Fork/Join框架是Java7提供了的一个用于并行执行任务的框架, 是一个把大任务分割成若干个小任务,最终汇总每一个小任务结果后获得大任务结果的框架html
在平常的业务需求中,常常出现的批量查询,批量写入等接口的提供,通常来讲,最简单最low的方式就是写一个for循环来一次执行,可是当业务方对接口的性能要求较高时,就比较尴尬了java
一般能够想到的方式是采用并发操做,首先想到能够实现的方式就是利用线程池来作数组
一般实现方式以下并发
// 1. 建立线程池 ExecutorService executorService = new ThreadPoolExecutor(3, 5, 60, TimeUnit.SECONDS, new LinkedBlockingDeque<Runnable>(10), new DefaultThreadFactory("biz-exec"), new ThreadPoolExecutor.CallerRunsPolicy()); // 2. 建立执行任务 List<Future<Object>> futureList = new ArrayList<>(); for(Object arg : list) { futureList.add(executorService.submit(new Callable<Object>() { @Override public Object call() throws Exception { // xxx } })); } // 3. 结果获取 for(Future f: futureList) { Object obj = f.get(); }
用上面的这种方式并无什么问题,咱们接下来考虑的是如何使用ForkJoin框架来实现相似的功能框架
Fork: 将大任务拆分红若干个能够并发执行的小任务异步
Join: 合并全部小任务的执行结果ide
ForkJoinTask
: 基本任务,使用forkjoin框架必须建立的对象,提供fork,join操做,经常使用的两个子类性能
RecursiveAction
: 无结果返回的任务RecursiveTask
: 有返回结果的任务说明:学习
fork
: 让task异步执行join
: 让task同步执行,能够获取返回值ForkJoinPool
执行 ForkJoinTask
,测试
三中提交方式:
execute
异步,无返回结果submit
异步,有返回结果 (返回Future<T>
)invoke
同步,有返回结果 (会阻塞)结合两个场景,给出使用姿式
实现从 start - end 的累加求和
首先是定义一个CountTask
来实现求和
首先是肯定任务分割的阀值,当 end-start
的差值大于阀值时,将任务一分为二
public class CountTask extends RecursiveTask<Integer> { private int start; private int end; private static final int THRED_HOLD = 30; public CountTask(int start, int end) { this.start = start; this.end = end; } @Override protected Integer compute() { int sum = 0; boolean canCompute = (end - start) <= THRED_HOLD; if (canCompute) { // 不须要拆分 for (int i = start; i <= end; i++) { sum += i; } System.out.println("thread: " + Thread.currentThread() + " start: " + start + " end: " + end); } else { int mid = (end + start) / 2; CountTask left = new CountTask(start, mid); CountTask right = new CountTask(mid + 1, end); left.fork(); right.fork(); sum = left.join() + right.join(); } return sum; } }
调用case
@Test public void testFork() throws ExecutionException, InterruptedException { int start = 0; int end = 200; CountTask task = new CountTask(start, end); ForkJoinPool pool = ForkJoinPool.commonPool(); Future<Integer> ans = pool.submit(task); int sum = ans.get(); System.out.println(sum); }
输出结果:
thread: Thread[ForkJoinPool.commonPool-worker-0,5,main] start: 51 end: 75 thread: Thread[ForkJoinPool.commonPool-worker-3,5,main] start: 101 end: 125 thread: Thread[ForkJoinPool.commonPool-worker-1,5,main] start: 0 end: 25 thread: Thread[ForkJoinPool.commonPool-worker-3,5,main] start: 126 end: 150 thread: Thread[ForkJoinPool.commonPool-worker-0,5,main] start: 76 end: 100 thread: Thread[ForkJoinPool.commonPool-worker-3,5,main] start: 151 end: 175 thread: Thread[ForkJoinPool.commonPool-worker-1,5,main] start: 26 end: 50 thread: Thread[ForkJoinPool.commonPool-worker-3,5,main] start: 176 end: 200 20100
int 数组进行排序
一样先定义一个SortTask, 主要是为了演示ForkJoin的使用姿式,具体的排序和合并的逻辑比较简陋的实现了一下(这块不是重点)
public class SortTask extends RecursiveTask<List<Integer>> { private List<Integer> list; private final static int THRESHOLD = 5; public SortTask(List<Integer> list) { this.list = list; } @Override protected List<Integer> compute() { if (list.size() < THRESHOLD) { Collections.sort(list); System.out.println("thread: " + Thread.currentThread() + " sort: " + list); return list; } int mid = list.size() >> 1; SortTask l = new SortTask(list.subList(0, mid)); SortTask r = new SortTask(list.subList(mid, list.size())); l.fork(); r.fork(); List<Integer> left = l.join(); List<Integer> right = r.join(); return merge(left, right); } private List<Integer> merge(List<Integer> left, List<Integer> right) { List<Integer> result = new ArrayList<>(left.size() + right.size()); int rightIndex = 0; for (int i = 0; i < left.size(); i++) { if (rightIndex >= right.size() || left.get(i) <= right.get(rightIndex)) { result.add(left.get(i)); } else { result.add(right.get(rightIndex++)); i -= 1; } } if (rightIndex < right.size()) { result.addAll(right.subList(rightIndex, right.size())); } return result; } }
测试case和上面基本同样,咱们改用 invoke 替换上面的 submit
@Test public void testMerge() throws ExecutionException, InterruptedException { List<Integer> list = Arrays.asList(100, 200, 150, 123, 4512, 3414, 3123, 34, 5412, 34, 1234, 893, 213, 455, 6, 123, 23); SortTask sortTask = new SortTask(list); ForkJoinPool pool = ForkJoinPool.commonPool(); List<Integer> ans = pool.invoke(sortTask); System.out.println(ans); }
输出结果
thread: Thread[ForkJoinPool.commonPool-worker-0,5,main] sort: [34, 3123, 3414, 4512] thread: Thread[ForkJoinPool.commonPool-worker-1,5,main] sort: [100, 123, 150, 200] thread: Thread[ForkJoinPool.commonPool-worker-3,5,main] sort: [34, 893, 1234, 5412] thread: Thread[ForkJoinPool.commonPool-worker-0,5,main] sort: [213, 455] thread: Thread[ForkJoinPool.commonPool-worker-3,5,main] sort: [6, 23, 123] [6, 23, 34, 34, 100, 123, 123, 150, 200, 213, 455, 893, 1234, 3123, 3414, 4512, 5412]
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