Sources Contact Advanced Search Tutorials

An Interest In:

Web News this Week

Search Archive

Some of Our Sources

View All Sources

Help Webnuz

Referal links:

September 13, 2022 10:09 pm GMT

Improve Performance with CompletableFuture in Java

Completable Futures

Repository : https://github.com/jorgetovar/completable_futures

Do you know that parallel stream in Java has performance limitations due to Java will use the number of available processors?

If you want to take advance of the latest Java features and overcome this problem, use CompletableFuture.

You can create a ThreadPool greater than the number of available processors and reap the performance improvements.
CompletableFuture uses lambdas, and the code is expressive.

My machine has 8 processors

   @Test    public void numberOfProcessors() {        assertThat(availableProcessors, is(equalTo(8)));    }

1 Second: CompletableFuture implementation has the best performance

    @Test    public void completableFuture_whenBooksAreMoreThanNumberOfProcessors() {        Executor executor = Executors.newFixedThreadPool(10);        long start = System.currentTimeMillis();        var futureCategories = getBooks()                .map(e -> CompletableFuture.supplyAsync(() -> BookClassifier.apply(e), executor))                .toList();        var categories = futureCategories.stream()                .map(CompletableFuture::join).toList();        int timeInSeconds = getTimeInSeconds(start);        assertThat(categories.size(), is(equalTo(10)));        assertThat(timeInSeconds, OrderingComparison.greaterThanOrEqualTo(1));        assertThat(timeInSeconds, OrderingComparison.lessThanOrEqualTo(1));    }

2 Seconds: Parallel Stream implementation has some limitations

Because our current limitation would have to process 8 books first and then 2 more

    @Testpublic void parallelStream_whenBooksAreMoreThanNumberOfProcessors() {        long start = System.currentTimeMillis();        var categories = getBooks()        .parallel()        .map(BookClassifier::apply)        .toList();        int timeInSeconds = getTimeInSeconds(start);        assertThat(categories.size(), is(equalTo(10)));        assertThat(timeInSeconds, OrderingComparison.greaterThanOrEqualTo(2));        assertThat(timeInSeconds, OrderingComparison.lessThanOrEqualTo(2));        }

1 Second: Parallel Stream implementation within the limitations

Because we are within the limit of the available processors

    @Test    public void parallelStream_whenBooksAreLessThanNumberOfProcessors() {        int limit = availableProcessors - 1;        long start = System.currentTimeMillis();        var categories = getBooks()                .limit(limit)                .parallel()                .map(BookClassifier::apply)                .toList();        int timeInSeconds = getTimeInSeconds(start);        System.out.printf("The operation took %s ms%n", timeInSeconds - start);        assertThat(categories.size(), is(equalTo(limit)));        assertThat(timeInSeconds, OrderingComparison.greaterThanOrEqualTo(1));        assertThat(timeInSeconds, OrderingComparison.lessThanOrEqualTo(1));    }

10 Seconds: Stream Synchronous implementation has the worst performance

   @Test   public void stream_whenBooksAreLessThanNumberOfProcessors() {        long start = System.currentTimeMillis();        var categories = getBooks()        .map(BookClassifier::apply).toList();        int timeInSeconds = getTimeInSeconds(start);        assertThat(categories.size(), is(equalTo(10)));        assertThat(timeInSeconds, OrderingComparison.greaterThanOrEqualTo(9));        assertThat(timeInSeconds, OrderingComparison.lessThanOrEqualTo(10));        System.out.printf("The stream operation took %s ms%n", timeInSeconds);        }

Original Link: https://dev.to/jorgetovar/improve-performance-with-completablefuture-in-java-1jb6

Share this article:

View Full Article

Dev To

An online community for sharing and discovering great ideas, having debates, and making friends

More About this Source Visit Dev To