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09-Jun-2019 21:45 by 8 Comments

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The method we chose to get text from one user to another involves loading an iframe on each Facebook page, and having that iframe's Javascript make an HTTP GET request over a persistent connection that doesn't return until the server has data for the client.The request gets reestablished if it's interrupted or times out.

Despite those advantages, using Erlang for a component of Facebook Chat had a downside: that component needed to communicate with the other parts of the system.Note that approach (a) changes the sending a chat message / loading a Facebook page from a one-to-one communication into a multicast to all online friends, while approach (b) ensures that users who are neither chatting nor browsing Facebook are nonetheless generating server load.Another challenge is ensuring the timely delivery of the messages themselves.Fault tolerance is a desirable characteristic of any big system: if an error happens, the system should try its best to recover without human intervention before giving up and informing the user.The results of inevitable programming bugs, hardware failures, et al., should be hidden from the user as much as possible and isolated from the rest of the system.The project I'm currently working on, Facebook Chat, offered a nice set of software engineering challenges: The most resource-intensive operation performed in a chat system is not sending messages.

It is rather keeping each online user aware of the online-idle-offline states of their friends, so that conversations can begin.Even without accounting for the sizeable overhead of spawning an OS process that, on average, twiddles its thumbs for a minute before reporting that no one has sent the user a message, the waiting time could be spent servicing 60-some requests for regular Facebook pages.The result of running out of Apache processes over the entire Facebook web tier is not pretty, nor is the dynamic configuration of the Apache process limits enjoyable.Having Thrift available freed us to split up the problem of building a chat system and use the best available tool to approach each sub-problem.The secret for going from zero to seventy million users overnight is to avoid doing it all in one fell swoop.One of the things I like most about working at Facebook is the ability to launch products that are (almost) immediately used by millions of people.

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