CompletableFuture: Await percentage complete

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I am writing identical data in parallel to n nodes of a distributed system.
When n% of these nodes have been written to successfully, the remaining writes to the other nodes are unimportant as n% guarantees replication between the other nodes.

Java's CompletableFuture seems to have very close to what I want eg:

CompletableFuture.anyOf()

(Returns when the first future is complete) - avoids waiting unnecessarily, but returns too soon as I require n% completions

CompletableFuture.allOf()

(Returns when all futures complete) - avoids returning too soon but waits unnecessarily for 100% completion

I am looking for a way to return when a specific percentage of futures have completed. For example if I supply 10 futures, return when 6 or 60% of these complete successfully.

For example, Bluebird JS has this feature with

Promise.some(promises, countThatNeedToComplete)

I was wondering if I could do something similar with TheadExecutor or vanilla CompletableFuture in java

completable-future percentage future parallel-processing java
1 Answers

I believe you can achieve what you want using only what's already provided by CompletableFuture, but you'll have to implement additional control to know how many future tasks were already completed and, when you reach the number/percentage that you need, cancel the remaining tasks.

Below is a class to illustrate the idea:

public class CompletableSome<T>
{
private List<CompletableFuture<Void>> tasks;
private int tasksCompleted = 0;

public CompletableSome(List<CompletableFuture<T>> tasks, int percentOfTasksThatMustComplete)
{
    int minTasksThatMustComplete = tasks.size() * percentOfTasksThatMustComplete / 100;
    System.out.println(
        String.format("Need to complete at least %s%% of the %s tasks provided, which means %s tasks.",
            percentOfTasksThatMustComplete, tasks.size(), minTasksThatMustComplete));

    this.tasks = new ArrayList<>(tasks.size());
    for (CompletableFuture<?> task : tasks)
    {
        this.tasks.add(task.thenAccept(a -> {
            // thenAccept will be called right after the future task is completed. At this point we'll
            // check if we reached the minimum number of nodes needed. If we did, then complete the 
            // remaining tasks since they are no longer needed.
            tasksCompleted++;
            if (tasksCompleted >= minTasksThatMustComplete)
            {
                tasks.forEach(t -> t.complete(null));
            }
        }));
    }
}

public void execute()
{
    CompletableFuture.allOf(tasks.toArray(new CompletableFuture<?>[0])).join();
}
}

You would use this class as in the example below:

public static void main(String[] args)
{
    int numberOfNodes = 4;

    // Create one future task for each node.
    List<CompletableFuture<String>> nodes = new ArrayList<>();
    for (int i = 1; i <= numberOfNodes; i++)
    {
        String nodeId = "result" + i;
        nodes.add(CompletableFuture.supplyAsync(() -> {
            try
            {
                // Sleep for some time to avoid all tasks to complete before the count is checked.
                Thread.sleep(100 + new Random().nextInt(500));
            }
            catch (InterruptedException e)
            {
                e.printStackTrace();
            }

            // The action here is just to print the nodeId, you would make the actual call here.
            System.out.println(nodeId + " completed.");
            return nodeId;
        }));
    }

    // Here we're saying that just 75% of the nodes must be called successfully.
    CompletableSome<String> tasks = new CompletableSome<>(nodes, 75);
    tasks.execute();
}

Please note that with this solution you could end up executing more tasks than the minimum required -- for instance, when two or more nodes respond almost simultaneously, you may reach the minimum required count when the first node responds, but there will be no time to cancel the other tasks. If that's an issue, then you'd have to implement even more controls.

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