sealed abstract class ExecutionModel extends Product with Serializable
Specification for run-loops, imposed by the Scheduler.
When executing tasks, a run-loop can always execute tasks asynchronously (by forking logical threads), or it can always execute them synchronously (same thread and call-stack, by using an internal trampoline), or it can do a mixed mode that executes tasks in batches before forking.
The specification is considered a recommendation for how run loops should behave, but ultimately it's up to the client to choose the best execution model. This can be related to recursive loops or to events pushed into consumers.
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- ExecutionModel.scala
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Abstract Value Members
- abstract val batchedExecutionModulus: Int
Always equal to
recommendedBatchSize-1.Always equal to
recommendedBatchSize-1.Provided for convenience.
- abstract def canEqual(that: Any): Boolean
- Definition Classes
- Equals
- abstract def nextFrameIndex(current: Int): Int
Returns the next frame index in the run-loop.
Returns the next frame index in the run-loop.
If the returned integer is zero, then the next cycle in the run-loop should execute asynchronously.
- abstract def productArity: Int
- Definition Classes
- Product
- abstract def productElement(n: Int): Any
- Definition Classes
- Product
- abstract val recommendedBatchSize: Int
Recommended batch size used for breaking synchronous loops in asynchronous batches.
Recommended batch size used for breaking synchronous loops in asynchronous batches. When streaming value from a producer to a synchronous consumer it's recommended to break the streaming in batches as to not hold the current thread or run-loop indefinitely.
This is rounded to the next power of 2, because then for applying the modulo operation we can just do:
val modulus = recommendedBatchSize - 1 // ... nr = (nr + 1) & modulus
For the JVM the default value can be adjusted with:
java -Dmonix.environment.batchSize=2048 \ ...
This is the API documentation for the Monix library.
Package Overview
monix.execution exposes lower level primitives for dealing with asynchronous execution:
Atomictypes, as alternative tojava.util.concurrent.atomicmonix.catnap exposes pure abstractions built on top of the Cats-Effect type classes:
monix.eval is for dealing with evaluation of results, thus exposing Task and Coeval.
monix.reactive exposes the
Observablepattern:Observableimplementationsmonix.tail exposes Iterant for purely functional pull based streaming:
BatchandBatchCursor, the alternatives to Scala'sIterableandIteratorrespectively that we are using within Iterant's encodingYou can control evaluation with type you choose - be it Task, Coeval, cats.effect.IO or your own as long as you provide correct cats-effect or cats typeclass instance.