Performance tuning

One of the biggest advantage of desktop translation tools is that they don’t have delays rendering the interface – at least not in such a scale as websites have. In it is crucial that our pages load very fast. In certain places we can and do use intelligent preloading to remove the delays, in other places we have to employ complex caching algorithms to reach that target. I am regularly monitoring the automatically collected profiling information to avoid regressions and to pick low-hanging fruit from time to time.

In the last sprint my main task was to convert the way we handle the translation of MediaWiki extensions in to use the same processes and interfaces as pretty much everything else. MediaWiki and MediaWiki extensions were the first things supported in and now they are among the last things to get modernized to take advantage of better interfaces built on the years of experience supporting various kinds of products.

The only user visible change is improved performance. The new interfaces are more efficient and enable more optimizations, which allows us to deliver faster page views and scale to more messages. It will also simplify the work of staff, as they don’t need to follow two different processes, especially after we update also MediaWiki translation code.

Perfection is achieved, not when there is nothing more to add, but when there is nothing left to take away.

As a developer I’m proud that the new code is unit tested. The culmination, however, was a change which removed hundreds of lines of old code: in fact, the above quote applies to software development too.

For those interested in details, the biggest performance boosts were achieved by avoiding the need to parse the translation files in many places – the list of message keys and their values are stored in intermediate cache files in CDB format. In addition there were many smaller performance optimizations, like not using some MediaWiki method to construct a link element, which consumed 20 kilobytes of memory for each link. When there are thousands of links, it adds up and is excessive for just making some hundred bytes of output. I switched it to a more low level method (memory usage: from 175 to 12 MB).

Some low-hanging fruit might not be as easy to pick as it seems at first. (Photo CC-BY-SA by Asit K. Ghosh.)

At the time of writing I still have some more fixes pending further testing and cleanup. For example, to access any message group, those all have to be loaded. They are cached as serialized PHP objects, but loading them takes 20 milliseconds and 10 megabytes of memory. I’m working on making it possible to load cached message groups individually.

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One Response to “Performance tuning”

  1. […] earlier post does not describe how I usually do performance improvements. Usually it starts with debugging the […]

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