• Hadoop 学习总结之二:HDFS读写过程解析(转载)


    一、文件的打开

    1.1、客户端

    HDFS打开一个文件,需要在客户端调用DistributedFileSystem.open(Path f, int bufferSize),其实现为:

    public FSDataInputStream open(Path f, int bufferSize) throws IOException {

      return new DFSClient.DFSDataInputStream(

            dfs.open(getPathName(f), bufferSize, verifyChecksum, statistics));

    }

    其中dfs为DistributedFileSystem的成员变量DFSClient,其open函数被调用,其中创建一个DFSInputStream(src, buffersize, verifyChecksum)并返回。

    在DFSInputStream的构造函数中,openInfo函数被调用,其主要从namenode中得到要打开的文件所对应的blocks的信息,实现如下:

    synchronized void openInfo() throws IOException {

      LocatedBlocks newInfo = callGetBlockLocations(namenode, src, 0, prefetchSize);

      this.locatedBlocks = newInfo;

      this.currentNode = null;

    }

    private static LocatedBlocks callGetBlockLocations(ClientProtocol namenode,

        String src, long start, long length) throws IOException {

        return namenode.getBlockLocations(src, start, length);

    }

    LocatedBlocks主要包含一个链表的List<LocatedBlock> blocks,其中每个LocatedBlock包含如下信息:

    • Block b:此block的信息
    • long offset:此block在文件中的偏移量
    • DatanodeInfo[] locs:此block位于哪些DataNode上

    上面namenode.getBlockLocations是一个RPC调用,最终调用NameNode类的getBlockLocations函数。

    1.2、NameNode

    NameNode.getBlockLocations实现如下:

    public LocatedBlocks   getBlockLocations(String src,

                                            long offset,

                                            long length) throws IOException {

      return namesystem.getBlockLocations(getClientMachine(),

                                          src, offset, length);

    }

    namesystem是NameNode一个成员变量,其类型为FSNamesystem,保存的是NameNode的name space树,其中一个重要的成员变量为FSDirectory dir。

    FSDirectory和Lucene中的FSDirectory没有任何关系,其主要包括FSImage fsImage,用于读写硬盘上的fsimage文件,FSImage类有成员变量FSEditLog editLog,用于读写硬盘上的edit文件,这两个文件的关系在上一篇文章中已经解释过。

    FSDirectory还有一个重要的成员变量INodeDirectoryWithQuota rootDir,INodeDirectoryWithQuota的父类为INodeDirectory,实现如下:

    public class INodeDirectory extends INode {

      ……

      private List<INode> children;

      ……

    由此可见INodeDirectory本身是一个INode,其中包含一个链表的INode,此链表中,如果仍为文件夹,则是类型INodeDirectory,如果是文件,则是类型INodeFile,INodeFile中有成员变量BlockInfo blocks[],是此文件包含的block的信息。显然这是一棵树形的结构。

    FSNamesystem.getBlockLocations函数如下:

    public LocatedBlocks getBlockLocations(String src, long offset, long length,

        boolean doAccessTime) throws IOException {

      final LocatedBlocks ret = getBlockLocationsInternal(src, dir.getFileINode(src),

          offset, length, Integer.MAX_VALUE, doAccessTime); 

      return ret;

    }

    dir.getFileINode(src)通过路径名从文件系统树中找到INodeFile,其中保存的是要打开的文件的INode的信息。

    getBlockLocationsInternal的实现如下:

    private synchronized LocatedBlocks getBlockLocationsInternal(String src,

                                                         INodeFile inode,

                                                         long offset,

                                                         long length,

                                                         int nrBlocksToReturn,

                                                         boolean doAccessTime)

                                                         throws IOException {

      //得到此文件的block信息

      Block[] blocks = inode.getBlocks();

      List<LocatedBlock> results = new ArrayList<LocatedBlock>(blocks.length);

