MongoDB規模化的設計模式

I had the recent opportunity to present a talk at MongoDB Seattle on Schema Design at Scale. It's basically a short case study on what steps the MongoDB Monitoring Service (MMS) folks did to evolve their schema, along with some quantitative performance comparisons between different schemas. Given that one of my most widely read blog posts is still MongoDB's Write Lock, I decided that my blog readers would also be interested in the quantitative comparison as well.

MongoDB Monitoring Service

First off, I should mention that I am not now, nor have I ever been, an employee of 10gen, the company behind MongoDB. I am, however, a longtime MongoDB user, and have seen a lot of presentations and use cases on the database. My knowledge of MMS's internal design comes from watching publicly available talks. I don't have any inside knowledge or precise performance numbers, so I decided to do some experiments on my own to see the impact of different schema designs they might have used to build MMS.


So what is MMS, anyway? The MongoDB Monitoring Service is a free service offered by 10gen to all MongoDB users to monitor several key performance indicators on their MongoDB installations. The way it works is this:

1. You download a small script. that you run on your own servers that will periodically upload performance statistics to MMS.

2. You access reports through the MMS website. You can graph per-minute performance of any of the metrics as well as see historical trends.

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