Implicits
Related Doc:
package concurrent
A global Scheduler instance, provided for convenience, piggy-backing
on top of Scala's own concurrent.ExecutionContext.global, which is a
ForkJoinPool.
A global Scheduler instance, provided for convenience, piggy-backing
on top of Scala's own concurrent.ExecutionContext.global, which is a
ForkJoinPool.
It can be tuned by setting the following JVM system properties:
- "scala.concurrent.context.minThreads" an integer specifying the minimum number of active threads in the pool
- "scala.concurrent.context.maxThreads" an integer specifying the maximum number of active threads in the pool
- "scala.concurrent.context.numThreads" can be either an integer,
specifying the parallelism directly or a string with the format "xNUM"
(e.g. "x1.5") specifying the multiplication factor of the number of
available processors (taken with Runtime.availableProcessors)
The formula for calculating the parallelism in our pool is
min(maxThreads, max(minThreads, numThreads)).
To set a system property from the command line, a JVM parameter must be
given to the java command as -Dname=value. So as an example, to customize
this global scheduler, we could start our process like this:
java -Dscala.concurrent.context.minThreads=2 \
-Dscala.concurrent.context.maxThreads=30 \
-Dscala.concurrent.context.numThreads=x1.5 \
...
As a note, this being backed by Scala's own global execution context,
it is cooperating with Scala's BlockContext, so when operations marked
with scala.concurrent.blocking are encountered, the thread-pool may
decide to add extra threads in the pool. However this is not a thread-pool
that is optimal for doing blocking operations, so for example if you want
to do a lot of blocking I/O, then use a Scheduler backed by a
thread-pool that is more optimal for blocking. See for example
Scheduler.io.
Defines implicit values that can be used by importing in the current context.
Example:
import monifu.concurrent.Implicits.globalScheduler