Github user BryanCutler commented on the issue:
https://github.com/apache/spark/pull/18281
@ajaysaini725 , I was just about to update my PR with an updated trait that
makes some small improvements when I saw you're update. I'll post what I have
in case if you would like to use it here
```scala
private[ml] trait HasParallelism extends Params {
/**
* param to control the level of parallelism
* Default: 1
*
* @group expertParam
*/
val parallelism: IntParam = new IntParam(this, "parallelism",
"set the level of parallelism to be used", ParamValidators.gtEq(1))
/** @group getParam */
@Since("2.3.0")
def getParallelism: Int = $(parallelism)
/** @group setParam */
@Since("2.3.0")
def setNumParallelEval(value: Int): this.type = set(parallelism, value)
/**
* Create an ExecutionContext that is determined from the param
[parallelism]. If this param
* is set to 1, a same-thread executor will be used to run in serial
otherwise a thread-pool
* with max threads set to the param value.
*/
@Since("2.3.0")
def getExecutionContext(maxThreads: Int): ExecutionContext = {
maxThreads match {
case 1 =>
ThreadUtils.sameThread
case n =>
ExecutionContext.fromExecutorService(
ThreadUtils.newDaemonCachedThreadPool(s"${this.getClass.getSimpleName}-thread-pool",
n))
}
}
setDefault(parallelism -> 1)
}
```
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