      //计算从offset开始,长度为length所涉及的blocks

      int curBlk = 0;

      long curPos = 0, blkSize = 0;

      int nrBlocks = (blocks[0].getNumBytes() == 0) ? 0 : blocks.length;

      for (curBlk = 0; curBlk < nrBlocks; curBlk++) {

        blkSize = blocks[curBlk].getNumBytes();

        if (curPos + blkSize > offset) {

          //当offset在curPos和curPos + blkSize之间的时候,curBlk指向offset所在的block

          break;

        }

        curPos += blkSize;

      }

      long endOff = offset + length;

      //循环,依次遍历从curBlk开始的每个block,直到当前位置curPos越过endOff

      do {

        int numNodes = blocksMap.numNodes(blocks[curBlk]);

        int numCorruptNodes = countNodes(blocks[curBlk]).corruptReplicas();

        int numCorruptReplicas = corruptReplicas.numCorruptReplicas(blocks[curBlk]);

        boolean blockCorrupt = (numCorruptNodes == numNodes);

        int numMachineSet = blockCorrupt ? numNodes :

                              (numNodes - numCorruptNodes);

        //依次找到此block所对应的datanode,将其中没有损坏的放入machineSet中

        DatanodeDescriptor[] machineSet = new DatanodeDescriptor[numMachineSet];

        if (numMachineSet > 0) {

          numNodes = 0;

          for(Iterator<DatanodeDescriptor> it =

              blocksMap.nodeIterator(blocks[curBlk]); it.hasNext();) {

            DatanodeDescriptor dn = it.next();

            boolean replicaCorrupt = corruptReplicas.isReplicaCorrupt(blocks[curBlk], dn);

            if (blockCorrupt || (!blockCorrupt && !replicaCorrupt))

              machineSet[numNodes++] = dn;

          }

        }

        //使用此machineSet和当前的block构造一个LocatedBlock

        results.add(new LocatedBlock(blocks[curBlk], machineSet, curPos,

                    blockCorrupt));

        curPos += blocks[curBlk].getNumBytes();

        curBlk++;

      } while (curPos < endOff

            && curBlk < blocks.length

            && results.size() < nrBlocksToReturn);

      //使用此LocatedBlock链表构造一个LocatedBlocks对象返回

      return inode.createLocatedBlocks(results);

    }

    1.3、客户端

    通过RPC调用,在NameNode得到的LocatedBlocks对象,作为成员变量构造DFSInputStream对象,最后包装为FSDataInputStream返回给用户。

    二、文件的读取

    2.1、客户端

    文件读取的时候,客户端利用文件打开的时候得到的FSDataInputStream.read(long position, byte[] buffer, int offset, int length)函数进行文件读操作。

    FSDataInputStream会调用其封装的DFSInputStream的read(long position, byte[] buffer, int offset, int length)函数,实现如下:

    public int read(long position, byte[] buffer, int offset, int length)

      throws IOException {

      long filelen = getFileLength();

      int realLen = length;

      if ((position + length) > filelen) {

        realLen = (int)(filelen - position);

      }

      //首先得到包含从offset到offset + length内容的block列表

      //比如对于64M一个block的文件系统来说,欲读取从100M开始,长度为128M的数据,则block列表包括第2,3,4块block

      List<LocatedBlock> blockRange = getBlockRange(position, realLen);

      int remaining = realLen;

      //对每一个block,从中读取内容

      //对于上面的例子,对于第2块block,读取从36M开始,读取长度28M,对于第3块,读取整一块64M,对于第4块,读取从0开始,长度为36M,共128M数据

      for (LocatedBlock blk : blockRange) {

        long targetStart = position - blk.getStartOffset();

        long bytesToRead = Math.min(remaining, blk.getBlockSize() - targetStart);

        fetchBlockByteRange(blk, targetStart,

                            targetStart + bytesToRead - 1, buffer, offset);

        remaining -= bytesToRead;

        position += bytesToRead;

        offset += bytesToRead;

      }

      assert remaining == 0 : "Wrong number of bytes read.";

      if (stats != null) {

        stats.incrementBytesRead(realLen);

      }

      return realLen;

