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March 18, 2014

In Meteor 0.7, we reworked how Meteor gets real-time database updates from MongoDB.

The key method that Meteor adds to the MongoDB API which makes it into a real-time database API is cursor.observeChanges. observeChanges run an arbitrary MongoDB query, returns its results via added callbacks, and then continues to watch the query and calls additional callbacks as its results change.

Most users don't use observeChanges directly, but whenever you return a cursor from a publish function, Meteor calls observeChanges on that cursor and provides it with callbacks which publish the query's changes to clients.

Previous versions of Meteor only had one strategy for implementing observeChanges: the "poll-and-diff" algorithm, implemented by the PollingObserveDriver class. This approach re-runs the query frequently and calculates the difference between each set of results. This code is simple and has historically contained very few bugs. But the cost of the PollingObserveDriver is proportional to the poll frequency and to the size of each query result, and the time from database change to callback invocation depends on whether the write originated in the same Meteor server process (very fast) or in another process (up to 10 seconds).

Starting with Meteor 0.7.0, Meteor can use an additional strategy to implemnt observeChanges: oplog tailing, implemented by the OplogObserveDriver class. Meteor now knows how to read the MongoDB "operations log" --- a special collection that records all the write operations as they are applied to your database. This means changes to the database can be instantly noticed and reflected in Meteor, whether they originated from Meteor or from an external database client. Oplog tailing has different performance characteristics than "poll-and-diff" which are superior in many cases.

OplogObserveDriver needs to understand the meaning of MongoDB selectors, field specifiers, modifiers, and sort specifiers at a much deeper level than PollingObserveDriver. This is because it actually needs to understand how write operations that it sees in the oplog interact with queries, instead of just relying on the MongoDB server to repeatedly execute the query. To deal with these structures, OplogObserveDriver uses Meteor's implementation of the MongoDB query engine, Minimongo, which Meteor also uses as its client-side local database cache.

As of Meteor 0.7.2, we use OplogObserveDriver for most queries. There are a few types of queries that still use PollingObserveDriver:

  • Selectors containing geospatial operators, the $where operator, or any operator not supported by Minimongo (such as $text)
  • Queries specifying the skip option
  • Queries specifying the limit option without a sort specifier or with a sort based on $natural order
  • Field specifiers and sort specifiers with $ operators such as $slice or $natural
  • Calls to observeChanges using "ordered" callbacks addedBefore and movedBefore. (The implicit call to observeChanges which occurs when you return a cursor from a publish function does not use the ordered callbacks.)

Oplog tailing is automatically enabled in development mode with meteor run, and can be enabled in production with the MONGO_OPLOG_URL environment variable.

OplogObserveDriver in production

To use oplog tailing in your production Meteor app, your MongoDB servers must be configured as a replica set; a single-mongod database has no oplog. Your cluster may not use Mongo sharding.

Once you have set up your replica set, you need to provide read access to the oplog to a user; we recommend creating a special user (say, oplogger) that is used only for this purpose. Note that the oplog is shared between all databases served by your replica set of mongod processes; if you are sharing your cluster with unrelated apps, the oplogger user will be able to see all changes to all databases in your cluster. You will need Mongo administrator credentials to create this user.

Log in to the admin database with the Mongo shell using your administrator credentials. (You must connect to the current primary in your replica set; if the prompt says SECONDARY instead of PRIMARY, type db.isMaster() in the mongo shell and try again connecting to the server listed under primary.)

$ mongo -u YourExistingAdminUserName -p YourExistingAdminPassword

Now run the following command to make an oplogger user with the ability to read collections in the local database.

If you are using Mongo 2.6 (though see the "Note for Mongo 2.6 users" below if you are running Meteor or earlier):

cluster:PRIMARY> db.createUser({user: "oplogger", pwd: "PasswordForOplogger", roles: [{role: "read", db: "local"}]})

If you are using Mongo 2.4:

cluster:PRIMARY> db.addUser({user: "oplogger", pwd: "PasswordForOplogger", roles: [], otherDBRoles: {local: ["read"]}})

Then, when running your bundled Meteor app, set the MONGO_OPLOG_URL environment variable:


(You can find the name of your replica set by running rs.config()._id in the mongo console).

(You may be used to running db.createUser (or db.addUser) inside the actual database that you want the new user to be able to access (in this case, local), instead of running it in admin and using the authSource flag to specify that you want to authenticate against admin. However, this doesn't work with the special case of the local database. Mongo 2.6 specifically prevents you from creating users in the local database, and while Mongo 2.4 would let you do it, you would find that you need to run db.addUser separately against each database replica (and risking ending up with different passwords on each), because the local database is not itself replicated across servers.)

(Note for Mongo 2.6 users: releases of Meteor prior to 1.0.4 were not tested with Mongo 2.6, and you will need to set up a custom user-defined role that can access the system.replset collection in order to use these versions of Meteor with Mongo 2.6. See this comment by @rwillmer for instructions. Meteor 1.0.4 does not require special permissions on system.replset and the simpler createUser call above will work.)

OplogObserveDriver is currently not supported for apps deployed with meteor deploy. Galaxy (the in-progress replacement for the meteor deploy servers which currently hosts some of Meteor Development Group's sites) will support OplogObserveDriver.

OplogObserveDriver during development

Starting with Meteor 0.7.0, whenever you run your local development server, the meteor tool will set up your local development database as a single-member replica set and automatically enable OplogObserveDriver.

Our goal is for OplogObserveDriver to be indistinguishable from PollingObserveDriver (except that it should notice database changes faster). However, if you do find a bug in OplogObserveDriver that affects your app's development, then (after reporting it), you can disable OplogObserveDriver as a workaround.

There are several ways to do so. For a specific query, you can specify the undocumented option _disableOplog to the find call:

Meteor.publish("comments", function (postId) {
  return Comments.find({post: postId}, {_disableOplog: true, fields: {secret: 0}});

Or to entirely disable OplogObserveDriver for your app, run $ meteor add disable-oplog. (And please let us know why!)

When running Meteor's internal tests with meteor test-packages, pass the --disable-oplog flag to disable OplogObserveDriver. (We do this during our pre-release QA process, to ensure that our tests pass with both observe drivers.)

How to tell if your queries are using OplogObserveDriver

For now, we only have a crude way to tell how many observeChanges calls are using OplogObserveDriver, and not which calls they are.

This uses the facts package, an internal Meteor package that exposes real-time metrics for the current Meteor server. In your app, run $ meteor add facts, and add the {{> serverFacts}} template to your app. If you are using the autopublish package, Meteor will automatically publish all metrics to all users. If you are not using autopublish, you will have to tell Meteor which users can see your metrics by calling Facts.setUserIdFilter in server code; for example:

Facts.setUserIdFilter(function (userId) {
  var user = Meteor.users.findOne(userId);
  return user && user.admin;

(When running your app locally, Facts.setUserIdFilter(function () { return true; }); may be good enough!)

Now look at your app. The facts template will render a variety of metrics; the ones we're looking for are observe-drivers-oplog and observe-drivers-polling in the mongo-livedata section. If observe-drivers-polling is zero or not rendered at all, then all of your observeChanges calls are using OplogObserveDriver!