Disclaimer: I’m not responsible for any damages or injury, including but not limited to special or consequential damages

Author : tforever.living
Publish Date : 2021-01-07 09:50:43


Disclaimer: I’m not responsible for any damages or injury, including but not limited to special or consequential damages

That’s where the concept of aSharedFlow comes in. A shared flow exists regardless of whether it is being collected or not. A collector of the shared flow is called a subscriber. All subscribers of a shared flow receive the same sequence of values. It effectively works like a “broadcast channel”, without most of the channel overhead. It makes the concept of a broadcast channel obsolete.

But how do you handle things like user actions, external device events, state updates, etc? They are operating independently of whether there is any code that is interested in them. They should support multiple observers inside the application. These are so-called hot sources of events.

The performance of such an operator was far from great, especially compared to just writing an if statement. In a hindsight, it is not surprising, because a channel is a synchronization primitive. Any channel, even an implementation that is optimized for a single producer and a single consumer, must support concurrent communicating coroutines and a data transfer between them needs synchronization, which is expensive in modern multicore systems. When you start building your application architecture on top of the asynchronous data streams, the need to have transformations naturally appears, and the channel costs start to accrue.

Thus the BroadcastChannel interface was introduced with buffered and ConflatedBroadcastChannel as its implementations. They served us well for a while, but they turned out to be a design dead-end. Now, since kotlinx-coroutines version 1.4 we have introduced a better solution — shared flows. Read on for the full story.

It has tunable parameters such as the number of old events to keep and replay for new subscribers and the extraBufferCapacity to provide cushion for fast emitters and slow subscribers.

So for the next few days, I will be running on this kernel a bit more and will report back if there’s anything noteworthy. My only concerns now are one, I am not familiar with systemd-boot so I am unsure if the above method has any repercussions and two, I am not sure how safe it is to run the low latency kernel with the rest of System76’s customized pieces against this hardware. I guess off to more reading and perhaps maybe even ask System76 support.

In the early versions of the library, we had only channels and we tried to implement various transformations of asynchronous sequences as functions that take one channel as an argument and return another channel as a result. It means that, for example, a filter operator would run in its own coroutine.

So for the next few days, I will be running on this kernel a bit more and will report back if there’s anything noteworthy. My only concerns now are one, I am not familiar with systemd-boot so I am unsure if the above method has any repercussions and two, I am not sure how safe it is to run the low latency kernel with the rest of System76’s customized pieces against this hardware. I guess off to more reading and perhaps maybe even ask System76 support.

The simple design of Kotlin Flow allows efficient implementation of transformation operators. In basic cases, values are emitted, transformed, and collected in the same coroutine, without any need for synchronization.

class BroadcastEventBus { private val _events = MutableSharedFlow() val events = _events.asSharedFlow() // read-only public view suspend fun postEvent(event: Event) { _events.emit(event) // suspends until subscribers receive it } }

Thus Channel was added as an inter-coroutine communication primitive. The channels are wonderful. Channels support one-to-one, one-to-many, many-to-one, and many-to-many communication between coroutines, and every value that is sent to the channel is received once.

Once upon a time coroutines were introduced to Kotlin and they were lightweight. We could launch a multitude of coroutines and we needed a way to communicate between those coroutines without running into a dreaded “mutable shared state” problem.

And… voila! The system booted up with the low latency kernel. However, when it first booted up, after I logged in, input (mouse and keyboard) was frozen up for a little bit. After a couple of minutes, it was back to normal and then things not only went back to normal but the system as a whole felt a bit snappier. Though I am immediately noticing that I am loosing a nominal amount of battery life (less than 5% of battery in a 4 hour time frame) which is to be expected.

The flow itself is not backed by any kind of computation and does not have any state by itself until it starts to be collected. Every collector coroutine executes its own instance of emitting code. The story on “Cold flow, hot channels” describes the reasoning behind Kotlin Flows and shows use-cases for which they fit better than channels — returning asynchronous streams of values that are computed on demand.

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http://news24.gruposio.es/ydd/video-Norway-Denmark-v-en-gb-1prd30122020-.php

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http://live-stream.munich.es/exd/Video-KS-Lechia-Tomaszow-AZS-Czestochowa-v-en-gb-1zbg-13.php

answer is 42 and the question is what I meant when I said now you know but you’re too young to understand. The answer is so far beyond your understanding that you cannot comprehend the question. And that, my child, is the answer to life, the Universe and everything.



Category : general

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