When it comes to programming languages and performance, you can read all and its opposite on the web. It’s definitely a very controversial topic!

[Edit 15-Nov-2012] I had questions on reddit about the data-structures and algorithms we used. We develop an embedded search engine for mobile, and tests were done on our own data-structure that is far more efficient than SQLite or other platform options for this use-case. [/Edit]

For Algolia the story started when researching an instant suggest algorithm. I used Java for two reasons:

Main reason : our first client was using Java on Google App Engine

: our first client was using Java on Google App Engine Secondary: at that stage, I was doing a lots of refactoring and Eclipse is very efficient for these tasks

Once our algorithm was designed, I started to optimize performance on a desktop computer (core I7 950). For this, I indexed all titles of the English version of Wikipedia (4 millions titles). I optimized the Java code mainly by reducing the number of allocations. All instant suggest queries were then faster than 10ms.



As we planned from the begining to support iOS and Android, I needed to optimize for high performance on mobile. I then ported the Java code to Android and ended up with a few modifications (we needed to support old Android versions which have not a full support of Java SDK).

In order to test performance, I created a small “demo” app: CitiesSuggest, a mobile application based on Geonames database to look for a city name. I filled the index with all places with a known population. In the end, the database contained 270 000 city names.

As could be expected, the resulting application was quite sluggish on my Galaxy S2. The worst queries could take more than one second of CPU.

I then applied all possible methods described in the Anroid documentation and was able to reduce the response time to 700ms for the longest queries. This is better but still gives end-users an impression of sluggishness! Fortunately, common queries worked well enough to present our very first demos at LeWeb’12 London. I was subsequently able to improve the user experience a lot by adding asynchronous support. At that point, we decided to start implementing the objective-C version for iOS.

I started a new implementation fully done in objective-C from scratch without any premature optimization. I then developed the same CitiesSuggest application for iOS. I first got stuck with some basic UI stuff. For example I needed to reimplement an UILabel that supports highlighting! The standard UILabel does no support this, and other implementations like Three20 just have too many dependencies (you can download AlgoliaUILabel on github, I released the code under Apache licence). Once the UI was ready, I could see the actual performance was catastrophic! Instant suggest queries were between 200ms and 10 seconds on an iPhone 4S!

After profilling, I discovered that 95% of the time was spent in Objective-C messaging and ARC. Actually, I have millions of calls to very small methods with 1 or 2 lines of code, and I found a very good explanation in the internal of objc_msgSend (mainly on mikeask.com). There is in fact a hash table lookup behind objc_msgSend! This explains most of my performance problems.

To fix these problems, I started to replace all this low level objective-C implementation by a C++ implementation with inlined methods. Eventually, I finished with Objective-C code for high level classes while all the core was C++.

This change has dramatically improved performance with instant-search queries between 2ms and 90ms on a iPhone 4S. I struggled to find complex enough queries to reach 90ms! This resulted in a very nice user experience with a remarkably slick demo 🙂

After this succes, I decided to use the same C++ code on Android with Android NDK. With this approach I reduced our maximum query time from 700ms to 80ms on a Galaxy S2. But I was really disappointed by the Android display, as I did not reach the same level of interactive experience that I had with iOS. The display of results stays slower on Android, probably because I did not spend enough time to optimize this part.

In the end, I lost a lot of time with Java and Objective-C trying to optimize code when the real solution was to use C/C++. I am fully convinced that it is just not possible to reach the same speed with Objective-C only or Java only.

And there is also another good property with C++ code: Blackberry supports C++, and there is large chance that Windows Phone 8 SDK will support C++ when released in a few weeks. Actually, I do not see any other alternative than C/C++ when you are looking for performance on mobile devices, which is our case 🙂

I hope this article will prevent you from spending as much time on Java/Objective-C optimizations as I did.