    }

    其中getBlockRange函数如下:

    private synchronized List<LocatedBlock> getBlockRange(long offset,

                                                          long length)

                                                        throws IOException {

      List<LocatedBlock> blockRange = new ArrayList<LocatedBlock>();

      //首先从缓存的locatedBlocks中查找offset所在的block在缓存链表中的位置

      int blockIdx = locatedBlocks.findBlock(offset);

      if (blockIdx < 0) { // block is not cached

        blockIdx = LocatedBlocks.getInsertIndex(blockIdx);

      }

      long remaining = length;

      long curOff = offset;

      while(remaining > 0) {

        LocatedBlock blk = null;

        //按照blockIdx的位置找到block

        if(blockIdx < locatedBlocks.locatedBlockCount())

          blk = locatedBlocks.get(blockIdx);

        //如果block为空,则缓存中没有此block,则直接从NameNode中查找这些block,并加入缓存

        if (blk == null || curOff < blk.getStartOffset()) {

          LocatedBlocks newBlocks;

          newBlocks = callGetBlockLocations(namenode, src, curOff, remaining);

          locatedBlocks.insertRange(blockIdx, newBlocks.getLocatedBlocks());

          continue;

        }

        //如果block找到,则放入结果集

        blockRange.add(blk);

        long bytesRead = blk.getStartOffset() + blk.getBlockSize() - curOff;

        remaining -= bytesRead;

        curOff += bytesRead;

        //取下一个block

        blockIdx++;

      }

      return blockRange;

    }

    其中fetchBlockByteRange实现如下:

    private void fetchBlockByteRange(LocatedBlock block, long start,

                                     long end, byte[] buf, int offset) throws IOException {

      Socket dn = null;

      int numAttempts = block.getLocations().length;

      //此while循环为读取失败后的重试次数

      while (dn == null && numAttempts-- > 0 ) {

        //选择一个DataNode来读取数据

        DNAddrPair retval = chooseDataNode(block);

        DatanodeInfo chosenNode = retval.info;

        InetSocketAddress targetAddr = retval.addr;

        BlockReader reader = null;

        try {

          //创建Socket连接到DataNode

          dn = socketFactory.createSocket();

          dn.connect(targetAddr, socketTimeout);

          dn.setSoTimeout(socketTimeout);

          int len = (int) (end - start + 1);

          //利用建立的Socket链接,生成一个reader负责从DataNode读取数据

          reader = BlockReader.newBlockReader(dn, src,

                                              block.getBlock().getBlockId(),

                                              block.getBlock().getGenerationStamp(),

                                              start, len, buffersize,

                                              verifyChecksum, clientName);

          //读取数据

          int nread = reader.readAll(buf, offset, len);

          return;

        } finally {

          IOUtils.closeStream(reader);

          IOUtils.closeSocket(dn);

          dn = null;

        }

        //如果读取失败,则将此DataNode标记为失败节点

        addToDeadNodes(chosenNode);

      }

    }

    BlockReader.newBlockReader函数实现如下:

    public static BlockReader newBlockReader( Socket sock, String file,

                                       long blockId,

                                       long genStamp,

                                       long startOffset, long len,

                                       int bufferSize, boolean verifyChecksum,

                                       String clientName)

                                       throws IOException {

      //使用Socket建立写入流,向DataNode发送读指令

      DataOutputStream out = new DataOutputStream(

        new BufferedOutputStream(NetUtils.getOutputStream(sock,HdfsConstants.WRITE_TIMEOUT)));

      out.writeShort( DataTransferProtocol.DATA_TRANSFER_VERSION );

      out.write( DataTransferProtocol.OP_READ_BLOCK );

      out.writeLong( blockId );

      out.writeLong( genStamp );

      out.writeLong( startOffset );

      out.writeLong( len );

      Text.writeString(out, clientName);

      out.flush();

      //使用Socket建立读入流,用于从DataNode读取数据

      DataInputStream in = new DataInputStream(

          new BufferedInputStream(NetUtils.getInputStream(sock),

                                  bufferSize));

