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• HTTP : improve performance by reducing forward seeks

  30 janvier 2017, par Joel Cunningham

  HTTP : improve performance by reducing forward seeks
  This commit optimizes HTTP performance by reducing forward seeks, instead
  
  favoring a read-ahead and discard on the current connection (referred to
  
  as a short seek) for seeks that are within a TCP window’s worth of data.
  
  This improves performance because with TCP flow control, a window’s worth
  
  of data will be in the local socket buffer already or in-flight from the
  
  sender once congestion control on the sender is fully utilizing the window.
  Note : this approach doesn’t attempt to differentiate from a newly opened
  
  connection which may not be fully utilizing the window due to congestion
  
  control vs one that is. The receiver can’t get at this information, so we
  
  assume worst case ; that full window is in use (we did advertise it after all)
  
  and that data could be in-flight
  The previous behavior of closing the connection, then opening a new
  
  with a new HTTP range value results in a massive amounts of discarded
  
  and re-sent data when large TCP windows are used.  This has been observed
  
  on MacOS/iOS which starts with an initial window of 256KB and grows up to
  
  1MB depending on the bandwidth-product delay.
  When seeking within a window’s worth of data and we close the connection,
  
  then open a new one within the same window’s worth of data, we discard
  
  from the current offset till the end of the window.  Then on the new
  
  connection the server ends up re-sending the previous data from new
  
  offset till the end of old window.
  Example (assumes full window utilization) :
  TCP window size : 64KB
  
  Position : 32KB
  
  Forward seek position : 40KB
        *                      (Next window)
  
  32KB |--------------| 96KB |---------------| 160KB
  
          *
  
    40KB |---------------| 104KB
  Re-sent amount : 96KB - 40KB = 56KB
  For a real world test example, I have MP4 file of 25MB, which ffplay
  
  only reads 16MB and performs 177 seeks. With current ffmpeg, this results
  
  in 177 HTTP GETs and 73MB worth of TCP data communication.  With this
  
  patch, ffmpeg issues 4 HTTP GETs and 3 seeks for a total of 22MB of TCP data
  
  communication.
  To support this feature, the short seek logic in avio_seek() has been
  
  extended to call a function to get the short seek threshold value.  This
  
  callback has been plumbed to the URLProtocol structure, which now has
  
  infrastructure in HTTP and TCP to get the underlying receiver window size
  
  via SO_RCVBUF.  If the underlying URL and protocol don’t support returning
  
  a short seek threshold, the default s->short_seek_threshold is used
  This feature has been tested on Windows 7 and MacOS/iOS.  Windows support
  
  is slightly complicated by the fact that when TCP window auto-tuning is
  
  enabled, SO_RCVBUF doesn’t report the real window size, but it does if
  
  SO_RCVBUF was manually set (disabling auto-tuning). So we can only use
  
  this optimization on Windows in the later case
  Signed-off-by : Joel Cunningham <joel.cunningham@me.com>
  
  Signed-off-by : Michael Niedermayer <michael@niedermayer.cc>
  

  • [DH] libavformat/avio.c
  • [DH] libavformat/avio.h
  • [DH] libavformat/aviobuf.c
  • [DH] libavformat/http.c
  • [DH] libavformat/tcp.c
  • [DH] libavformat/url.h

• A Comprehensive Guide to Robust Digital Marketing Analytics

  15 novembre 2023, par Erin — Analytics Tips

  First impressions are everything. This is not only true for dating and job interviews but also for your digital marketing strategy. Like a poorly planned job application getting tossed in the “no thank you” pile, 38% of visitors to your website will stop engaging with your content if they find the layout unpleasant. Thankfully, digital marketers can access data that can be harnessed to optimise websites and turn those “no thank you’s” into “absolutely’s.”

  So, how can we transform raw data into valuable insights that pay off ? The key is web analytics tools that can help you make sense of it all while collecting data ethically. In this article, we’ll equip you with ways to take your digital marketing strategy to the next level with the power of web analytics.

  What are the different types of digital marketing analytics ?

  Digital marketing analytics are like a cipher into the complex behaviour of your buyers. Digital marketing analytics help collect, analyse and interpret data from any touchpoint you interact with your buyers online. Whether you’re trying to gauge the effectiveness of a new email marketing campaign or improve your mobile app layout, there’s a way for you to make use of the insights you gain.

  

  As we go through the eight commonly known types of digital marketing analytics, please note we’ll primarily focus on what falls under the umbrella of web analytics. 

