Why do YouTube views freeze at 301?

Numberphile
22 Jun 201209:47

Summary

TLDR在这段视频脚本中,Brady Haran 探讨了 YouTube 视频的观看次数计数问题,尤其是数字 301 的神秘现象。Ted Hamilton,YouTube Analytics 的产品经理,解释了观看次数的统计过程以及为何当视频观看次数达到 301 时会暂时冻结。这涉及到对大量观看次数进行统计验证,以确保没有虚假观看。此外,还讨论了代码编写中的一个错误,导致计数器在达到 300 后错误地增加到 301 而不是停止。这段对话揭示了 YouTube 计数系统背后的技术细节和一些有趣的事实。

Takeaways

  • 🔢 YouTube视频的观看次数在达到301时会暂停更新,这是由于系统开始进行统计验证过程。
  • 🕒 观看次数在301暂停可能是半天到一天,以完成对真实观看次数的验证。
  • 🤔 观看次数的统计涉及到全球不同服务器的日志收集和聚合。
  • 🛑 视频观看次数被视为一种“货币”,因此需要通过严格的统计验证来排除虚假观看。
  • 💡 观看次数的统计和验证过程是自动化的,由计算机完成,而非人工。
  • 📈 当视频观看次数少于300时,系统不需要太严格的统计验证。
  • 🔄 观看次数的统计问题部分源于全球不同地点的视频缓存和请求响应。
  • 👨‍💻 代码中的一个逻辑错误导致了观看次数在达到300时不是立即停止,而是增加到301。
  • 🌐 由于全球服务器的同步问题,有时观看次数可能会超过301,达到302、305或310等。
  • 🔄 系统在统计验证后,所有额外的观看次数会累积并显示在视频的总观看次数上。
  • 📹 这段对话来自Numberphile频道,讨论了YouTube观看次数统计的内部机制和301现象。

Q & A

  • 为什么YouTube视频的观看次数会在301时暂停计数?

    -YouTube视频的观看次数在301时暂停计数是因为YouTube有一个统计验证过程。当视频观看次数超过300时,系统需要进行统计验证以确保观看次数是真实的,这个过程需要一些时间。

  • YouTube上的'观看次数'是如何定义的?

    -在YouTube上,'观看次数'被定义为由实际用户请求的视频播放,并且用户得到了他们想要的内容并拥有良好的用户体验。YouTube将观看次数视为一种'货币',因此需要努力消除虚假的观看次数。

  • YouTube是如何防止虚假观看次数的?

    -YouTube通过统计验证过程来防止虚假观看次数。这个过程中,系统会检查并验证观看次数,以确保它们是真实的,防止机器人或其他方式人为增加观看次数。

  • 为什么YouTube视频在全球不同服务器上缓存?

    -YouTube视频在全球不同服务器上缓存是为了提高视频加载速度和用户体验。这样,当用户请求视频时,视频数据不需要从很远的地方传输,而是从最近的服务器提供。

  • YouTube视频的日志是如何收集和处理的?

    -当用户观看视频时,服务器会在日志中写入一条消息。定期地,这些日志会被收集到中央日志收集区域,然后聚合在一起进行计数。

  • 为什么YouTube视频的观看次数有时会在302或305等数字上暂停?

    -这可能是因为在全球不同服务器上的日志同时更新到中央数据库时,可能会有多个观看次数同时被计入,即使它们已经超过了301。这是由于代码中的'小于或等于'逻辑导致的。

  • YouTube视频的观看次数冻结是否意味着实际观看次数被遗漏了?

    -不会,YouTube视频的观看次数冻结并不意味着实际观看次数被遗漏。一旦完成统计验证,所有在验证期间累积的额外观看次数都会被添加到总观看次数中。

  • 为什么YouTube视频的点赞数不会像观看次数那样冻结?

    -点赞数没有像观看次数那样经过同样严格的统计验证过程。点赞数的数量较少,因此系统可以更容易地处理它们,而不会出现像观看次数那样的冻结现象。

  • YouTube视频的观看次数冻结是否对视频的推广有影响?

