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Twitter Not Rocket Science, but Still a Work in Progress 111

While it may not be rocket science, the Twitter team has been making a concerted effort to effect better communication with their community at large. Recently they were set-upon by a barrage of technical and related questions and the resulting answers are actually somewhat interesting. "Before we share our answers, it's important to note one very big piece of information: We are currently taking a new approach to the way Twitter functions technically with the help of a recently enhanced staff of amazing systems engineers formerly of Google, IBM, and other high-profile technology companies added to our core team. Our answers below refer to how Twitter has worked historically--we know it is not correct and we're changing that."
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Twitter Not Rocket Science, but Still a Work in Progress

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  • by bsDaemon ( 87307 ) on Monday June 02, 2008 @04:19PM (#23630915)
    Man, who *IS* this guy that his trolling has gotten its own front page article?
    • Re: (Score:1, Funny)

      by nawcom ( 941663 )
      heh. as soon as i read the title I just had to see who got first post on it, and which insult they are going to use on twitter.
    • Re:twitter hate... (Score:5, Interesting)

      by Jeff DeMaagd ( 2015 ) on Monday June 02, 2008 @04:45PM (#23631251) Homepage Journal
      Dude, I'm not seeing the hate here. May be an eye of the beholder kind of thing.

      I do have two concerns about the service, apart from the supposed outages.

      One is that they don't seem to have any plan that can make money on their service. I suppose they are trying to build up a service that they can sell to Microsoft, Yahoo or Google, but how much of the user base is going to tolerate ads if any of them bought it as a platform to serve ads?

      Another is that they are very quick to cancel passwords due to inactivity, requiring a request to get it reset. I don't know if it's one week or one month, but it's as if they don't want you at all if you don't log in at least once a week. However often they do it, I've not seen any other service do it so quickly.
      • Re: (Score:2, Informative)

        It's a joke... []
      • Re: (Score:3, Funny)

        by bsDaemon ( 87307 )
        I was attempting to make a joke based on the fact that everyone seems to hate the user named "twitter" who allegedly has a vast army of fake accounts he uses to reply to himself and create little Socratic dialogs to solicit karma.

        of course, now its not funny anymore.
      • by niceone ( 992278 ) *
        Another is that they are very quick to cancel passwords due to inactivity

        Dude, if you can't be bothered to tell people what you had for breakfast each day maybe twitter's not for you.
      • >> One is that they don't seem to have any plan that can make money on their service

        Who cares when you've still got venture capital to burn through?
    • by rts008 ( 812749 ) on Monday June 02, 2008 @04:52PM (#23631355) Journal
      I have been confused about this also.
      I DO hang out at places other than /., but until all of the '/. twitter' troll posts, I had never even heard of the twitter weblog. I assumed they were connected somehow and totally dismissed the twitter weblog.

      Now that I have seen the twitter weblog, I'm still tempted mentally to associate the two, and want to spam it with links to somehow balance the shite. (just kidding-sort of)

      I could not get an answer from the twitter weblog about how many sock puppet accounts you could register though, so I guess I will pass on the whole thing, and attempt to just filter 'anything twitter' from my web experience, as any more in my mind twitter==mindless rant.

      And before some twitter (weblog) fanboy tries to bust my chops, yes I know I could be 'missing out on something' with that attitude, well that also goes for a million and one other websites that I currently don't know about. Save it!
      • Re: (Score:3, Funny)

        I thought that the Twitter product was a free roving troll for all weblogs and somebody had figured out a way to profit from it.

        So I went to the site and found I was correct. Its a AI-based troll that talks up products. Sadly there is a glitch where it also talks about toilet related obsessions.
        • Funny thing; I knew about the twitter blog before the twitter troll, and figured someone was using the twitter service to spam slashdot instead of uploading posts to the blog. Took me a while to figure out it was two different things.

          Then again, I guess someone could set up a twitter-like slashdot posting service....
  • Answers on a postcard please.