  1. Web analytics help you better understand how users interact with your website. Good web analytics tools will help you understand user behaviour while securely handling user data. 
  2. Learn more about the effectiveness of your organisation’s social media platforms with social media analytics. Social media analytics include user engagement, post reach and audience demographics. 
  3. Email marketing analytics help you see how email campaigns are being engaged with.
  4. Search engine optimisation (SEO) analytics help you understand your website’s visibility in search engine results pages (SERPs). 
  5. Pay-per-click (PPC) or campaign analytics measure the performance of paid advertising campaigns.
  6. Content marketing analytics focus on how your content is performing with your audience. 
  7. Customer analytics helps organisations identify and examine buyer behaviour to retain the biggest spenders. 
  8. Mobile app analytics track user interactions within mobile applications. 

  Choosing which digital marketing analytics tools are the best fit for your organisation is not an easy task. When making these decisions, it’s critical to remember the ethical implications of data collection. Although data insights can be invaluable to your organisation, they won’t be of much use if you lose the trust of your users. 

  Tips and best practices for developing robust digital marketing analytics 

  So, what separates top-notch, robust digital marketing analytics from the rest ? We’ve already touched on it, but a big part involves respecting user privacy and ethically handling data. Data security should be on your list of priorities, alongside conversion rate optimisation when developing a digital marketing strategy. In this section, we will examine best practices for using digital marketing analytics while retaining user trust.

  

  Clear objectives

  Before comparing digital marketing analytics tools, you should define clear and measurable goals. Try asking yourself what you need your digital marketing analytics strategy to accomplish. Do you want to improve conversion rates while remaining data compliant ? Maybe you’ve noticed users are not engaging with your platform and want to fix that. Save yourself time and energy by focusing on the most relevant pain points and areas of improvement.

  Choose the right tools for the job

  Don’t just base your decision on what other people tell you. Take the tool for a test drive — free trials allow you to test features and user interfaces and learn more about the platform before committing. When choosing digital marketing analytics tools, look for ones that ensure data accuracy as well as compliance with privacy laws like GDPR.

  Don’t overlook data compliance

  GDPR ensures organisations prioritise data protection and privacy. You could be fined up to €20 million, or 4% of the previous year’s revenue for violations. Without data compliance practices, you can say goodbye to the time and money spent on digital marketing strategies. 

  Don’t sacrifice data quality and accuracy

  Inaccurate and low-quality data can taint your analysis, making it hard to glean valuable insights from your digital marketing analytics efforts. Many analytics tools only show sampled data or use AI and ML to fill data gaps, potentially compromising the accuracy and completeness of your analytics. 

  When your analytics are based on incomplete or inaccurate data, it’s like trying to assemble a puzzle with missing pieces—you might get a glimpse of the whole picture, but it’s never quite clear. Accurate data isn’t just helpful—it’s the backbone of smart marketing strategies. It lets you make confident decisions and enables precise targeting for greater impact.

  Communicate your findings

  Having insights is one thing ; effectively communicating complex data findings is just as important. Customise dashboards to display key metrics aligned with your objectives. Make sure to automate reports, allowing stakeholders to stay updated without manual intervention. 

  Understand the user journey

  To optimise your conversion rates, you need to understand the user journey. Start by analysing visitors interactions with your website — this will help you identify conversion bottlenecks in your sales or lead generation processes. Implement A/B testing for landing page optimisation, refining elements like call-to-action buttons or copy, and leverage Form Analytics to make informed, data-driven improvements to your forms.

  Continuous improvement

  Learn from the data insights you gain, and iterate your marketing strategies based on the findings. Stay updated with evolving web analytics trends and technologies to leverage new growth opportunities. 

  Why you need web analytics to support your digital marketing analytics toolbox

  You wouldn’t set out on a roadtrip without a map, right ? Digital marketing analytics without insights into how users interact with your website are just as useless. Used ethically, web analytics tools can be an invaluable addition to your digital marketing analytics toolbox. 

  The data collected via web analytics reveals user interactions with your website. These could include anything from how long visitors stay on your page to their actions while browsing your website. Web analytics tools help you gather and understand this data so you can better understand buyer preferences. It’s like a domino effect : the more you understand your buyers and user behaviour, the better you can assess the effectiveness of your digital content and campaigns. 

  Web analytics reveal user behaviour, highlighting navigation patterns and drop-off points. Understanding these patterns helps you refine website layout and content, improving engagement and conversions for a seamless user experience.

  

  Concrete CMS harnessed the power of web analytics, specifically Matomo’s Form Analytics, to uncover crucial insights within their user onboarding process. Their data revealed a significant issue : the “address” input field was causing visitors to drop off and not complete the form, severely impacting the overall onboarding experience and conversion rate.

  Armed with these insights, Concrete CMS made targeted optimisations to the form, resulting in a substantial transformation. By addressing the specific issue identified through Form Analytics, they achieved an impressive outcome – a threefold increase in lead generation.