    -观看次数冻结可能会让一些用户感到困惑,但它不会影响视频的实际推广效果。一旦统计验证完成,真实的观看次数会被正确反映。

  • YouTube视频的观看次数冻结现象是否是一个bug?

    -观看次数冻结现象并不是一个bug,而是YouTube设计的一个特性,用于确保观看次数的真实性和准确性。

  • 为什么YouTube视频的观看次数会在达到一定数量后进行统计验证?

    -当视频观看次数达到一定数量后,YouTube会进行统计验证以确保这些观看次数是真实的,防止虚假观看次数对视频排名和推广造成影响。

Outlines

00:00

📊 YouTube视频播放量的秘密

Brady Haran介绍了YouTube视频播放量在301这个数字停滞的现象,这引起了许多观众的好奇。他解释了当新视频上传后,播放量会迅速增加到301,然后冻结一段时间。这一现象让许多人感到困惑,促使他们要求Numberphile调查原因。

05:00

👨‍💻 解析YouTube播放量统计机制

YouTube产品经理Ted Hamilton解释了视频播放量统计的基本机制。他提到,YouTube将播放量视为一种货币,因此需要努力消除虚假播放量。他还谈到,视频通常会分布在全球不同的服务器上,这使得播放量统计变得更加复杂。

🔍 301停滞现象的根本原因

Ted Hamilton进一步解释了为什么播放量会停滞在301的原因。随着播放量超过300,YouTube开始进行统计验证,这一过程需要时间,导致播放量不再逐个增加,而是批量更新。这个验证过程旨在确保播放量的真实性,防止机器人或误导性内容产生的虚假播放量。

⚙️ 代码中的关键细节

Ted Hamilton解释了为何播放量会停在301的技术原因。原本的代码逻辑中使用了“<=300”这一条件判断,导致播放量在达到301时才停止。这种逻辑错误使得播放量卡在了301,直到YouTube完成验证过程。

🌍 全球服务器同步导致的变化

Brady Haran解释了为什么有时播放量会停在302、305甚至310。这是因为来自不同地区服务器的播放记录同时更新至中央数据库,导致多个播放量同时被计入,从而使得最终停滞的数字有所不同。

🎥 播放量冻结带来的困扰

Ted Hamilton提到,播放量冻结现象虽然没有引起严重问题,但确实让人感到不便,尤其是当点赞数与播放量不匹配时。尽管如此,这一现象也促成了像这类视频的诞生,帮助观众更好地理解YouTube的工作原理。

🕵️ 更多细节即将揭晓

Brady Haran透露,他与Ted Hamilton的对话还有更多未公开的内容,尤其是关于播放量定义的进一步探讨。他表示将很快在Numberphile频道上传这些内容。对于不喜欢与计算机或互联网相关话题的观众,他也承诺未来会有更为多样的内容。

Mindmap

Keywords

💡Numberphile

Numberphile 是一个专注于数字和数学现象的YouTube频道。在视频中,它通常用来介绍一些有趣的数学问题或数字特性。例如,本视频中讨论了YouTube视频观看次数计数器在达到301时的冻结现象,这是Numberphile频道上一个经常被请求的话题。

💡YouTube view counter

YouTube的观看次数计数器是一个显示视频被观看次数的功能。视频中提到,当视频上传后,如果它非常受欢迎,观看次数会迅速上升,但在达到301时会暂时停止计数,这引起了人们的好奇。

💡Ted Hamilton

Ted Hamilton 是YouTube Analytics的产品管理人,在视频中他解释了YouTube观看次数计数器的工作原理以及为什么会在301时冻结。他的角色对于理解视频计数器背后的技术逻辑至关重要。

💡Counterfeit views

虚假观看次数指的是那些不是由真实用户请求而产生的观看次数,可能是由机器人或误导性标题和缩略图导致的。视频中提到,YouTube需要通过统计验证过程来消除这些虚假观看次数,以确保计数的准确性。