      DataChecksum checksum = DataChecksum.newDataChecksum( in );

      long firstChunkOffset = in.readLong();

      //生成一个reader,主要包含读入流,用于读取数据

      return new BlockReader( file, blockId, in, checksum, verifyChecksum,

                              startOffset, firstChunkOffset, sock );

    }

    BlockReader的readAll函数就是用上面生成的DataInputStream读取数据。

    2.2、DataNode

    在DataNode启动的时候,会调用函数startDataNode,其中与数据读取有关的逻辑如下:

    void startDataNode(Configuration conf,

                       AbstractList<File> dataDirs

                       ) throws IOException {

      ……

      // 建立一个ServerSocket,并生成一个DataXceiverServer来监控客户端的链接

      ServerSocket ss = (socketWriteTimeout > 0) ?

            ServerSocketChannel.open().socket() : new ServerSocket();

      Server.bind(ss, socAddr, 0);

      ss.setReceiveBufferSize(DEFAULT_DATA_SOCKET_SIZE);

      // adjust machine name with the actual port

      tmpPort = ss.getLocalPort();

      selfAddr = new InetSocketAddress(ss.getInetAddress().getHostAddress(),

                                       tmpPort);

      this.dnRegistration.setName(machineName + ":" + tmpPort);

      this.threadGroup = new ThreadGroup("dataXceiverServer");

      this.dataXceiverServer = new Daemon(threadGroup,

          new DataXceiverServer(ss, conf, this));

      this.threadGroup.setDaemon(true); // auto destroy when empty

      ……

    }

    DataXceiverServer.run()函数如下:

    public void run() {

      while (datanode.shouldRun) {

          //接受客户端的链接

          Socket s = ss.accept();

          s.setTcpNoDelay(true);

          //生成一个线程DataXceiver来对建立的链接提供服务

          new Daemon(datanode.threadGroup,

              new DataXceiver(s, datanode, this)).start();

      }

      try {

        ss.close();

      } catch (IOException ie) {

        LOG.warn(datanode.dnRegistration + ":DataXceiveServer: "

                                + StringUtils.stringifyException(ie));

      }

    }

    DataXceiver.run()函数如下:

    public void run() {

      DataInputStream in=null;

      try {

        //建立一个输入流,读取客户端发送的指令

        in = new DataInputStream(

            new BufferedInputStream(NetUtils.getInputStream(s),

                                    SMALL_BUFFER_SIZE));

        short version = in.readShort();

        boolean local = s.getInetAddress().equals(s.getLocalAddress());

        byte op = in.readByte();

        // Make sure the xciver count is not exceeded

        int curXceiverCount = datanode.getXceiverCount();

        long startTime = DataNode.now();

        switch ( op ) {

        //读取

        case DataTransferProtocol.OP_READ_BLOCK:

          //真正的读取数据

          readBlock( in );

          datanode.myMetrics.readBlockOp.inc(DataNode.now() - startTime);

          if (local)

            datanode.myMetrics.readsFromLocalClient.inc();

          else

            datanode.myMetrics.readsFromRemoteClient.inc();

          break;

        //写入

        case DataTransferProtocol.OP_WRITE_BLOCK:

          //真正的写入数据

          writeBlock( in );

          datanode.myMetrics.writeBlockOp.inc(DataNode.now() - startTime);

          if (local)

            datanode.myMetrics.writesFromLocalClient.inc();

          else

            datanode.myMetrics.writesFromRemoteClient.inc();

          break;

        //其他的指令

        ……

        }

      } catch (Throwable t) {

        LOG.error(datanode.dnRegistration + ":DataXceiver",t);

      } finally {

        IOUtils.closeStream(in);

        IOUtils.closeSocket(s);

        dataXceiverServer.childSockets.remove(s);

      }

    }

    private void readBlock(DataInputStream in) throws IOException {

      //读取指令

      long blockId = in.readLong();         

      Block block = new Block( blockId, 0 , in.readLong());

      long startOffset = in.readLong();

      long length = in.readLong();

