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root/jsr166/jsr166/src/jsr166y/RecursiveTask.java
Revision: 1.6
Committed: Wed Jul 22 19:04:11 2009 UTC (14 years, 9 months ago) by dl
Branch: MAIN
Changes since 1.5: +0 -6 lines
Log Message:
Add ForkJoinTask.inForkJoinPool; other misc

File Contents

# Content
1 /*
2 * Written by Doug Lea with assistance from members of JCP JSR-166
3 * Expert Group and released to the public domain, as explained at
4 * http://creativecommons.org/licenses/publicdomain
5 */
6
7 package jsr166y;
8
9 /**
10 * Recursive result-bearing ForkJoinTasks.
11 * <p> For a classic example, here is a task computing Fibonacci numbers:
12 *
13 * <pre> {@code
14 * class Fibonacci extends RecursiveTask<Integer> {
15 * final int n;
16 * Fibonacci(int n) { this.n = n; }
17 * Integer compute() {
18 * if (n <= 1)
19 * return n;
20 * Fibonacci f1 = new Fibonacci(n - 1);
21 * f1.fork();
22 * Fibonacci f2 = new Fibonacci(n - 2);
23 * return f2.compute() + f1.join();
24 * }
25 * }}</pre>
26 *
27 * However, besides being a dumb way to compute Fibonacci functions
28 * (there is a simple fast linear algorithm that you'd use in
29 * practice), this is likely to perform poorly because the smallest
30 * subtasks are too small to be worthwhile splitting up. Instead, as
31 * is the case for nearly all fork/join applications, you'd pick some
32 * minimum granularity size (for example 10 here) for which you always
33 * sequentially solve rather than subdividing.
34 *
35 * @since 1.7
36 * @author Doug Lea
37 */
38 public abstract class RecursiveTask<V> extends ForkJoinTask<V> {
39
40 /**
41 * The result returned by compute method.
42 */
43 V result;
44
45 /**
46 * The main computation performed by this task.
47 */
48 protected abstract V compute();
49
50 public final V getRawResult() {
51 return result;
52 }
53
54 protected final void setRawResult(V value) {
55 result = value;
56 }
57
58 /**
59 * Implements execution conventions for RecursiveTask
60 */
61 protected final boolean exec() {
62 result = compute();
63 return true;
64 }
65
66 }