💡Cache

缓存是一种存储技术,用于暂时存储数据以加快访问速度。在视频中,Ted Hamilton 解释了YouTube如何通过在不同地理位置缓存视频副本来提高视频加载速度,这也影响了观看次数的计数过程。

💡Log collection

日志收集是指将分散在不同服务器上的日志信息汇总到一个中心位置的过程。视频中提到,YouTube通过收集和聚合这些日志来计算视频的观看次数,这是统计验证过程的一部分。

💡Statistical verification process

统计验证过程是YouTube用来确保观看次数真实性的一种方法。视频中解释说,当视频观看次数超过300时,YouTube会启动这一过程,以防止机器人或其他不正当手段增加观看次数。

💡Batch increment

批量增加是指在统计验证过程完成后,将所有已验证的真实观看次数一次性添加到视频的总观看次数中。视频中提到,这与单个观看次数逐个增加的方式不同,是YouTube确保观看次数真实性的一种做法。

💡Code logic

代码逻辑是编程中用于控制程序行为的一系列指令和决策。视频中提到,YouTube观看次数计数器在301时冻结的现象是由于代码逻辑中的一个错误导致的,即使用了“小于或等于”而不是“小于”300的条件。

💡Idiosyncrasy

特性是指某物或某人特有的性质或行为。在视频中,Ted Hamilton 将YouTube观看次数计数器在301时的冻结现象称为YouTube的一个特性,这是因为它是由于编程决策和历史原因形成的。

💡Simultaneous update

同时更新是指在多个地方几乎同时发生的数据更新。视频中解释说,由于视频在全球多个服务器上被缓存,有时在301的门槛上可能会有多个观看次数同时被计入,导致计数器有时会暂时超过301。

Highlights

YouTube上的301现象:新视频上传后,观看次数达到301时会暂时冻结。

Ted Hamilton,YouTube Analytics的产品经理,解释了这一现象。

YouTube的观看次数被视为一种“货币”,需要严格防止虚假观看。

视频在全球范围内的缓存分布增加了观看次数统计的复杂性。

当视频观看次数超过300时,YouTube会启动统计验证过程。

301现象的产生是因为代码逻辑错误,将“小于300”误写为“小于等于300”。

代码编写者可能没有意识到这一逻辑错误对YouTube的巨大影响。

有时观看次数会停在302、305或310,这是由于全球服务器同时更新造成的。

视频的点赞数不会经过与观看次数相同的严格统计过程。

观看次数的暂时冻结可能导致一些尴尬的情况,例如视频有2000个赞却只有300次观看。

Brady Haran计划在未来上传更多关于YouTube观看次数的详细讨论。

观看次数的统计和验证过程是为了防止机器人刷量或误导性标题和缩略图带来的影响。

YouTube的观看次数统计系统是为了防止虚假观看而设计的。

观看次数的暂时冻结是YouTube的一个独特现象,由代码逻辑错误引起。

Ted Hamilton提到,尽管301现象引起了许多疑问,但它更多被视为一种烦恼而非严重问题。

Brady Haran和Ted Hamilton的对话深入探讨了YouTube观看次数统计的工作原理。

Numberphile频道通过这次访谈揭示了YouTube背后的技术细节和决策过程。

Transcripts

play00:00

BRADY HARAN: I want to deal with a number that must be the

play00:02

most requested so far on Numberphile, and that is 301.

play00:08

Now, for those of you who don't pay much attention to

play00:10

the YouTube view counters, you might wonder what the big deal

play00:13

is with 301, and let me tell you.

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When a new video is uploaded, and if it's quite a popular

play00:19

one, you'll quickly see the view counter rise and rise and

play00:22

rise, and then it will get to 301, and it will freeze.

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And it will stay on 301 for a day, maybe half a day, and

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then it will start counting to higher numbers as usual.

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Now, a lot of people have been very mystified by this, and

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have asked us to check it out.

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TED HAMILTON: I'm Ted Hamilton, I'm a product

play00:39

manager for YouTube Analytics.

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BRADY HARAN: So there you go.

