final class AsyncScheduler extends ReferenceScheduler with BatchingScheduler
An AsyncScheduler
schedules tasks to happen in the future with the
given ScheduledExecutorService
and the tasks themselves are executed on
the given ExecutionContext
.
- Source
- AsyncScheduler.scala
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- AsyncScheduler
- BatchingScheduler
- ReferenceScheduler
- Scheduler
- Executor
- UncaughtExceptionReporter
- Serializable
- ExecutionContext
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- final def asInstanceOf[T0]: T0
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- Any
- def clockMonotonic(unit: TimeUnit): Long
Returns a monotonic clock measurement, if supported by the underlying platform.
Returns a monotonic clock measurement, if supported by the underlying platform.
This is the pure equivalent of Java's
System.nanoTime
, or ofCLOCK_MONOTONIC
from Linux'sclock_gettime()
.timer.clockMonotonic(NANOSECONDS)
The returned value can have nanoseconds resolution and represents the number of time units elapsed since some fixed but arbitrary origin time. Usually this is the Unix epoch, but that's not a guarantee, as due to the limits of
Long
this will overflow in the future (263 is about 292 years in nanoseconds) and the implementation reserves the right to change the origin.The return value should not be considered related to wall-clock time, the primary use-case being to take time measurements and compute differences between such values, for example in order to measure the time it took to execute a task.
As a matter of implementation detail, Monix's
Scheduler
implementations useSystem.nanoTime
and the JVM will useCLOCK_MONOTONIC
when available, instead ofCLOCK_REALTIME
(seeclock_gettime()
on Linux) and it is up to the underlying platform to implement it correctly.And be warned, there are platforms that don't have a correct implementation of
CLOCK_MONOTONIC
. For example at the moment of writing there is no standard way for such a clock on top of JavaScript and the situation isn't so clear cut for the JVM either, see:- bug report
- concurrency-interest discussion on the X86 tsc register
The JVM tries to do the right thing and at worst the resolution and behavior will be that of
System.currentTimeMillis
.The recommendation is to use this monotonic clock when doing measurements of execution time, or if you value monotonically increasing values more than a correspondence to wall-time, or otherwise prefer clockRealTime.
- Definition Classes
- ReferenceScheduler → Scheduler
- def clockRealTime(unit: TimeUnit): Long
Returns the current time, as a Unix timestamp (number of time units since the Unix epoch).
Returns the current time, as a Unix timestamp (number of time units since the Unix epoch).
This is the equivalent of Java's
System.currentTimeMillis
, or ofCLOCK_REALTIME
from Linux'sclock_gettime()
.The provided
TimeUnit
determines the time unit of the output, its precision, but not necessarily its resolution, which is implementation dependent. For example this will return the number of milliseconds since the epoch:import scala.concurrent.duration.MILLISECONDS scheduler.clockRealTime(MILLISECONDS)
N.B. the resolution is limited by the underlying implementation and by the underlying CPU and OS. If the implementation uses
System.currentTimeMillis
, then it can't have a better resolution than 1 millisecond, plus depending on underlying runtime (e.g. Node.js) it might return multiples of 10 milliseconds or more.See clockMonotonic, for fetching a monotonic value that may be better suited for doing time measurements.
- Definition Classes
- ReferenceScheduler → Scheduler
- def clone(): AnyRef
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- protected[lang]
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- final def execute(runnable: Runnable): Unit
Schedules the given
command
for execution at some time in the future.Schedules the given
command
for execution at some time in the future.The command may execute in a new thread, in a pooled thread, in the calling thread, basically at the discretion of the Scheduler implementation.
- Definition Classes
- BatchingScheduler → Scheduler → Executor → ExecutionContext
- def executeAsync(runnable: Runnable): Unit
- Attributes
- protected
- Definition Classes
- AsyncScheduler → BatchingScheduler
- val executionModel: ExecutionModel
The ExecutionModel is a specification of how run-loops and producers should behave in regards to executing tasks either synchronously or asynchronously.
The ExecutionModel is a specification of how run-loops and producers should behave in regards to executing tasks either synchronously or asynchronously.
- Definition Classes
- AsyncScheduler → Scheduler
- val features: Features
Exposes a set of flags that describes the Scheduler's features.
Exposes a set of flags that describes the Scheduler's features.
- Definition Classes
- AsyncScheduler → Scheduler
- def finalize(): Unit
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- protected[lang]
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- @throws(classOf[java.lang.Throwable])
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- final def notify(): Unit
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- final def notifyAll(): Unit
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- @native()
- def reportFailure(t: Throwable): Unit
Reports that an asynchronous computation failed.
Reports that an asynchronous computation failed.
- Definition Classes
- AsyncScheduler → Scheduler → UncaughtExceptionReporter → ExecutionContext
- def scheduleAtFixedRate(initialDelay: Long, period: Long, unit: TimeUnit, r: Runnable): Cancelable
Schedules a periodic task that becomes enabled first after the given initial delay, and subsequently with the given period.
Schedules a periodic task that becomes enabled first after the given initial delay, and subsequently with the given period. Executions will commence after
initialDelay
theninitialDelay + period
, theninitialDelay + 2 * period
and so on.If any execution of the task encounters an exception, subsequent executions are suppressed. Otherwise, the task will only terminate via cancellation or termination of the scheduler. If any execution of this task takes longer than its period, then subsequent executions may start late, but will not concurrently execute.