  • by Anonymous Coward
    Making 10 slashdot accounts is not rocket science.
    • Re: (Score:1, Funny)

      by Anonymous Coward
      ... says an AC.
  • by XanC ( 644172 ) on Monday June 02, 2008 @04:27PM (#23631003)
    This is one of those cases where "effect" is a verb.
  • Kinda surprised. I use neither Twitter nor Ruby, but seems like the talk has been than Rails wasn't scaling well. Thought the Q&A would confirm or deny this.
    • Re: (Score:1, Insightful)

      by Anonymous Coward

      I use neither Twitter nor Ruby, but seems like the talk has been than Rails wasn't scaling well.

      So you're basically flamebait. Rails might had been a factor, but this is not what it's about. It's not as easy as, rewrite it all in java or php and it will work blazing fast. Twitter needs to find a better way to reorganize or perhaps rewrite their code and it may still be in ruby as far I am concerned. Dare I also mention that their biggest overhead is not the rails framework, nor the ruby language, but their database, wich lead to their downtime in the first place. Nevertheless, big players such as IBM

    • by QuoteMstr ( 55051 ) <> on Monday June 02, 2008 @08:06PM (#23633195)
      Ruby is not Twitter's problem. The algorithm Twitter uses is the problem.

      When I started irately writing this post, I wrote it in a tone that would have gotten me modded into oblivion. But then I realized that ignorance, not idiocy, drives the particular myth I'm debunking. let me educate, not flame, those of you who haven't formally studied computer science.

      It's become fashionable to blame Ruby for Twitter's problems, but that's wrong. The particular choice of language doesn't matter a bit when you talk about scalability, no matter what the language or the problem.

      First, sending a twitter message is an algorithm. An algorithm is just a recipe for doing something to some data. Although most computer science literature deals with more abstract and general algorithms, like those for sorting and searching, the same principles applies to even the most mundane processes, like what rm foo does to a file system, or how a database engine runs an INSERT.

      One way we can talk about algorithms is to use something called Big-O Notion [], which describes the relationship between how much stuff an algorithm processes and how long it takes to run.*

      It's easier to see things with examples. Say we have an algorithm and we give it three sets of data, D1 and D2, and D3, each twice as large as the last, so that D2 is twice as large as D1, and D3 is four times as large as D1.

      If we call the algorithm O(1), it will take the same amount of time to process D1, D2, and D3. If we instead say it's O(N), D2 will take twice as long to run as D1, and D3 will take four times as long.

      If N represents the number of users for a web application, and we want to double N, twice as many users, we'd need twice as many web servers if the bottleneck algorithms are O(N). If the database is the bottleneck, we'd need a twice-beefier database server, or some partitioning.

      Things start to get interesting with O(N^2). In that case, D2 takes four times longer to run than D1, and D3 takes four times longer than D2, which sixteen times longer than D1.

      That means that if we want to support twice as many users, we need four times as many web servers, or more likely, a four-times beefier database server.

      It can get a lot worse than O(N^2) too, especially if you're not paying attention to complexity. For example, many graph (think social networking) algorithms can easily become O(2^N), which is a lot worse than N to a constant power.

      When you try to scale a poorly-designed algorithm (pretty much anything worse than O(N)), you start running out of cores, rack space, electricity, and atoms in the universe.

      One useful bit about big-O notation is that it lets us ignore piddly details that don't matter. Say we had an O(2N) version of the O(N) algorithm. Sure, the O(2) algorithm might take twice as long to run, but it can still handle double the data with double the capacity or double the time. Even if it's O(10N), you don't start boiling the oceans to cool your data center when you want to increase your visit capacity a thousandfold.

      This observation is why the choice of language doesn't matter. If a language implementation is slow, all it does is add a constant factor to any algorithms written in that language. A Python application might be ten times slower than one written in C, but its big-O complexity will be the same.

      At the worst, that means you'll need ten times as many servers as with the C web application. The increase in development efficiency writing in Python (or Ruby on Rails, or Lisp, or anything else) might make the trade-off worth it. You can deal with a constant factor slowdown.