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I've got in touch with the people who actually count the

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YouTube views.

play00:46

TED HAMILTON: That is correct.

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Well, we actually have the computers do it.

play00:49

We don't count them ourselves, but yes.

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BRADY HARAN: So before we get to this whole 301 malarkey,

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what is a view on YouTube?

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I've always wondered.

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is someone just pressing play counting as a view?

play01:00

TED HAMILTON: Well, that's actually a bit

play01:01

of a YouTube secret.

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A view should be a video playback that was requested by

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an actual user who got what they were intending to get and

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had a good user experience.

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We think of views as a currency, and therefore we

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have to make a significant effort to eliminate

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counterfeit views, if you will.

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BRADY HARAN: Now, I know that all sounds a bit mysterious,

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and we will come back to it later on in the video, but

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let's crack on with this 301 figure.

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And you're going to find out counterfeit views actually

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have a bit to do with it.

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But the next thing we need to realize is when you watch any

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video, like this one for example, you're probably not

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all watching it from the same server.

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It gets distributed all around the world.

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TED HAMILTON: So there is the original, which

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you will have uploaded.

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Or I guess by the time you are watching this,

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have already uploaded.

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Then this gets, what do you call it?

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Cached in different locations, so that when you make a

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request for a video, it doesn't need to travel all the

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way from London over to California and say OK, send me

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back all of these bytes way back here.

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BRADY HARAN: So with multiple copies of the video all around

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the world, counting the views starts to get a little bit

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more complicated.

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TED HAMILTON: Here's you at your computer

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watching the video.

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If you make a request to this server, this server is going

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to give you the video, right?

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And at the same time, this server is going to write a

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little message to a log.

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It's just one line in a log.

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Every once in awhile, we collect all of these logs.

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So we'll ship this thing in from central Europe, or

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whatever into the central log collection area, aggregate

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them all together, and then go through and count them up.

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BRADY HARAN: Well OK, that seems simple enough, but it

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doesn't explain why the view counter freezes.

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TED HAMILTON: Views, as mentioned, are a currency.

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When you have a video with a very small amount of views,

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then you don't need to be too careful about

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what that view was.

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However, once it gets to be above 300 and beyond, this

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currency we really need to verify and make sure that the

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number is what it purports to be.

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So this means that we have to go through a statistical

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verification process, and that statistical verification

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process actually takes some time.

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And thus we go from incrementing one by one to

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then saying, OK, now we're incrementing in batch, and all

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of these views that have been added on have been verified by

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YouTube to be real views.

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We are preventing things like bots to go in and add a bunch

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of views to a video.

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Or we are preventing something that may have perhaps misled

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someone into watching a video.

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Say you had a title that was completely misleading, and a

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thumbnail that was completely misleading, and people

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actually went on there and just viewed for a few seconds,

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and then left.

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If you see that enough times, it a fair enough indicator

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that something was wrong there, so that we might not

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authorize all of those to be legitimate views.

play03:55

BRADY HARAN: All right, then.

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They're verifying the numbers.

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They're checking everything.

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I guess we probably could have guessed that.

play04:00

But why 301?

play04:03

TED HAMILTON: I was not there when the decision was made,

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but at some point the decision was made that we need to draw

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a line between what is innocuous and the database can

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handle, and what is all of a sudden serious business.

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The proportion was calculated to be at about 300, that this

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is the portion that we need to take care of.

play04:22

But the formula that we use to arrive at 300, I don't know if

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anyone actually knows that.

play04:28

BRADY HARAN: Well, OK.

play04:29

They drew a line in the sand.

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It was kind of arbitrary.

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They wanted to differentiate between people just sharing

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their home movies and the videos that are more popular,

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the ones that are a bit more serious.

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The ones that need scrutiny.

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But that was 300.

play04:44

The view counter freezes at 301.

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What's going on here?

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Is there a reason?

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TED HAMILTON: Yeah, there is a reason.

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And the reason was the number 300 was chosen.

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And when someone's writing code, they need to put the

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logic in the code that says where you should stop, or

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where you should, if one condition is true,

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you go to the left.

