infinitereactivestreams | Hello everyone | Reactive Programming library
kandi X-RAY | infinitereactivestreams Summary
kandi X-RAY | infinitereactivestreams Summary
Hello everyone, I hope you are all doing well. In this post we will look at how to setup and consume infinite streams of data and then process and redistribute the data. We look at the use case of a broadcaster of stock price data, which could be the main stock market. This is consumed by an investment company that has clients who subscribe to this information know as the subscribers. So the StockPriceBroadcaster is the provider. I use only one broadcaster here but we could extend the use case to multiple broadcasters. This is then consumed by the investment company’s application called InfiniteReactiveStreams. The consumed stock market data is then processed and distributed to it’s clients, who are the investor subscribers. We call one such subscriber InvestorSubscriber. Once again we could have a number of investor subscribers. The InfiniteReactiveStreams will “pull” data from a the StockPriceBroadcaster. This data will then be processed and sent to the InvestorSubscriber. The important question to ask is, why do we use reactive streams? Well the StockPriceBroadcaster sends frequent broad casts of stock market prices. These prices are available for a short period of time and no historical results are stored – maybe due to volume of storage on their system. So the Investment company at a given frequency must pull the stock price data in a timely manner. However the InvestorSubscriber might not be able to keep up with the data at the same pace that it is sent because the InvestorSubscriber might be performing analysis on the incoming data, for example Machine learning such as timeseries analysis to influence buy/sell decisions of the investor subscriber’s portfolio. This analysis of the results takes more time than the consumption of the results. This delay introduces the concept of backpressure and the need for replay of recent values – hence Reactive Streams are a suitable candidate technology for such a use case. In this tutorial we are going to use the RxJava3 Reactive Streams implementation. Most notably we will use RxJava3 specific features such as replay on Flowables(The RxJava3 terminology for a stream of data). Even though the source of data is a Hot observable we are pulling that data periodically hence we are using a cold observable with backpressure to store the hot observable data. We present two applications in this tutorial. The main application with the all the functionality is the InfiniteReactiveStreams application and the second is just a small Spring-maven-java application that exposes a REST endpoint to GET stock prices.
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Top functions reviewed by kandi - BETA
- Starts the infinite stream
- Starts a streaming stream
- Get the singleton subscriber
- Set the subscription
- Returns a string representation as a string
- Gets the value of this entry
- Gets the id
- Fetch stock stats summary
- Gets the subscription
- Request n items
- Add a stock to the list
- Displays the stock prices
- The main application
- This method cancels the scheduler
- This method is called when the application completes
- Log an error
infinitereactivestreams Key Features
infinitereactivestreams Examples and Code Snippets
Community Discussions
Trending Discussions on Reactive Programming
QUESTION
How can we divide work of consumers over a limited set of resources in RXJS?
I have a Pool class here (simplified):
ANSWER
Answered 2022-Mar-31 at 12:55So the main thing is you need to share the actual part that does the work, not only the resources.
Here's a solution from me:
https://stackblitz.com/edit/rxjs-yyxjh2?devToolsHeight=100&file=index.ts
QUESTION
There are two observables: the first named activator emits booleans. The second named signaler emits void events. There's a function f() which must be called under the next conditions:
If the last event from activator is true, and event from signaler comes, call f(). Otherwise (the last activator's event is false, or activator has not yet emitted anything), "remember" that signaler sent the event. As soon as activator emits true, call f() and clear "remembered" flag.
Example:
...ANSWER
Answered 2022-Mar-23 at 18:10You need a state machine, but you can contain the state so you aren't leaving the monad... Something like this:
QUESTION
We are using spring webflux (project reactor), as part of the requirement we need to call one API from our server.
For the API call, we need to cache the response. So we are using Mono.cache operator.
It caches the response Mono and the next time the same API call happens, it will get it from the cache. Following is example implementation
ANSWER
Answered 2022-Mar-03 at 14:54You can initialize the Mono in the constructor (assuming it doesn't depend on any request time parameter). Using cache operator will prevent multiple subscriptions to the source.
