Flowable and back pressure


Backpressure : 

The process of handling a fast item producer means it allows to control how fast a source emits items
RxJava 2 introduced Flowable to represent backpressure-aware sources using a dedicated class

 Flowable : 


It is type of observables which emits 0 or n items and terminates with an success or an error event.
Supports backpressure.

Creating Flowables :

Simple Flowable : 


  1. We can create a Flowable using the just() method.

Flowable from Observable : 



  1.  Observable we can be easily transform to Flowable using the toFlowable() method.

Flowable from FlowableOnSubscribe : 



  1. RxJava 2 introduced a functional interface FlowableOnSubscribe, which represents a Flowable that starts emitting events after the consumer subscribes to it.

Backpressure Strategy:

Dropping


  1. Discards the unrequested items if it exceeds the buffer size.

    Latest : 

    1. Preserve the latest item
    2. It is type of observables which emits 0 or n items and terminates with an success or an error event.
    3. Supports backpressure.

    Buffring : 


    1. Buffers all the items from the producer, watch for OOMs.
    2. Error throws a MissingBackpressureException in case of over emission

    Missing: 


    1. No strategy, it would throw a MissingBackpressureException sooner or later somewhere on the downstream

    Reactive Pull

    In reactive pull, subscriber requests required number of items from observable by calling request()

    Comments

    Post a Comment

    Popular posts from this blog

    Difference between Imperative Approach and Reactive Approach

    Imperative Approach Pull based approach , means as a developer I am responsible for everything. Like I want to know any change in data I want to ask. Redundant code .Take data in Callback and later they share by using EventBuses, Broadcast Receivers or save in static objects. Or Polling mechanism ,so What I am doing now. This method call after every 1s or 1000ms Order of execution is Important - Synchronous Difficulty in scalability . eg. MVC Eg:  int val1 = 10;  int val2 = 20;  int sum = val1 + val2;  System.out.println(sum); // 30  val1 = 5; System.out.println(sum); // 30  Reactive Approach In Push approach developer only write simple code and give orders to data. Hey if any change in you, inform me. Achieved using observer pattern. Removes boilerplate code. If you want data from API’s which will be shared with more then one screens or classes on same time, always use Observer Pattern . Observer Pattern which is ...
    Read more

    The 10 Most Popular Coding Challenge Websites 2021

    Image
      A great way to improve your skills when learning to code is by solving coding challenges. Solving different types of challenges and puzzles can help you become a better problem solver, learn the intricacies of a programming language, prepare for job interviews, learn new algorithms, and more. Below is a list of some popular coding challenge websites with a short description of what each one offers. 1 . LeetCode LeetCode is a popular  Online Judge  that provides a list of 190+ challenges that can help you prepare for technical job interviews. You can solve the challenges  directly online  in one of 9 programming languages. You are not able to view other users' solutions, but you are provided statistics for your own solutions such as how fast your code ran when compared to other users' code. They also have a  Mock Interview  section that is specifically for job interview preparation, they host their own coding  contests , and they have a section f...
    Read more

    Java - Recursion

    Image
      What is Recursion? The process in which a function calls itself directly or indirectly is called recursion and the corresponding function is called as recursive function. Using recursive algorithm, certain problems can be solved quite easily. Examples of such problems are  Towers of Hanoi (TOH) ,  Inorder/Preorder/Postorder Tree Traversals ,  DFS of Graph , etc. What is base condition in recursion? In the recursive program, the solution to the base case is provided and the solution of the bigger problem is expressed in terms of smaller problems. int fact(int n) { if (n < = 1) // base case return 1; else return n*fact(n-1); } In the above example, base case for n < = 1 is defined and larger value of number can be solved by converting to smaller one till base case is reached. How a particular problem is solved using recursion? The idea is to represent a problem in terms of one or more smaller problems, and add one or more base co...
    Read more