      String clientName = Text.readString(in);

      //创建一个写入流,用于向客户端写数据

      OutputStream baseStream = NetUtils.getOutputStream(s,

          datanode.socketWriteTimeout);

      DataOutputStream out = new DataOutputStream(

                   new BufferedOutputStream(baseStream, SMALL_BUFFER_SIZE));

      //生成BlockSender用于读取本地的block的数据,并发送给客户端

      //BlockSender有一个成员变量InputStream blockIn用于读取本地block的数据

      BlockSender blockSender = new BlockSender(block, startOffset, length,

              true, true, false, datanode, clientTraceFmt);

       out.writeShort(DataTransferProtocol.OP_STATUS_SUCCESS); // send op status

       //向客户端写入数据

       long read = blockSender.sendBlock(out, baseStream, null);

       ……

      } finally {

        IOUtils.closeStream(out);

        IOUtils.closeStream(blockSender);

      }

    }

    三、文件的写入

    下面解析向hdfs上传一个文件的过程。

    3.1、客户端

    上传一个文件到hdfs,一般会调用DistributedFileSystem.create,其实现如下:

      public FSDataOutputStream create(Path f, FsPermission permission,

        boolean overwrite,

        int bufferSize, short replication, long blockSize,

        Progressable progress) throws IOException {

        return new FSDataOutputStream

           (dfs.create(getPathName(f), permission,

                       overwrite, replication, blockSize, progress, bufferSize),

            statistics);

      }

    其最终生成一个FSDataOutputStream用于向新生成的文件中写入数据。其成员变量dfs的类型为DFSClient,DFSClient的create函数如下:

      public OutputStream create(String src,

                                 FsPermission permission,

                                 boolean overwrite,

                                 short replication,

                                 long blockSize,

                                 Progressable progress,

                                 int buffersize

                                 ) throws IOException {

        checkOpen();

        if (permission == null) {

          permission = FsPermission.getDefault();

        }

        FsPermission masked = permission.applyUMask(FsPermission.getUMask(conf));

        OutputStream result = new DFSOutputStream(src, masked,

            overwrite, replication, blockSize, progress, buffersize,

            conf.getInt("io.bytes.per.checksum", 512));

        leasechecker.put(src, result);

        return result;

      }

    其中构造了一个DFSOutputStream,在其构造函数中,同过RPC调用NameNode的create来创建一个文件。
    当然,构造函数中还做了一件重要的事情,就是streamer.start(),也即启动了一个pipeline,用于写数据,在写入数据的过程中,我们会仔细分析。

      DFSOutputStream(String src, FsPermission masked, boolean overwrite,

          short replication, long blockSize, Progressable progress,

          int buffersize, int bytesPerChecksum) throws IOException {

        this(src, blockSize, progress, bytesPerChecksum);

        computePacketChunkSize(writePacketSize, bytesPerChecksum);

        try {

          namenode.create(

              src, masked, clientName, overwrite, replication, blockSize);

        } catch(RemoteException re) {

          throw re.unwrapRemoteException(AccessControlException.class,

                                         QuotaExceededException.class);

        }

        streamer.start();

      }

    3.2、NameNode

    NameNode的create函数调用namesystem.startFile函数,其又调用startFileInternal函数,实现如下:

      private synchronized void startFileInternal(String src,

                                                  PermissionStatus permissions,

                                                  String holder,

                                                  String clientMachine,

                                                  boolean overwrite,

                                                  boolean append,

                                                  short replication,

                                                  long blockSize

                                                  ) throws IOException {

        ......

       //创建一个新的文件,状态为under construction,没有任何data block与之对应

       long genstamp = nextGenerationStamp();

       INodeFileUnderConstruction newNode = dir.addFile(src, permissions,

          replication, blockSize, holder, clientMachine, clientNode, genstamp);

       ......

