/* * DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER. * * This code is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 2 only, as * published by the Free Software Foundation. Oracle designates this * particular file as subject to the "Classpath" exception as provided * by Oracle in the LICENSE file that accompanied this code. * * This code is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * version 2 for more details (a copy is included in the LICENSE file that * accompanied this code). * * You should have received a copy of the GNU General Public License version * 2 along with this work; if not, write to the Free Software Foundation, * Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA. * * Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA * or visit www.oracle.com if you need additional information or have any * questions. */ /* * This file is available under and governed by the GNU General Public * License version 2 only, as published by the Free Software Foundation. * However, the following notice accompanied the original version of this * file: * * Written by Doug Lea with assistance from members of JCP JSR-166 * Expert Group and released to the public domain, as explained at * http://creativecommons.org/publicdomain/zero/1.0/ */ package java.util.concurrent; /** * A recursive result-bearing {@link ForkJoinTask}. * *
For a classic example, here is a task computing Fibonacci numbers: * *
{@code
* class Fibonacci extends RecursiveTask {
* final int n;
* Fibonacci(int n) { this.n = n; }
* Integer compute() {
* if (n <= 1)
* return n;
* Fibonacci f1 = new Fibonacci(n - 1);
* f1.fork();
* Fibonacci f2 = new Fibonacci(n - 2);
* return f2.compute() + f1.join();
* }
* }}
*
* However, besides being a dumb way to compute Fibonacci functions
* (there is a simple fast linear algorithm that you'd use in
* practice), this is likely to perform poorly because the smallest
* subtasks are too small to be worthwhile splitting up. Instead, as
* is the case for nearly all fork/join applications, you'd pick some
* minimum granularity size (for example 10 here) for which you always
* sequentially solve rather than subdividing.
*
* @since 1.7
* @author Doug Lea
*/
public abstract class RecursiveTask