      If on the other hand, you code a wicked fast implementation of an O(N^3) algorithm in C, no amount of hardware will save you. You'll hit a number of users beyond which your servers slow to a crawl and you lose blagosphereic karma. Even if you double your capacity, or buy a four-times-beefier database server, that
      • Re: (Score:1, Redundant)

        Some web frameworks make it easy to scale and some don't. I don't why you need to get all worke d up when people say Rails does not scale easily as well as other frameworks. Rewriting Twitter in C may not yield much benefits but if it makes it easier to go out and buy 10 machines and make it scale even with a algo that isn't super perfect or elegant, that's better than having a framework that doesnt' do that.
        • Re: (Score:3, Insightful)

          by QuoteMstr ( 55051 )
          That's the beauty of the web. At a basic level, it's stateless. Web frameworks don't have any concept of communicating with other clients. The highest level they'll work at is the individual session. You only see complexities worse than O(N) when clients communicate with each other, and that communication must be an entirely application-specified thing. The web framework and language have nothing to do with this communication between clients, and so have nothing to do with scalability writ large.
      • Re: (Score:3, Insightful)

        by mcrbids ( 148650 )
        Well written post! It's amazing how few people really understanding the difference between performance and scalability. Getting good performance isn't all that hard. Getting good scalability is much harder.

        Good scalability is not about how fast something processes, it's about how much the speed degrades as the load increases. It sounds simple - but it's NOT.
      • Re: (Score:3, Insightful)

        by Gazzonyx ( 982402 )
        First let me say, that was a very well thought out and informative post. I only would like to bring up a counter point for the sake of discussion.

        The language you choose may affect your ability to scale when you take its concurrency model (or lack thereof in some cases) in to account. For instance, I can have a O(1) algorithm, using a hashmap, but that doesn't mean that I'll be able to have the runtime performance of constant time. For a solid example, let's use Java (Java 6, with java.util.concurrent,
        • by QuoteMstr ( 55051 ) <> on Tuesday June 03, 2008 @04:00AM (#23635563)
          Thank you for your polite reply, but I feel like I haven't adequately communicated my point.

          The language you choose may affect your ability to scale when you take its concurrency model (or lack thereof in some cases) in to account. For instance, I can have a O(1) algorithm, using a hashmap, but that doesn't mean that I'll be able to have the runtime performance of constant time.

          If your whole web application is bottlenecked by one hashmap, you're going to run into scalability problems as soon as you need more than one machine anyway. On the other hand, If the performance of the web application as a whole does not depend on the hashmap, then your argument is irrelevant to the scalability of the application as a whole.

          I concede that a more efficient runtime environment might make better use of the same hardware, supporting, say, 70 clients instead of 50 per machine. But that's not the kind of scalability I'm talking about. Even a platform that achieved only one client per machine that scaled linearly would be better than one that handled 70 clients per machine, except that you were limited to one machine.

          And yes, on one machine, a bad choice of data structure can affect scalability. But the blame for that rests on the data structure itself, not the language in which it is implemented. As an associative array, a Python hash table (dict) will scale far better than a C linked list. Why? Because one's a hash table and one is a linked list!

          Which data structures are available in which language might factor into the choice of language, but it's only a convenience: you can always create your own data structure implementations.

          Granted, there are ways around this, but you can't just throw hardware at the problem and pretend it doesn't exist.

          Creating a scalable application means being able to throw hardware at the problem.

          Let's assume you've gotten your application to scale beyond one machine anyway. That's a prerequisite for this section.

          Now, if the machines don't communicate and users don't care, you automatically win O(N) scalability.

          If your machines must communicate, they do so over some kind of network. The way this communication is achieved determines the scalability of the application. While some environments might have more intuitive network facilities than others (think Erlang), ultimately one can use any approach to networking with any language.

          Again, we're reduced to choice of data structures and algorithms, not language, as the marker of scalability.

