有个功能需要同时上传N个文件。代码如下:
ApiService as = ApiManager.getApiService(); final ExecutorService es = Executors.newFixedThreadPool(9); final int count = Bimp.tempSelectBitmap.size(); final CountDownLatch finishedLatch = new CountDownLatch(count); final long start = System.currentTimeMillis(); for (int k = 0; k < count; k++) { final String fp = Bimp.tempSelectBitmap.get(k).getImagePath(); RequestBody fbody = RequestBody.create(MediaType.parse("image/*"), new File(fp)); as.uploadAttach(fbody) .subscribeOn(Schedulers.from(es)) .observeOn(Schedulers.computation()) .subscribe(new Subscriber<UploadAttachJSON>() { @Override public void onCompleted() { } @Override public void onError(Throwable e) { finishedLatch.countDown(); Log.e("UPLOAD FAILED -------->", fp); } @Override public void onNext(UploadAttachJSON uploadAttachJSON) { finishedLatch.countDown(); sb.append(uploadAttachJSON.url).append(","); Log.e("UPLOADED IMAGE URL -->", uploadAttachJSON.url); h.post(new Runnable() { @Override public void run() { pd.setMessage("正在上传... " + (count - finishedLatch.getCount()) + "/" + count); } }); } }); } try { finishedLatch.await(); } catch (InterruptedException e) { e.printStackTrace(); } long end = System.currentTimeMillis(); Log.e("IMAGE UPLOAD COMPLETED", (end - start) + ""); es.shutdown();
以上为并行的写法。从线程池中拿出N个线程来同时上传这N个文件。
串行写法: .subscribeOn(Schedulers.io())
或者 用Observable.merge
来合并这些请求。
结果发现并行和串行所花费的时间几乎都差不多。。 是不是和android底层有关?这些网络请求其实最后都被底层给block了,然后串行出去?
设备的网速是不是有限制
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