Facilitates parallel operations like map and reduce on collections using coroutines, enhancing performance with chunked operations for efficient multithreading and data locality benefits.
Parallel map, reduce, and various indexed and in-place operations on collections for Kotlin Multiplatform using coroutines.
The parallel map implementation is called .mapParallel(). It is implemented like this.
suspend fun <T, R> Iterable<T>.mapParallel(transform: (T) -> R): List<R> = coroutineScope {
map { async { transform(it) } }.map { it.await() }
}
Example of using the parallel map operation.
fun showCase() {
val list = listOf(1,2,3)
runBlocking(Dispatchers.Default) {
var mappedList = list.mapParallel { it * 2 } // Results in [2,4,6]
}
}
There is also the parallel reduce operation with chunked variations, which can be used to perform associative operations on a collection, like sum.
Note: If you want to achieve multithreading, make sure to run the coroutine with the Default dispatcher.
Chunked operations improve performance since they split the collection into just a couple of segments, which are processed each by a single thread. That benefits from data locality and lesser thread management. It is particularly useful (pretty much needed for operations like sum) in the reduce operation when using multithreading, since each thread takes one chunk that it reduces on its own. After all coroutines finish, their results are then reduced again to the final result.
The library is published in the Maven Central repository. Include this line in your module build.gradle file.
dependencies {
implementation("io.github.cvb941:kotlin-parallel-operations:2.0.0")
}
In the future, I would like other transformation functions to be implemented.
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