QUESTION
I would like to combine two observables in such a way that
- I mirror at most 1 value from the source observable (same moment it arrives),
- Then ignore its subsequent values until the notifier observable emits;
- Then, I allow to mirror at most 1 more value from the source;
- After which I again ignore elements until the notifier observable emits
- etc.
Source:
...ANSWER
Answered 2022-Jan-20 at 13:05I believe this is a simple use case of the throttle() operator.
QUESTION
I need to copy date from one source (in parallel) to another with batches.
I did this:
...ANSWER
Answered 2021-Dec-04 at 19:50You need to do your heavy work in individual Publisher-s which will be materialized in flatMap() in parallel. Like this
QUESTION
Context
I started working on a new project and I've decided to move from RxJava to Kotlin Coroutines. I'm using an MVVM clean architecture, meaning that my ViewModels communicate to UseCases classes, and these UseCases classes use one or many Repositories to fetch data from network.
Let me give you an example. Let's say we have a screen that is supposed to show the user profile information. So we have the UserProfileViewModel:
ANSWER
Answered 2021-Dec-06 at 14:53The most obvious problem I see here is that you're using Flow for single values instead of suspend functions.
Coroutines makes the single-value use case much simpler by using suspend functions that return plain values or throw exceptions. You can of course also make them return Result-like classes to encapsulate errors instead of actually using exceptions, but the important part is that with suspend functions you are exposing a seemingly synchronous (thus convenient) API while still benefitting from asynchronous runtime.
In the provided examples you're not subscribing for updates anywhere, all flows actually just give a single element and complete, so there is no real reason to use flows and it complicates the code. It also makes it harder to read for people used to coroutines because it looks like multiple values are coming, and potentially collect being infinite, but it's not the case.
Each time you write flow { emit(x) } it should just be x.
Following the above, you're sometimes using flatMapMerge and in the lambda you create flows with a single element. Unless you're looking for parallelization of the computation, you should simply go for .map { ... } instead. So replace this:
QUESTION
I am trying to create a table (with DT, pls don't use rhandsontable) which has few existing columns, one selectinput column (where each row will have options to choose) and finally another column which will be populated based on what user select from selectinput dropdown for each row.
in my example here, 'Feedback' column is the user dropdown selection column. I am not able to update the 'Score' column which will be based on the selection from 'Feedback' column dropdown.
...ANSWER
Answered 2021-Sep-30 at 14:31I'd suggest using dataTableProxy along with replaceData to realize the desired behaviour. This is faster than re-rendering the datatable.
Furthermore, re-rendering the table seems to be messing around with the bindings of the selectInputs.
Also please note: for this to work I needed to switch to server = TRUE
QUESTION
I'm receiving a request through a rest controller method with an object that I'm then passing to a method in the service layer.
The object in this request contains a list as follows:
...ANSWER
Answered 2021-Oct-18 at 16:21The expected way to do that is to actually use the fromIterable method and provide your List:
QUESTION
The following code attempts to react to one Supply and then, based on the content of some message, change its mind and react to messages from a different Supply. It's an attempt to provide similar behavior to Supply.migrate but with a bit more control.
ANSWER
Answered 2021-Oct-07 at 10:20I tend to consider whenever as the reactive equivalent of for. (It even supports the LAST loop phaser for doing something when the tapped Supply is done, as well as supporting next, last, and redo like an ordinary for loop!) Consider this:
QUESTION
I'm trying to use Combine to do several millions concurrent request through the network. Here is a mock up of the naive approach I'n using:
...ANSWER
Answered 2021-Oct-05 at 15:18The issue appears to be a Combine bug, as pointed out here. Using Publishers.Sequence causes the following operator to accumulate every value sent downstream before proceeding.
A workaround is to type-erase the sequence publisher:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
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Install infinitereactivestreams
You can use infinitereactivestreams like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the infinitereactivestreams component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .
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