Turbulence

Simple tools for working with data streams in LazyLists

Turbulence provides a few useful methods for working with LazyLists for streaming

Features

• provides several stream-related operations on LazyLists
• can multiplex several streams into a single stream
• can cluster together short sequences of events which happen within a predefined period of time

Availability Plan

Turbulence has not yet been published. The medium-term plan is to build Turbulence with Fury and to publish it as a source build on Vent. This will enable ordinary users to write and build software which depends on Turbulence.

Subsequently, Turbulence will also be made available as a binary in the Maven Central repository. This will enable users of other build tools to use it.

For the overeager, curious and impatient, see building.

Getting Started

Operations on LazyLists

Funnels

A Funnel receives asynchronous events, potentially from multiple threads, and puts them into a LazyList

For example,

val funnel: Funnel[Int] = Funnel[Int]()
funnel.put(2)
Future(funnel.put(6))
val events: LazyList[Int] = funnel.stream

Note that evaluation of the Funnel#stream method constructs a LazyList which consumes events, and should be called exactly once. Later releases of Turbulence will change the API to avoid this trap.

Clustering

An event stream provided by a LazyList[T] may yield events irregularly, often with several events happening at the same time. A simple event-handling loop, which performs a slow operation, such as,

stream.foreach: event =>
  slowOperation(event)

will incur a time cost for every event in the stream; so if the operation takes one second and ten events arrive at around the same time, it will take about ten seconds from the first event arriving until the last event is processed.

Sometimes it can be quicker to process events in a batch, or the results of processing earlier events can be invalidated by the arrival of later events. In these cases, clustering the events on a stream can be useful.

The LazyList#cluster extension method can transform a LazyList[T] into a LazyList[List[T]]. It will group together sequences of events arriving with less than a specified gap in time between them.

For example,

stream.cluster(1000).foreach: events =>
  slowOperation(events.last)

will effectively ignore all but the last event, but will not start processing an event until 1000ms has passed without any new events.

As a more complete example, consider the event stream, stream, which produces events 0-9 at the times shown in the "Time" column.

Event	Time	Gap	stream	stream.cluster(10)	stream.cluster(100)
0	4ms		0 @ 4ms
1	8ms	4ms	1 @ 8ms	{0,1} @ 18ms
2	15ms	7ms	2 @ 15ms	{2} @ 25ms
3	26ms	11ms	3 @ 26ms	{3} @ 36ms
4	75ms	49ms	4 @ 75ms
5	80ms	5ms	5 @ 80ms
6	85ms	5ms	6 @ 85ms
7	90ms	5ms	7 @ 90ms	{4,5,6,7} @ 100ms	{1,2,3,4,5,6,7} @ 190ms
8	203ms	113ms	8 @ 203ms	{8} @ 213ms	{8} @ 303ms
9	304ms	101ms	9 @ 304ms	{8} @ 308ms	{9} @ 308ms
END	308ms	4ms

The event streams stream.cluster(10) and stream.cluster(100) will produce results at different times. Note that event 0 is not received on stream.cluster(100) until 190ms after it is produced, and likewise event 4 is not received on stream.cluster(10) until 25ms after it fires.

In the worst-case scenario, a stream steadily producing events with a gap slightly shorter than the cluster interval will never produce a value! To mitigate this possibility, an optional second parameter can be provided which specifies the maximum number of events to include in a single clustered event, for example,

stream.cluster(100, 10)

The LazyList#cluster extension method expects a parameter of the contextual Timekeeping type.

Multiplexing

Multiple LazyList streams may be combined into a single stream by multiplexing them. The extension method LazyList.multiplex takes a variable number of LazyList arguments to construct a new LazyList from two or more existing LazyLists, for example:

val combinedStream = LazyList.multiplex(source1, source2, source3)

The type parameter of the resultant LazyList will be the least upper-bound of that of the input streams.

Rate-limiting

Often a stream will produce results faster than desired if it is actively consumed. The LazyList#rate method will guarantee a minimum amount of time passes between consecutive values. If the elapsed time since the previous element already exceeds the minimum, it will be yielded immediately.

For example,

LazyList.from(1).rate(100)

will count from 1, yielding approximately ten numbers per second.

Note that a rate-limited LazyList which has already been partially or completely evaluated will evaluate without any delay on subsequent reads.

Mutable Multiplexing

It may be desirable to add or remove streams from the set being multiplexed. This is possible with a Multiplexer instance, which takes two type parameters: K, the type of the keys with which streams will be associated, and T, the type of the elements in the resultant stream.

