zk-and-rx

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Documentationobertwenzel
obertwenzel

Author
Robert Wenzel, Engineer, Potix Corporation
Date
September, 2017
Version
ZK 8.5

Introduction

Assume you are working for a project on a Robot Farm (I think there could be worse projects). Unfortunately those Robots are a bit moody and unreliable sometimes - so of course there needs to be a supervisor sitting in his/her office chair and watching a screen to follow all the Robots movements.

Since human supervisors are prone to errors too there should be multiple employees observing the same Robots simultaneously.

Based on their current assignment and in order to preserve bandwidths it must be possible to track certain Robots near real-time (filtered by mood or position) without completely losing track of the overall situation, i.e. highlighted Robots have a faster update rate than others (100 ms vs. 1 sec).

Employees may come and go as they like and connect/disconnect to the live data feed on demand.

However the Robots are constantly sending data at high frequency to your back-end process. Your challenge is to connect the UI to the stream of information reducing it based on the filter criteria and throttle the sheer amount of data to something the human eye and your network connection can handle.

Architecture

For the Robot event stream you choose rxjava LINK ME and ZK for the frontend (disclaimer: I work for ZK and rxjava's reactive streams fit well into ZK's MVVM design pattern, making an interesting combination worth talking about).

Here the technologies used:

The Backend (RX Observable)

The stream of TrackEvents is produced by a single hot Observable LINK ME initialized at first subscription.

  • constantly streams TrackEvent at 10ms intervals
  • unreliability simulated by randomly updating~30% of the robots with an additional 2% chance to change the mood
  • allows multiple consumers (using observable.publish() / observable.connect() LINK ME)

This Observable is unaware of the front end and will just stream the data no matter what - once started. For each new subscriber it will initially sends TrackEvents for all Robots followed by the random stream of events every subscriber shares.

The UI (ZK MVVM application)

  • render robots as divs + dynamic styles reacting on robot status (position, mood)

The Magic in the Middle

  • filter the events (by selectable criteria)
  • throttle UI updates (reducing the network load)
    • buffer updates (100ms / 1000ms)
    • avoid redundant updates
    • batch update (in a single ZK execution)

Summary

Example Sources

The code examples are available on github in the zk-rxdemo repository

Running the Example

Clone the repo

   git clone [email protected]:zkoss-demo/zk-rxdemo.git

The example war file can be built using the gradle-wrapper (on windows simply omit the prefix './'):

   ./gradlew war

Execute using jetty-runner (fastest):

   ./gradlew startJettyRunner

Execute using gretty:

   ./gradlew appRun


Then access the example http://localhost:8080/zk-rxdemo CHECK LINK


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Copyright © Potix Corporation. This article is licensed under GNU Free Documentation License.