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2

The default balancing window is 24x7x365, which means balancer will always move chunks if its on


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Config servers are a special case, you can use one (for testing), or three and that's it. They are not a replica set, at least not yet, that might change in the future, see SERVER-1448. Go and (re)read the first two paragraphs here - note the piece about them not being a replica set is explicitly mentioned. I will pick out some other relevant points: ...


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Since there is already and answer submitted, and a useful and valid one at that, I do not want to distract from it's own usefulness but there are indeed points to raise that go way beyond just a short comment. So consider this "augmentation", which is hopefully valid but primarily in addition to what has already been said. The truth is to really consider ...


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Since best practice also suggest that "The appropriate number of mongos processes will depend on the nature of the application and deployment" I started to wonder whether our usage of mongos actually appropriate I think this is a question that ultimately only you can answer, as the documentation refers to. One of the recommended strategies is to ...


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Compound indexes are great for static values Flip the WHERE components so that static values are first db.data.find( { c:"test", d:"yes", a: {$gte:1,$lt:2}, b: {$gt: 3} }).sort( { b: 1 } ) Create a different compound index db.data.ensureIndex({c:1},{d:1},{b:1},{a:1}) How does it help ? Static c value Static d value Sorted Range on b One more thing ...


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First question: You can't if you are not running on a replica set. On a replica set you may follow that guide http://docs.mongodb.org/manual/tutorial/build-indexes-on-replica-sets/. Indexes are persistent, upon an index is created it doesn't rebuild on start-up unless something trigger it (maybe your application?) Second question: I don't see any index ...


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It just means that this is a sharded cluster and the aggregation is happening via a mongos (also known as a query router). This is important for aggregations internally because it means that the output from multiple shards may need to be merged but it's not really relevant for most end users (you usually already know you are running in a sharded ...


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You have basically allocated space by defining two capped collections, the oplog and the second capped collection in MyDatabase. Unless you specify the oplogSize, the oplog will be allocated at 5% of free space on the volume containing the MongoDB data (so I am guessing you had ~170GB free). The second capped collection size would have been defined by you, ...


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One reason could be that your oplog is too small. On the master: db.getReplicationInfo() If timeDiffHours is shorter than the time that your initial sync takes, then the initial sync will fail and start again... Resizing the oplog is quite easy, if this is indeed your problem. The documentation is here: ...



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