      }

    3.3、客户端

    下面轮到客户端向新创建的文件中写入数据了,一般会使用FSDataOutputStream的write函数,最终会调用DFSOutputStream的writeChunk函数:

    按照hdfs的设计,对block的数据写入使用的是pipeline的方式,也即将数据分成一个个的package,如果需要复制三分,分别写入DataNode 1, 2, 3,则会进行如下的过程:

    • 首先将package 1写入DataNode 1
    • 然后由DataNode 1负责将package 1写入DataNode 2,同时客户端可以将pacage 2写入DataNode 1
    • 然后DataNode 2负责将package 1写入DataNode 3, 同时客户端可以讲package 3写入DataNode 1,DataNode 1将package 2写入DataNode 2
    • 就这样将一个个package排着队的传递下去,直到所有的数据全部写入并复制完毕

      protected synchronized void writeChunk(byte[] b, int offset, int len, byte[] checksum)

                                                            throws IOException {

          //创建一个package,并写入数据

          currentPacket = new Packet(packetSize, chunksPerPacket,

                                       bytesCurBlock);

          currentPacket.writeChecksum(checksum, 0, cklen);

          currentPacket.writeData(b, offset, len);

          currentPacket.numChunks++;

          bytesCurBlock += len;

          //如果此package已满,则放入队列中准备发送

          if (currentPacket.numChunks == currentPacket.maxChunks ||

              bytesCurBlock == blockSize) {

              ......

              dataQueue.addLast(currentPacket);

              //唤醒等待dataqueue的传输线程,也即DataStreamer

              dataQueue.notifyAll();

              currentPacket = null;

              ......

          }

      }


    DataStreamer的run函数如下:

      public void run() {

        while (!closed && clientRunning) {

          Packet one = null;

          synchronized (dataQueue) {

            //如果队列中没有package,则等待

            while ((!closed && !hasError && clientRunning

                   && dataQueue.size() == 0) || doSleep) {

              try {

                dataQueue.wait(1000);

              } catch (InterruptedException  e) {

              }

              doSleep = false;

            }

            try {

              //得到队列中的第一个package

              one = dataQueue.getFirst();

              long offsetInBlock = one.offsetInBlock;

              //由NameNode分配block,并生成一个写入流指向此block

              if (blockStream == null) {

                nodes = nextBlockOutputStream(src);

                response = new ResponseProcessor(nodes);

                response.start();

              }

              ByteBuffer buf = one.getBuffer();

              //将package从dataQueue移至ackQueue,等待确认

              dataQueue.removeFirst();

              dataQueue.notifyAll();

              synchronized (ackQueue) {

                ackQueue.addLast(one);

                ackQueue.notifyAll();

              }

              //利用生成的写入流将数据写入DataNode中的block

              blockStream.write(buf.array(), buf.position(), buf.remaining());

              if (one.lastPacketInBlock) {

                blockStream.writeInt(0); //表示此block写入完毕

              }

              blockStream.flush();

            } catch (Throwable e) {

            }

          }

          ......

      }

     

    其中重要的一个函数是nextBlockOutputStream,实现如下:

      private DatanodeInfo[] nextBlockOutputStream(String client) throws IOException {

        LocatedBlock lb = null;

        boolean retry = false;

        DatanodeInfo[] nodes;

        int count = conf.getInt("dfs.client.block.write.retries", 3);

        boolean success;

        do {

          ......

          //由NameNode为文件分配DataNode和block

          lb = locateFollowingBlock(startTime);

          block = lb.getBlock();

          nodes = lb.getLocations();

          //创建向DataNode的写入流

          success = createBlockOutputStream(nodes, clientName, false);

          ......

        } while (retry && --count >= 0);

        return nodes;

      }

    locateFollowingBlock中通过RPC调用namenode.addBlock(src, clientName)函数

     

    3.4、NameNode

    NameNode的addBlock函数实现如下:

      public LocatedBlock addBlock(String src,

                                   String clientName) throws IOException {

        LocatedBlock locatedBlock = namesystem.getAdditionalBlock(src, clientName);

        return locatedBlock;

      }

    FSNamesystem的getAdditionalBlock实现如下:

      public LocatedBlock getAdditionalBlock(String src,

                                             String clientName

                                             ) throws IOException {

        long fileLength, blockSize;

        int replication;

        DatanodeDescriptor clientNode = null;

        Block newBlock = null;

        ......