For example the following schedules a message to be printed to standard output approximately every 10 seconds with an initial delay of 5 seconds:
val task = scheduler.scheduleAtFixedRate(5, 10, TimeUnit.SECONDS, new Runnable { def run() = print("Repeated message") }) // later if you change your mind ... task.cancel()
- initialDelay
is the time to wait until the first execution happens
- period
is the time to wait between 2 successive executions of the task
- unit
is the time unit used for the
initialDelay
and theperiod
parameters- r
is the callback to be executed
- returns
a cancelable that can be used to cancel the execution of this repeated task at any time.
- Definition Classes
- ReferenceScheduler → Scheduler
- def scheduleOnce(initialDelay: Long, unit: TimeUnit, r: Runnable): Cancelable
Schedules a task to run in the future, after
initialDelay
.Schedules a task to run in the future, after
initialDelay
.For example the following schedules a message to be printed to standard output after 5 minutes:
val task = scheduler.scheduleOnce(5, TimeUnit.MINUTES, new Runnable { def run() = print("Hello, world!") }) // later if you change your mind ... task.cancel()
- initialDelay
is the time to wait until the execution happens
- unit
is the time unit used for
initialDelay
- r
is the callback to be executed
- returns
a
Cancelable
that can be used to cancel the created task before execution.
- Definition Classes
- AsyncScheduler → Scheduler
- def scheduleWithFixedDelay(initialDelay: Long, delay: Long, unit: TimeUnit, r: Runnable): Cancelable
Schedules for execution a periodic task that is first executed after the given initial delay and subsequently with the given delay between the termination of one execution and the commencement of the next.
Schedules for execution a periodic task that is first executed after the given initial delay and subsequently with the given delay between the termination of one execution and the commencement of the next.
For example the following schedules a message to be printed to standard output every 10 seconds with an initial delay of 5 seconds:
val task = s.scheduleWithFixedDelay(5, 10, TimeUnit.SECONDS, new Runnable { def run() = print("Repeated message") }) // later if you change your mind ... task.cancel()
- initialDelay
is the time to wait until the first execution happens
- delay
is the time to wait between 2 successive executions of the task
- unit
is the time unit used for the
initialDelay
and thedelay
parameters- r
is the callback to be executed
- returns
a cancelable that can be used to cancel the execution of this repeated task at any time.
- Definition Classes
- ReferenceScheduler → Scheduler
- final def synchronized[T0](arg0: => T0): T0
- Definition Classes
- AnyRef
- def toString(): String
- Definition Classes
- AnyRef → Any
- final def wait(): Unit
- Definition Classes
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- Annotations
- @throws(classOf[java.lang.InterruptedException])
- final def wait(arg0: Long, arg1: Int): Unit
- Definition Classes
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- @throws(classOf[java.lang.InterruptedException])
- final def wait(arg0: Long): Unit
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- def withExecutionModel(em: ExecutionModel): AsyncScheduler
Given a function that will receive the underlying ExecutionModel, returns a new Scheduler reference, based on the source, that exposes the transformed
ExecutionModel
when queried by means of the executionModel property.Given a function that will receive the underlying ExecutionModel, returns a new Scheduler reference, based on the source, that exposes the transformed
ExecutionModel
when queried by means of the executionModel property.This method enables reusing global scheduler references in a local scope, but with a slightly modified execution model to inject.
The contract of this method (things you can rely on):
- the source
Scheduler
must not be modified in any way - the implementation should wrap the source efficiently, such that the
result mirrors the source
Scheduler
in every way except for the execution model
Sample:
import monix.execution.Scheduler.global implicit val scheduler = { val em = global.executionModel global.withExecutionModel(em.withAutoCancelableLoops(true)) }
- Definition Classes
- AsyncScheduler → ReferenceScheduler → Scheduler
- the source
- def withUncaughtExceptionReporter(r: UncaughtExceptionReporter): Scheduler
Returns a new
Scheduler
that piggybacks on this, but uses the given exception reporter for reporting uncaught errors.Returns a new
Scheduler
that piggybacks on this, but uses the given exception reporter for reporting uncaught errors.Sample:
import monix.execution.Scheduler.global import monix.execution.UncaughtExceptionReporter implicit val scheduler = { val r = UncaughtExceptionReporter { e => e.printStackTrace() } global.withUncaughtExceptionReporter(r) }
- Definition Classes
- ReferenceScheduler → Scheduler
Deprecated Value Members
- def prepare(): ExecutionContext
- Definition Classes
- ExecutionContext
- Annotations
- @deprecated
- Deprecated
(Since version 2.12.0) preparation of ExecutionContexts will be removed
This is the API documentation for the Monix library.
Package Overview
monix.execution exposes lower level primitives for dealing with asynchronous execution:
Atomic
types, as alternative tojava.util.concurrent.atomic
monix.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
Observable
pattern:Observable
implementationsmonix.tail exposes Iterant for purely functional pull based streaming:
Batch
andBatchCursor
, the alternatives to Scala'sIterable
andIterator
respectively 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.