Concurrency

Functional reactive programming seems to have taken the whole development world by storm. It’s one of the hottest thing even after 2 years of constant traction in the communities of several programming languages, where different implementations of the specifications defined by Rx or Reactive Extensions have changed the paradigm of programming for many professional and enthusiast developers. RxJava is no exception, not only has it been widely adopted by Android and Java developers unanimously, but also received attention of well known and top developers of both communities. The reason of its success is the fluent API with heavy toolset it provides from the Functional Programming paradigm and its ease and natural ability to handle concurrency on different levels based on the type of operation being performed, i.e., computations, I/O, etc. It basically takes away the several constraints and concurrency related checklists developers had to maintain while working with thread management. So, now, developers can’t make an excuse for using database operations on the Main Thread because offloading it on another thread is hard. So, in this blog post, I will be detailing the process of converting the existing synchronous code of your app into a performant reactive code without breaking the structure of your project, like we did in Open Event Android (Github Repo). Before starting, I have assumed that you know how to add RxJava dependency to your project as it is covered in many other blog posts and the documentation is also very clear. Secondly, you should also add RxAndroid dependency as it contains the Scheduler needed to work on Android’s Main Thread. So, Let’s start. Current State Currently, our code loads the queries from database synchronously on Main Thread using the SQLiteDatabase for an Android application. This is how it looks like - As we can see, we are directly returning the loaded results to the caller. This is called synchronous call, meaning the caller will block till the function is returned, and can’t move further to do anything else. It basically waits for the function to return, which may take hundreds of milliseconds to seconds based on the function it performs. New Android version crash the applications that perform Network interactions on the main thread but no such restriction for disk based operations is there, making it hard to enforce best performance practices. Before RxJava, there were interfaces made for different kinds of objects, passed in as parameters of the db request function, which created a new thread and performed operations and when completed, returned back the results to the main thread using the postOnUiThread method, so that the views could update themselves. The interface implementations passed are called callbacks because they call a particular function that you provide back when the asynchronous operation is completed. Even the calling of callback function is delegated on the implementor and may result in undesired effects. The query done in this fashion is called an asynchronous query because the execution of this takes place in parallel with main thread…