but I can't find how I can get tailabale cursor in MongoDB shell. It's possible in Python with tailable option in Collection.find() though..
You can add the option after find() using addOption():
db.coll.find().addOption(2) // probably want to use 2(tailable) + 32(await_data)
See all the options here: http://www.mongodb.org/display/DOCS/Mongo+Wire+Protocol#MongoWireProtocol-OPQUERY
You will want to put this in a loop as even tailable cursors (w/await_data) return no results sometimes.