        //为新的block选择DataNode

        DatanodeDescriptor targets[] = replicator.chooseTarget(replication,

                                                               clientNode,

                                                               null,

                                                               blockSize);

        ......

        //得到文件路径中所有path的INode,其中最后一个是新添加的文件对的INode,状态为under construction

        INode[] pathINodes = dir.getExistingPathINodes(src);

        int inodesLen = pathINodes.length;

        INodeFileUnderConstruction pendingFile  = (INodeFileUnderConstruction)

                                                    pathINodes[inodesLen - 1];

        //为文件分配block, 并设置在那写DataNode上

        newBlock = allocateBlock(src, pathINodes);

        pendingFile.setTargets(targets);

        ......

        return new LocatedBlock(newBlock, targets, fileLength);

      }

    3.5、客户端

    在分配了DataNode和block以后,createBlockOutputStream开始写入数据。

      private boolean createBlockOutputStream(DatanodeInfo[] nodes, String client,

                      boolean recoveryFlag) {

          //创建一个socket,链接DataNode

          InetSocketAddress target = NetUtils.createSocketAddr(nodes[0].getName());

          s = socketFactory.createSocket();

          int timeoutValue = 3000 * nodes.length + socketTimeout;

          s.connect(target, timeoutValue);

          s.setSoTimeout(timeoutValue);

          s.setSendBufferSize(DEFAULT_DATA_SOCKET_SIZE);

          long writeTimeout = HdfsConstants.WRITE_TIMEOUT_EXTENSION * nodes.length +

                              datanodeWriteTimeout;

          DataOutputStream out = new DataOutputStream(

              new BufferedOutputStream(NetUtils.getOutputStream(s, writeTimeout),

                                       DataNode.SMALL_BUFFER_SIZE));

          blockReplyStream = new DataInputStream(NetUtils.getInputStream(s));

          //写入指令

          out.writeShort( DataTransferProtocol.DATA_TRANSFER_VERSION );

          out.write( DataTransferProtocol.OP_WRITE_BLOCK );

          out.writeLong( block.getBlockId() );

          out.writeLong( block.getGenerationStamp() );

          out.writeInt( nodes.length );

          out.writeBoolean( recoveryFlag );

          Text.writeString( out, client );

          out.writeBoolean(false);

          out.writeInt( nodes.length - 1 );

          //注意,次循环从1开始,而非从0开始。将除了第一个DataNode以外的另外两个DataNode的信息发送给第一个DataNode, 第一个DataNode可以根据此信息将数据写给另两个DataNode

          for (int i = 1; i < nodes.length; i++) {

            nodes[i].write(out);

          }

          checksum.writeHeader( out );

          out.flush();

          firstBadLink = Text.readString(blockReplyStream);

          if (firstBadLink.length() != 0) {

            throw new IOException("Bad connect ack with firstBadLink " + firstBadLink);

          }

          blockStream = out;

      }

    客户端在DataStreamer的run函数中创建了写入流后,调用blockStream.write将数据写入DataNode

     

    3.6、DataNode

    DataNode的DataXceiver中,收到指令DataTransferProtocol.OP_WRITE_BLOCK则调用writeBlock函数:

      private void writeBlock(DataInputStream in) throws IOException {

        DatanodeInfo srcDataNode = null;

        //读入头信息

        Block block = new Block(in.readLong(),

            dataXceiverServer.estimateBlockSize, in.readLong());

        int pipelineSize = in.readInt(); // num of datanodes in entire pipeline

        boolean isRecovery = in.readBoolean(); // is this part of recovery?

