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Friday
Jan022009

Strategy: Understanding Your Data Leads to the Best Scalability Solutions

In article Building Super-Scalable Web Systems with REST Udi Dahan tells an interesting story of how they made a weather reporting system scale for over 10 million users. So many users hitting their weather database didn't scale. Caching in a straightforward way wouldn't work because weather is obviously local. Caching all local reports would bring the entire database into memory, which would work for some companies, but wasn't cost efficient for them.

So in typical REST fashion they turned locations into URIs. For example: http://weather.myclient.com/UK/London. This allows the weather information to be cached by intermediaries instead of hitting their servers. Hopefully for each location their servers will be hit a few times and then the caches will be hit until expiry.


In order to send users directly to the correct location an IP location check is performed on login and stored in a cookie. The lookup is done once and from then on out a GET is performed directly on the resource. There's no need to hit their servers and do a lookup on the user to get the location. That's all bypassed.

I like Udi's summary of the approach and is why I think this is a good strategy : This isn’t a “cheap trick”. While being straight forward for something like weather, understanding the nature of your data and intelligently mapping that to a URI space is critical to building a scalable system, and reaping the benefits of REST.

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