Hadoop DataNode启动之asyncBlockReport

   DN会不定期定期向NN发送块报告，以使NN能知道自己的块存储情况，便于对外提供服务，对于Hadoop这个大货来说，存放的数据量非常大，如果每次块报告时同步的扫描block显然是不现实的，这时就需要有服务把块报告先准备好，以提高报告的效率，这个服务就是asyncBlockReport，这是一个后台守护线程，在DN创建FSDataset时一并启动。

public FSDataset(DataStorage storage, Configuration conf) throws IOException {    .....    .....    FSVolume[] volArray = new FSVolume[storage.getNumStorageDirs()];    for (int idx = 0; idx < storage.getNumStorageDirs(); idx++) {      volArray[idx] = new FSVolume(storage.getStorageDir(idx).getCurrentDir(), conf);    }    //获得卷组结构    volumes = new FSVolumeSet(volArray);    //获得数据块到块文件的映射，并存放到HashMap中    volumes.getVolumeMap(volumeMap);    //创建异步块报告实例并启动    asyncBlockReport = new AsyncBlockReport(this);    asyncBlockReport.start();    File[] roots = new File[storage.getNumStorageDirs()];    for (int idx = 0; idx < storage.getNumStorageDirs(); idx++) {      roots[idx] = storage.getStorageDir(idx).getCurrentDir();    }    asyncDiskService = new FSDatasetAsyncDiskService(roots);    registerMBean(storage.getStorageID());  }

看下线程的执行体

public void run() {      while (shouldRun) {        try {          waitForReportRequest();//等待扫描请求，在DN的启动过程中会先扫描一次          assert requested && scan == null;          //打印日志，并记录启动时间          DataNode.LOG.info("Starting asynchronous block report scan");          long st = System.currentTimeMillis();          //开始扫描，并生成块报告          HashMap<Block, File> result = fsd.roughBlockScan();          DataNode.LOG.info("Finished asynchronous block report scan in "              + (System.currentTimeMillis() - st) + "ms");          //给blockreport赋值          synchronized (this) {            assert scan == null;            this.scan = result;          }        } catch (InterruptedException ie) {          // interrupted to end scanner        } catch (Throwable t) {          DataNode.LOG.error("Async Block Report thread caught exception", t);          try {            // Avoid busy-looping in the case that we have entered some invalid            // state -- don't want to flood the error log with exceptions.            Thread.sleep(2000);          } catch (InterruptedException e) {          }        }      }}

如何扫描是我们关心的，看下roughBlockScan函数，扫描时并未对目录加锁，有可能更新正在进行，所以这是一个比较粗糙的块报告，但也提供了更高的性能

  HashMap<Block, File> roughBlockScan() {    int expectedNumBlocks;    synchronized (this) {      expectedNumBlocks = volumeMap.size();    }    HashMap<Block, File> seenOnDisk =        new HashMap<Block, File>(expectedNumBlocks, 1.1f);    //开始扫描    volumes.scanBlockFilesInconsistent(seenOnDisk);    return seenOnDisk;  }

继续贴scanBlockFilesInconsistent函数

void scanBlockFilesInconsistent(Map<Block, File> results) {      // 创建文件卷的一个快照，以防扫描时发生更改      FSVolume volumesCopy[];      synchronized (this) {        volumesCopy = Arrays.copyOf(volumes, volumes.length);      }      for (FSVolume vol : volumesCopy) {        vol.scanBlockFilesInconsistent(results);//注意这里      }}

层层调用

void scanBlockFilesInconsistent(Map<Block, File> results) {      scanBlockFilesInconsistent(dataDir.dir, results);}

下面看真正干活的函数scanBlockFilesInconsistent，注意这里生成的块报告并不是同步的，因为在扫描过程中可能会有块的增加或删除，所以在向NN发送之前会通过reconcileRoughBlockScan再次进行核对

private void scanBlockFilesInconsistent(        File dir, Map<Block, File> results) {      //获得数据目录下的所有文件      File filesInDir[] = dir.listFiles();      if (filesInDir != null) {        for (File f : filesInDir) {          //判断是否为块文件          if (Block.isBlockFilename(f)) {            long blockLen = f.length();            //文件是否存在，因为扫描时可能会被删除            if (blockLen == 0 && !f.exists()) {              // length 0 could indicate a race where this file was removed              // while we were in the middle of generating the report.              continue;            }            //生成一个标志位，并用该标识创建块实例            long genStamp = FSDataset.getGenerationStampFromFile(filesInDir, f);            Block b = new Block(f, blockLen, genStamp);            //构建一个blockreport条目，存入HashMap            results.put(b, f);          } else if (f.getName().startsWith("subdir")) {            // 如果有子目录则进行递归扫描            scanBlockFilesInconsistent(f, results);          }        }      }}

每个数据目录都会进行相同的操作，待函数执行完，一个可能不一致的blockreport就产生了，等重新核对报告后便会向NN发送该报告。