          The choice of language does not dictate the data structure the designer of the application uses, and so the language is not a serious barrier to scalability. I concede it may be more difficult to implement efficient protocols in some languages than in others, but we're dealing with turing-complete languages here, aren't we?

          I should note that languages typically thought of as "slower" are often more expressive. It often takes less effort to write efficient algorithms in expressive languages.

          (Returning to our previous example, since writing a hash table is more complex than writing a naive linked list in C, a C programmer is more likely to use a linked list at the expense of scalability. In Python, using a hash table is as simple as writing {}, so an equally-skilled programmer is more likely to use the more efficient data structure, resulting in better performance in a "slower" language.)

          The bottom line is that if communication between nodes is required, complexity must be > O(N). And if complexity is greater than O(N), then as N increase without bound, the communication overhead approaches infinity anyway. The key is to make that growth as slow as possible.

          The tools and techniques used to slow that growth --- thinking about the problem, designing efficient algorithms --- are features of the human mind, and not any particular language.

          Saying that one language is better at scaling than another is like arguing that one human language is better for building cars than another!
        • That is almost a good counterpoint, but for one thing: What you're effectively saying is not that the language itself is poor, or slow (in the usual "bytecode is slow" sense), but rather that the data structure itself is slow or poorly implemented, or whatever. The same data structure implemented in C with the same algorithms would yield the exact same performance bottlenecks. The problem with Java and .NET and similar architectures is that you have issues separating the concept of "Language" with the conce
      • Re: (Score:3, Interesting)

        by Just Some Guy ( 3352 )

        This observation is why the choice of language doesn't matter. If a language implementation is slow, all it does is add a constant factor to any algorithms written in that language.

        That's the crappiest, most long-winded apology for poor performance I've seen. Yes, everything you said about O() notation is more or less correct. No, you can't wish it to be applicable just by squinting really hard and hoping.

        At some point, that constant does start to matter. Suppose your O(n) algorithm written in $fast_language can support the world's population logged in simultaneously. Further suppose that you wrote prototype #1 in $spiffy_language that can support about 100 users on the same h

  • by trybywrench ( 584843 ) on Monday June 02, 2008 @04:37PM (#23631145)
    I wonder what they mean by "elegant filesystem-based approach"? Maybe their going to treat tweets like an email and store it all in the filesystem rather than a database? There's certainly some proven extremely high volume email servers so you know that method scales.

    I wonder what the disadvantages of setting up a front end to an email system and covert incoming tweets to actual an actual email is. On the retrieval side you just read the mailbox and convert back to the tweet format then send them on to the destination.
    • I was on hold, with CIHost no less, while posting so ignore my bad spelling and grammer :(
    • Re: (Score:2, Informative)

      by Balerion ( 25115 )
      This post [], from the author of a similar system, breaks down the pros and cons of an email-like approach to the problem.

      One simple but painfully restrictive solution is to duplicate the data for each user. Basically what this means is turning the service into an email system. Each user is given a mailbox and whenever someone they are following publishes a status, it is copied into their inbox, as well as into all the other followers' inboxes. This brings the solution in line with existing systems such as web

    • by PhotoGuy ( 189467 ) on Monday June 02, 2008 @09:17PM (#23633683) Homepage
      I was founder of a top 100 internet site during the .COM era. We grew to serve millions of hits a day, millions of users, yadda, yadda, yadda.

      We initially used a simple file based approach for user data (on vanilla Linux commodity boxes). It worked well.

      As we grew, there was some pressure to move to a database approach, so we switched to Sybase (free on Linux). It worked well, and scaled us through a lot of growth.

      However, eventually, when the database bogged down and no amount of tuning would help, rather than clustering, we looked at the nature of our data (a user's data was self-contained, generally not related to any other user's data), so having a massive relational database of hundreds of millions of records wasn't really necessary. So we went back to the file-based approach (with a good central "locking daemon" to ensure atomicity of writes), and gained a lot of performance (and simplicity). Even with thousands of bits of information or transactions for a user, a flat file is pretty darn manageable.

