Applying coroutines for asynchronous data processing

In this recipe, we are going to implement a generic extension for the Iterable type, which will provide a replacement for the Iterable<T>.map() function. Our implementation of the Iterable<T>.mapConcurrent() function is going to allow data-mapping-operation optimization by running it concurrently with coroutines. Next, we are going to test our concurrent mapping function implementation by employing it to perform a simulation of a time-expensive operation applied to each of the elements of a sample Iterable object.

How to do it...

1. Implement an extension function for the generic Iterable<T> class responsible for handling the mapping operation of its elements concurrently:

suspend fun <T, R> Iterable<T>.mapConcurrent(transform: suspend (T) -> R) =
this.map {
async { transform(it) }
    }.map {
        it.await()
}

2. Simulate time-consuming mapping operations applied to the sample Iterable range elements:

runBlocking...