mtumilowicz/java11-stream-completablefuture-dedicated-executor

Implementation of dedicated executor for parallel processing of completable future tasks.

java11-stream-completablefuture-dedicated-executor

Reference: https://www.amazon.com/Modern-Java-Action-functional-programming/dp/1617293563

project description

1. We could ask shop for a price of a product (by its id)

   class Shop {
       Price getPrice(int id) {
           Delay.delay();
           return Price.of(id);
       }
   }
   

2. Shop answers with some delay (200 ms)

   class Delay {
       static void delay() {
           try {
               Thread.sleep(200);
           } catch (InterruptedException e) {
               // not used
           }
       }
   }
   

3. we want to ask shop for many ids (for example we have a stream of ids)

solution

• naive approach - scales badly
  • one product

    var priceFutures = IntStream.range(1, 2)
            .parallel()
            .mapToObj(id -> CompletableFuture.supplyAsync(
                    () -> shop.getPrice(id)))
            .collect(toList());
    
    var prices = priceFutures.stream()
            .parallel()
            .map(CompletableFuture::join)
            .collect(toList());
    

    time: 203 ms
  • four products

    var priceFutures = IntStream.range(1, 4)
            .parallel()
            .mapToObj(id -> CompletableFuture.supplyAsync(
                    () -> shop.getPrice(id)))
            .collect(toList());
    
    var prices = priceFutures.stream()
            .parallel()
            .map(CompletableFuture::join)
            .collect(toList());
    

    time: 203 ms
  • many products

    var priceFutures = IntStream.range(1, 30)
            .parallel()
            .mapToObj(id -> CompletableFuture.supplyAsync(
                    () -> shop.getPrice(id)))
            .collect(toList());
    
    var prices = priceFutures.stream()
            .parallel()
            .map(CompletableFuture::join)
            .collect(toList());
    

    time: 2 s
• dedicated executor - scales perfectly

  var size = 300;
      
  var executor =
          Executors.newFixedThreadPool(Math.min(size, 100),
                  r -> {
                      Thread t = new Thread(r);
                      t.setDaemon(true);
                      return t;
                  });
  
  var priceFutures = IntStream.range(1, size)
          .parallel()
          .mapToObj(id -> CompletableFuture.supplyAsync(
                  () -> shop.getPrice(id), executor))
          .collect(toList());
  
  var prices = priceFutures.parallelStream()
          .map(CompletableFuture::join)
          .collect(toList());
  

  time: 668 ms

explanation

CompletableFuture and parallel streams internally use the same common pool that by default has a fixed number of threads equal to the one returned by Runtime.getRuntime().availableProcessors().

So we decide to prepare dedicated executor for CompletableFuture tasks. How we estimated the number of threads in a fixed pool? From the given formula:

• Nthreads = NCPU * UCPU * (1 + W/C)
  • NCPU is the number of cores, available through Runtime.getRuntime().availableProcessors()
  • UCPU is the target CPU utilization (between 0 and 1), and
  • W/C is the ratio of wait time to compute time