I’m having oplog scaling issues. Every 10 minutes I have a lot of mongodb updates and server cpu spikes. I can’t find much info about what to do about it. I remember seeing some slides from a talk but can’t find them. Anyone have links to info about what people have done to get around too many updates to the oplog.
It’s like before my updates I want to turn off oplog tailing for certain collections then when the updates are done poll to catch up the resume oplog tailing. I saw that 1.3 has options to make a publish function poll instead of oplog tail but it doesn’t look like it’s possible to change that while the app is running.
When there are a large number of updates to the DB the meteor app falls back to polling. This is because oplog tailing is flooding the meteor app which in extreme cases can crash the app. To reduce the CPU spikes you can try to set METEOR_OPLOG_TOO_FAR_BEHIND to a much smaller value but apparently that does not always work.
The other option is to move any collections that requires a large number of batch updates into a separate DB instance, but if you do that you will lose the ability to run reactive queries.
mz103 what happened is that just after I posted that, I found Meteor 1.3 parameter disableOplog. I went into my application and selectively applied that to all find functions for the high-insert collection, particularly those instructions in Meteor.publish functions. I’ve been doing some testing, and it is working as advertised. There is still a small CPU spike on the front end Node.js server on the batch insert function, but it is tiny by comparison with what was happening before.
So my deleted post was asking for a robust solution, and in my case it appears that disableOplog is delivers that solution. It allowed me to keep the OPLOG tailing on.