New streams may be added to the Multiplexer with the Multiplexer#add method, which takes a key and a stream, and removed with the Multiplexer#remove method, taking just the key. For example,

val multiplexer = Multiplexer[Text, Int]()
multiplexer.add(t"Fibonacci", fib(0, 1).rate(500))
multiplexer.add(t"Naturals", LazyList.from(1).rate(350))
multiplexer.stream.take(10).foreach(println(_))
multiplexer.remove(t"Fibonacci")
multiplexer.stream.take(10).foreach(println(_))
multiplexer.close()

Tap

Sometimes it's useful to have direct control over when a LazyList is yielding values and when it is "paused", using an external trigger. This functionality is provided by a Tap, a mutable object which defines two methods, open() and close(), and holds the tap's current state.

Given a LazyList[T], stream, the regulate extension method may be used to specify a Tap which can control it.

For example,

val tap = Tap()
def regulatedStream = stream.regulate(tap)

Elsewhere, perhaps in another thread, tap.close() and tap.open() may be called to pause or resume output on the LazyList. Any events which arise while the Tap is closed will be buffered, and emitted when it is re-opened. Accessing isEmpty, head or tail on the LazyList will, of course, block while the tap is closed.

Pulsar

A Pulsar provides a regular stream of Unit values and a predefined rate. It may be created simply with the pulsar extension method on the LazyList object, taking a time duration as its only parameter, for example,

LazyList.pulsar(1000L).foreach:
  unit => println("Hello")

will print Hello once per second, forever.

Status

Turbulence is classified as fledgling. For reference, Soundness projects are categorized into one of the following five stability levels:

• embryonic: for experimental or demonstrative purposes only, without any guarantees of longevity
• fledgling: of proven utility, seeking contributions, but liable to significant redesigns
• maturescent: major design decisions broady settled, seeking probatory adoption and refinement
• dependable: production-ready, subject to controlled ongoing maintenance and enhancement; tagged as version 1.0.0 or later
• adamantine: proven, reliable and production-ready, with no further breaking changes ever anticipated

Projects at any stability level, even embryonic projects, can still be used, as long as caution is taken to avoid a mismatch between the project's stability level and the required stability and maintainability of your own project.

Turbulence is designed to be small. Its entire source code currently consists of 928 lines of code.

Building

Turbulence will ultimately be built by Fury, when it is published. In the meantime, two possibilities are offered, however they are acknowledged to be fragile, inadequately tested, and unsuitable for anything more than experimentation. They are provided only for the necessity of providing some answer to the question, "how can I try Turbulence?".

1. Copy the sources into your own project

   Read the fury file in the repository root to understand Turbulence's build structure, dependencies and source location; the file format should be short and quite intuitive. Copy the sources into a source directory in your own project, then repeat (recursively) for each of the dependencies.

   The sources are compiled against the latest nightly release of Scala 3. There should be no problem to compile the project together with all of its dependencies in a single compilation.

2. Build with Wrath

   Wrath is a bootstrapping script for building Turbulence and other projects in the absence of a fully-featured build tool. It is designed to read the fury file in the project directory, and produce a collection of JAR files which can be added to a classpath, by compiling the project and all of its dependencies, including the Scala compiler itself.

   Download the latest version of wrath, make it executable, and add it to your path, for example by copying it to /usr/local/bin/.

   Clone this repository inside an empty directory, so that the build can safely make clones of repositories it depends on as peers of turbulence. Run wrath -F in the repository root. This will download and compile the latest version of Scala, as well as all of Turbulence's dependencies.

   If the build was successful, the compiled JAR files can be found in the .wrath/dist directory.

Contributing

Contributors to Turbulence are welcome and encouraged. New contributors may like to look for issues marked beginner.

We suggest that all contributors read the Contributing Guide to make the process of contributing to Turbulence easier.

Please do not contact project maintainers privately with questions unless there is a good reason to keep them private. While it can be tempting to repsond to such questions, private answers cannot be shared with a wider audience, and it can result in duplication of effort.

Author

Turbulence was designed and developed by Jon Pretty, and commercial support and training on all aspects of Scala 3 is available from Propensive OÜ.

Name

Turbulence describes multiple interacting flows, or streams, of fluids; this library makes it easier to streamline interacting streams.

In general, Soundness project names are always chosen with some rationale, however it is usually frivolous. Each name is chosen for more for its uniqueness and intrigue than its concision or catchiness, and there is no bias towards names with positive or "nice" meanings—since many of the libraries perform some quite unpleasant tasks.

Names should be English words, though many are obscure or archaic, and it should be noted how willingly English adopts foreign words. Names are generally of Greek or Latin origin, and have often arrived in English via a romance language.

Logo

The logo shows a turbulent (and colorful) vortex.

License

Turbulence is copyright © 2024 Jon Pretty & Propensive OÜ, and is made available under the Apache 2.0 License.