golem-parallel-workers-scala
Agent BuildingFan out work to multiple parallel agents and collect results in a Scala Golem project. Use when the user asks about parallel execution, fan-out/fan-in, spawning child agents for parallel work, forking, or aggregating results from multiple agents.
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Parallel Workers — Fan-Out / Fan-In (Scala)
Overview
Golem agents process invocations sequentially — a single agent cannot run work in parallel. To execute work concurrently, distribute it across multiple agent instances. This skill covers two approaches:
- Child agents via codegen-generated
XClient.get(id)— spawn separate agent instances, dispatch work, and collect results HostApi.fork()— clone the current agent at the current execution point for lightweight parallel execution
Approach 1: Child Agent Fan-Out
Spawn child agents, dispatch work, and collect results using Future.sequence or Golem promises.
Basic Pattern with Future.sequence
import golem.*
import golem.runtime.annotations.{agentDefinition, agentImplementation}
import scala.concurrent.Future
import scala.scalajs.concurrent.JSExecutionContext.Implicits.queue
@agentDefinition()
trait Coordinator extends BaseAgent {
class Id()
def fanOut(items: List[String]): Future[List[String]]
}
@agentImplementation()
class CoordinatorImpl() extends Coordinator {
override def fanOut(items: List[String]): Future[List[String]] = {
// Spawn one child per item and call concurrently
val futures = items.zipWithIndex.map { case (item, i) =>
val child = WorkerClient.get(i)
child.process(item)
}
// Wait for all children to finish
Future.sequence(futures)
}
}
@agentDefinition()
trait Worker extends BaseAgent {
class Id(val id: Int)
def process(data: String): Future[String]
}
@agentImplementation()
class WorkerImpl(private val id: Int) extends Worker {
override def process(data: String): Future[String] = {
Future.successful(s"processed-$data")
}
}
Fire-and-Forget with Promise Collection
For long-running work, trigger children with fire-and-forget and collect results via Golem promises:
import golem.HostApi
import golem.HostApi.PromiseId
import zio.blocks.schema.Schema
case class WorkResult(value: String) derives Schema
@agentImplementation()
class CoordinatorImpl() extends Coordinator {
override def dispatchAndCollect(regions: List[String]): Future[List[String]] = {
// Create one promise per child
val promiseIds = regions.map(_ => HostApi.createPromise())
// Fire-and-forget: trigger each child with its promise ID
regions.zip(promiseIds).foreach { case (region, pid) =>
val child = RegionWorkerClient.get(region)
child.runReport.trigger(pid)
}
// Collect all results (agent suspends on each until completed)
val futures = promiseIds.map { pid =>
HostApi.awaitPromiseJson[WorkResult](pid).map(_.value)
}
Future.sequence(futures)
}
}
@agentImplementation()
class RegionWorkerImpl(private val region: String) extends RegionWorker {
override def runReport(promiseId: PromiseId): Future[Unit] = {
val result = WorkResult(s"Report for $region: OK")
HostApi.completePromiseJson(promiseId, result)
Future.successful(())
}
}
Chunked Fan-Out
Batch children to limit concurrency:
override def fanOutChunked(items: List[String]): Future[List[String]] = {
val chunks = items.grouped(5).toList
chunks.foldLeft(Future.successful(List.empty[String])) { (accFut, chunk) =>
accFut.flatMap { acc =>
val futures = chunk.zipWithIndex.map { case (item, i) =>
WorkerClient.get(i).process(item)
}
Future.sequence(futures).map(acc ++ _)
}
}
}
Error Handling
Use Future.traverse with recover for partial failure handling:
override def fanOutWithErrors(items: List[String]): Future[(List[String], List[String])] = {
val futures = items.zipWithIndex.map { case (item, i) =>
WorkerClient.get(i).process(item)
.map(Right(_))
.recover { case e: Throwable => Left(s"Item $item failed: ${e.getMessage}") }
}
Future.sequence(futures).map { results =>
val successes = results.collect { case Right(v) => v }
val failures = results.collect { case Left(e) => e }
(successes, failures)
}
}
Approach 2: HostApi.fork()
HostApi.fork() clones the current agent at the current execution point, creating a new agent instance with the same state but a unique phantom ID. Use Golem promises to synchronize between the original and forked agents.
Basic Fork Pattern
import golem.HostApi
import golem.HostApi.{ForkResult, PromiseId}
override def parallelCompute(): Future[String] = {
val promiseId = HostApi.createPromise()
HostApi.fork() match {
case ForkResult.Original(_) =>
// Wait for the forked agent to complete the promise
HostApi.awaitPromise(promiseId).map { bytes =>
val forkedResult = new String(bytes, "UTF-8")
s"Combined: original + $forkedResult"
}
case ForkResult.Forked(_) =>
// Do work in the forked copy
val result = "forked-result"
HostApi.completePromise(promiseId, result.getBytes("UTF-8"))
Future.successful("forked done") // Only seen by the forked agent
}
}
Multi-Fork Fan-Out
Fork multiple times for N-way parallelism:
override def multiFork(n: Int): Future[List[String]] = {
val promiseIds = (0 until n).map(_ => HostApi.createPromise()).toList
for (i <- 0 until n) {
HostApi.fork() match {
case ForkResult.Original(_) =>
// Continue to next fork
case ForkResult.Forked(_) =>
// Each forked agent does its slice of work
val output = s"result-from-fork-$i"
HostApi.completePromise(promiseIds(i), output.getBytes("UTF-8"))
return Future.successful(Nil) // Forked agent exits here
}
}
// Original agent collects all results
val futures = promiseIds.map { pid =>
HostApi.awaitPromise(pid).map(bytes => new String(bytes, "UTF-8"))
}
Future.sequence(futures)
}
When to Use Which Approach
| Criteria | Child Agents | HostApi.fork() |
|---|---|---|
| Work is independent and stateless | ✅ Best fit | Works but overkill |
| Need to share current state with workers | ❌ Must pass via args | ✅ Forked copy inherits state |
| Workers need persistent identity | ✅ Each has own ID | ❌ Forked agents are ephemeral phantoms |
| Number of parallel tasks is dynamic | ✅ Spawn as many as needed | ✅ Fork in a loop |
| Need simple error isolation | ✅ Child failure doesn't crash parent | ⚠️ Forked agent shares oplog lineage |
Key Points
- No threads: Golem is single-threaded per agent — parallelism is achieved by distributing across agent instances
- Durability: All RPC calls, promises, and fork operations are durably recorded — work survives crashes
- Deadlock avoidance: Never have two agents awaiting each other synchronously — use
.triggerto break cycles - Cleanup: Child agents persist after the coordinator finishes; delete them explicitly if they hold unwanted state
- Aggregation: Use
Future.sequenceto collect results from multipleFutures, or iterate over promise IDs withHostApi.awaitPromise/awaitPromiseJson