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And the other condition is true, you go to the right.

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Now, this condition can be written like this.

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If the view count is less than 300, then go ahead and add one

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to the view count.

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Otherwise, go to x where x is our much more complicated view

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count pipeline.

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However, what actually got written was not this, but if

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view count is less than or equal to 300, then increment

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the view count.

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So what this means is if the view count is at 300, this

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says is the view count less than or equal to 300?

play05:47

Yes, it is.

play05:48

Let me add one.

play05:48

So then you end up at 301.

play05:50

BRADY HARAN: Let me recap what's going on here.

play05:53

The code which is controlling where this view counter

play05:55

freezes contains a less than or equal to sign.

play06:00

So that means when a new early view comes along, it's checked

play06:03

against the code.

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Say the overall view count on the database is 299.

play06:10

OK, then.

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We'll let another one on.

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Here comes another view.

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Now the view count is 300.

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That isn't less than 300, but it is equal to 300.

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So the code lets another view jump onto the total.

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Now we're at 301, and when another view comes along, it's

play06:29

not less than 300, but it's also not equal to 300 anymore,

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and the door is shut.

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There are going to be no more views added to the publicly

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visible count until YouTube have done their checks.

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And that will take half a day to a day.

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Then of course, all the extra views that have been counted

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in the interim all pile onto the total.

play06:49

Nothing's missed.

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At least that's what I'm told.

play06:52

TED HAMILTON: Yeah, so whoever wrote this code probably did

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not realize the magnitude of what they were doing.

play06:56

View counts have been around since the beginning of

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YouTube, and who was to know what YouTube would become.

play07:03

So yeah, that was actually a rather monumental second of

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time in San Bruno, California, when a coder decided to write

play07:12

that logic in.

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It is now one of the idiosyncrasies of YouTube.

play07:16

BRADY HARAN: Now, I can hear some of you screaming at your

play07:18

computer screens.

play07:19

The view count doesn't stop at 301.

play07:22

Sometimes it stops at 302, or 305, or 310.

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What's going on there?

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There's an explanation for that, too, and that comes back

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to how I was saying the videos are shared around servers all

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across the world.

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So here's what's going on there.

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Views are coming in from the logs at the different videos,

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the different places around the world.

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And they're coming to this central database.

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And we know the door's going to be shut at 301, we just

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explained that a minute ago.

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But what happens if views are coming in at the same time?

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Someone watched it in Africa at the exact same time someone

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watched in Europe.

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Now we've got multiple views coming in.

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Checking if they're allowed to join the count, yes they are.

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It's less than or equal to 300.

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So they all pile on at the same time.

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Now when a new view comes along, sorry,

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we're closed for business.

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But because of that simultaneous update, a few

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extra views were able to sneak on.

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TED HAMILTON: We get asked about it all the time.

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I wouldn't say that it causes angst, but it's certainly, I

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would classify it more as an annoyance.

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You can go and see a very popular video, and you look

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and you'll see that it has 2,000 likes and 300 views.

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That's a little bit interesting.

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The issue there is that we don't put the likes through

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the same rigor, same rigorous process.

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And likes are far fewer in magnitude, so our systems can

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handle them more easily.

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But the views do freeze, and it can result in some awkward

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situations.

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But that actually results in terrific videos like this, so.

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BRADY HARAN: I did speak to Ted for maybe 45, 50 minutes

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and recorded it all.

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I've got loads of footage, a lot more detail, including a

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bit more about what constitutes a view.

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And I know some of you will want to see it.

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I haven't had time to edit it all just yet, but stay tuned

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because I'll be uploading that to

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Numberphile in the near future.

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And for those of you who don't like these ones that are a bit

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more about computers and the internet, I'm sorry.

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Numberphile's always unpredictable, and I promise

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next time it might be something

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you enjoy a bit more.

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MATT PARKER: How many arrows do you want?

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So the next one, let's say we did 3 to the power of, to the

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power of, oh, arrow, arrow, arrow, or whatever you

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want to call this.

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3.

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Will that--

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