  This case is a great example of how web analytics can uncover customer needs and preferences and positively impact conversion rates. 

  Ethical implications of digital marketing analytics

  As we’ve touched on, digital marketing analytics are a powerful tool to help better understand online user behaviour. With great power comes great responsibility, however, and it’s a legal and ethical obligation for organisations to protect individual privacy rights. Let’s get into the benefits of practising ethical digital marketing analytics and the potential risks of not respecting user privacy : 

  • If someone uses your digital platform and then opens their email one day to find it filled with random targeted ad campaigns, they won’t be happy. Avoid losing user trust — and facing a potential lawsuit — by informing users what their data will be used for. Give them the option to consent to opt-in or opt-out of letting you use their personal information. If users are also assured you’ll safeguard personal information against unauthorised access, they’ll be more likely to trust you to handle their data securely.
  • Protecting data against breaches means investing in technology that will let you end-to-end encrypt and securely store data. Other important data-security best practices include access control, backing up data regularly and network and physical security of assets.

  A fine line separates digital marketing analytics and misusing user data — many companies have gotten into big trouble for crossing it. (By big trouble, we mean millions of dollars in fines.) When it comes to digital marketing analytics, you should never cut corners when it comes to user privacy and data security. This balance involves understanding what data can be collected and what should be collected and respecting user boundaries and preferences.

  

  Learn more 

  We discussed a lot of facets of digital marketing analytics, namely how to develop a robust digital marketing strategy while prioritising data compliance. With Matomo, you can protect user data and respect user privacy while gaining invaluable insights into user behaviour with 100% accurate data. Save your organisation time and money by investing in a web analytics solution that gives you the best of both worlds. 

  If you’re ready to begin using ethical and robust digital marketing analytics on your website, try Matomo. Start your 21-day free trial now — no credit card required.

• What Every Programmer Should Know

  24 décembre 2012, par Multimedia Mike — General

  During my recent effort to force myself to understand Unicode and modern text encoding/processing, I was reminded that this is something that “every programmer should just know”, an idea that comes up every so often, usually in relation to a subject in which the speaker is already an expert. One of the most absurd examples I ever witnessed was a blog post along the lines of “What every working programmer ought to know about [some very specific niche of enterprise-level Java programming]“. I remember reading through the article and recognizing that I had almost no knowledge of the material. Disturbing, since I am demonstrably a “working programmer”.

  For fun, I queried the googles on the matter of what ever programmer ought to know.

  Specific Topics
  Here is what every programmer should know about : Unicode, time, memory (simple), memory (extremely in-depth), regular expressions, search engine optimization, floating point, security, basic number theory, race conditions, managed C++, VIM commands, distributed systems, object-oriented design, latency numbers, rate monotonic algorithm, merging branches in Mercurial, classes of algorithms, and human names.

  Broader Topics
  20 subjects every programmer should know, 97 things every programmer should know, 12 things every programmer should know, things every programmer should know (27 items), 10 papers every programmer should read at least twice, 10 things every programmer should know for their first job.

  Meanwhile, I remain fond of this xkcd comic whose mouseover text describes all that a person genuinely needs to know. Still, the new year is upon us, a time when people often make commitments to bettering themselves, and it couldn’t hurt (much) to at least skim some of the lists and find out what you never knew that you never knew.

  What About Multimedia ?
  Reading the foregoing (or the titles of the foregoing pieces), I naturally wonder if I should write something about what every programmer should know about multimedia. I think it would look something like a multimedia programming FAQ. These are some items that I can think of :

  1. YUV : The other colorspace (since most programmers are only familiar with RGB and have no idea what to make of the YUV that comes out of most video decoding APIs)
  2. Why you can’t easily seek randomly to any specific frame in a video file (keyframe/interframe discussion and their implications)
  3. Understand your platform before endeavoring to implement multimedia software (modern platforms, particularly mobile platforms, probably provide everything you need in the native APIs and there is likely little reason to compile libavcodec for the platform)
  4. Difference between containers and codecs (longstanding item, but I would argue it’s less relevant these days due to standardization on the MPEG — MP4/H.264/AAC — stack)
  5. What counts as a multimedia standard in this day and age (comparing the foregoing MPEG stack with the WebM/VP8/Vorbis stack)
  6. Trade-offs to consider when engineering a multimedia solution
  7. Optimization doesn’t always work the way you think it does (not everything touted as a massive speed-up in the world of computing — whether it be multithreaded CPUs, GPGPUs, new SIMD instruction sets — will necessarily be applicable to multimedia processing)
  8. A practical guide to legal issues would not be amiss
  9.  ???

  What other items count as “something multimedia-related that every programmer should know” ?