Mongo Map Reduce Vs. Query

Just had something come up today where I had to take a bunch of users from an existing collection and put some of their data in a new collection with new IDs. Here are two approaches that do the same thing, with wildly different speeds.


Map reduce is way faster than looping over a really fast query for this kind of work!

	// map reduce way is slow for querying a count, but fast for creating a new table (~20s)
	map = function() {
	if (this.alerts && this.alerts.length > 0 && this.apns) {
	emit(new ObjectId(), {alerts: this.alerts, uuid: this.uuid, hiddenChannels: this.hiddenChannels, provider: this.provider})
	}
	}
	reduce = function(){}
	options = {out:{replace:"alertingUsers"}}
	db.users.mapReduce(map, reduce, options)
	db.alertingUsers.count() // 34554
	// really fast queries / counts (~1s)
	db.users.count({alerts:{$exists:true, $not: { $size: 0 }}, apns:{$exists:true}}) // 34554
	// but makes for really slow inserts (~5 minutes)
	db.users.find({alerts:{$exists:true, $not: { $size: 0 }}, apns:{$exists:true}}, {hiddenChannels: 1, apns: 1, _id: 0, alerts: 1, uuid: 1, provider: 1}).forEach(function(user) {
	db.alertingUsersSlow.insert(user)
	})
	db.alertingUsersSlow.count() // 34554

view raw mongo-map-reduce-speed-test.js hosted with ❤ by GitHub