      Generally people jump at databases as a default way to store data. If a single user's data is fairly manageable, and you have millions of users, there are times when plain old files suffice. (Doing some smart things like ensuring that directories don't grow arbitrarily and such also help, but that stuff is generally a lot easier than db design and maintenance.)

      It sounds like Twitter didn't have well-thought out foundations, and they're reworking some of that. Good for them. (I've actually found some good consulting work in helping companies like them deal with scalability issues, from my experience with such things...)
      • Are you saying that in your situation a direct file-based approach would be faster than an indexed and range-partitioned table in a database like Oracle?
        • Are you saying that in your situation a direct file-based approach would be faster than an indexed and range-partitioned table in a database like Oracle?

          Faster? Than a properly designed, maintained, backed-up, optimized, licensed, Oracle database? Probably not.

          But it's fast enough, scalable, an order of magnitude simpler, doesn't require a six or seven-figure licensing fee once you get big, doesn't require major hardware to run on, and doesn't require a $100k/year Oracle specialist to maintain it. I've a

    • I wonder what they mean by "elegant filesystem-based approach"?
      Part of me thinks "what a load of pretentious bullshit" and part of me thinks "wow, some lucky bastard will have fun coding that".
  • by revscat ( 35618 ) on Monday June 02, 2008 @04:39PM (#23631191) Journal
    You know, I wonder how hard it would be to do a Twitter clone on Google's App Engine. It seems like it would be the perfect fit: relatively simple application that needs to be massively scalable.
  • ...twitter blog is hosted on blogger (Google), and this morning it was out of service.

  • ...the Twitter team has been making a concerted effort to affect better communication...

    From what I've heard the only affect twitter's had on communication isn't one worth bragging about.

  • by bistromath007 ( 1253428 ) on Monday June 02, 2008 @05:02PM (#23631449)
    It seems to be meant to suggest that the article's use of "affect" is incorrect. Surely this is mistaken. If suggesting that twitter has anything to do with better communication isn't an affectation, I don't know what is.
  • Fargin' hilarious []. Twitter seems to me to be absolutely February 2001, just milliseconds before the crash stupid.
  • ergh Twitter (Score:1, Flamebait)

    by aztektum ( 170569 )
    Talk about sites the US Gov should shut down. Facebook and MySpace are up there too.
  • by the JoshMeister ( 742476 ) on Monday June 02, 2008 @05:17PM (#23631641) Homepage Journal

    Plurk [] has been gaining popularity in the past 24 hours, and it's handling scalability rather well so far (after having been mentioned by Leo Laporte, Robert Scoble, TechCrunch, and others). I'm very curious to see how well it would hold up if it had the same number of users as Twitter, though.

    • Re: (Score:3, Insightful)

      That is interesting. Sounds like were still running on in house development level servers when the load hit -- ouch. If I do end up using such a site, I d rather say I'm Plurking than tweeting. It sounds much cooler, like something to do after having too many beers, rather than trying to imitate a bird.
  • Nice try... (Score:3, Funny)

    by wigginz ( 730819 ) on Monday June 02, 2008 @05:37PM (#23631847)
    but who would quit Google to work for Twitter???
  • Why would they try to "affect" better communication when they could actually put it into effect instead?
  • ...was using Ruby on Rails"

    I doubt they'll come out and say that. But look at how flaky twitter is (try using it for a while). The two biggest sites on the internet that are built on RoR - Penny Arcade and twitter - are flaky as hell. I've met the PA coder, and I'm not willing to believe the twitter guys are incompetent, so it's obviously not their fault.

    RoR is known for obscenely high resource usage. I can't believe it'd be a good choice for large sites like twitter, long term.
  • 'team' (Score:3, Informative)

    by spazdor ( 902907 ) on Tuesday June 03, 2008 @03:49AM (#23635525)

    While it may not be rocket science, the Twitter team has been making...

    Psst, there's actually no "Twitter team." It's just one guy with like ten accounts.

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