        String client = Text.readString(in); // working on behalf of this client

        boolean hasSrcDataNode = in.readBoolean(); // is src node info present

        if (hasSrcDataNode) {

          srcDataNode = new DatanodeInfo();

          srcDataNode.readFields(in);

        }

        int numTargets = in.readInt();

        if (numTargets < 0) {

          throw new IOException("Mislabelled incoming datastream.");

        }

        //读入剩下的DataNode列表,如果当前是第一个DataNode,则此列表中收到的是第二个,第三个DataNode的信息,如果当前是第二个DataNode,则受到的是第三个DataNode的信息

        DatanodeInfo targets[] = new DatanodeInfo[numTargets];

        for (int i = 0; i < targets.length; i++) {

          DatanodeInfo tmp = new DatanodeInfo();

          tmp.readFields(in);

          targets[i] = tmp;

        }

        DataOutputStream mirrorOut = null;  // stream to next target

        DataInputStream mirrorIn = null;    // reply from next target

        DataOutputStream replyOut = null;   // stream to prev target

        Socket mirrorSock = null;           // socket to next target

        BlockReceiver blockReceiver = null; // responsible for data handling

        String mirrorNode = null;           // the name:port of next target

        String firstBadLink = "";           // first datanode that failed in connection setup

        try {

          //生成一个BlockReceiver, 其有成员变量DataInputStream in为从客户端或者上一个DataNode读取数据,还有成员变量DataOutputStream mirrorOut,用于向下一个DataNode写入数据,还有成员变量OutputStream out用于将数据写入本地。

          blockReceiver = new BlockReceiver(block, in,

              s.getRemoteSocketAddress().toString(),

              s.getLocalSocketAddress().toString(),

              isRecovery, client, srcDataNode, datanode);

          // get a connection back to the previous target

          replyOut = new DataOutputStream(

                         NetUtils.getOutputStream(s, datanode.socketWriteTimeout));

          //如果当前不是最后一个DataNode,则同下一个DataNode建立socket连接

          if (targets.length > 0) {

            InetSocketAddress mirrorTarget = null;

            // Connect to backup machine

            mirrorNode = targets[0].getName();

            mirrorTarget = NetUtils.createSocketAddr(mirrorNode);

            mirrorSock = datanode.newSocket();

            int timeoutValue = numTargets * datanode.socketTimeout;

            int writeTimeout = datanode.socketWriteTimeout +

                                 (HdfsConstants.WRITE_TIMEOUT_EXTENSION * numTargets);

            mirrorSock.connect(mirrorTarget, timeoutValue);

            mirrorSock.setSoTimeout(timeoutValue);

            mirrorSock.setSendBufferSize(DEFAULT_DATA_SOCKET_SIZE);

            //创建向下一个DataNode写入数据的流

            mirrorOut = new DataOutputStream(

                 new BufferedOutputStream(

                             NetUtils.getOutputStream(mirrorSock, writeTimeout),

                             SMALL_BUFFER_SIZE));

            mirrorIn = new DataInputStream(NetUtils.getInputStream(mirrorSock));

            mirrorOut.writeShort( DataTransferProtocol.DATA_TRANSFER_VERSION );

            mirrorOut.write( DataTransferProtocol.OP_WRITE_BLOCK );

            mirrorOut.writeLong( block.getBlockId() );

            mirrorOut.writeLong( block.getGenerationStamp() );

            mirrorOut.writeInt( pipelineSize );

            mirrorOut.writeBoolean( isRecovery );

            Text.writeString( mirrorOut, client );

            mirrorOut.writeBoolean(hasSrcDataNode);

            if (hasSrcDataNode) { // pass src node information

              srcDataNode.write(mirrorOut);

            }

            mirrorOut.writeInt( targets.length - 1 );

            //此出也是从1开始,将除了下一个DataNode的其他DataNode信息发送给下一个DataNode

            for ( int i = 1; i < targets.length; i++ ) {

              targets[i].write( mirrorOut );

            }

            blockReceiver.writeChecksumHeader(mirrorOut);

            mirrorOut.flush();

          }

          //使用BlockReceiver接受block

          String mirrorAddr = (mirrorSock == null) ? null : mirrorNode;

          blockReceiver.receiveBlock(mirrorOut, mirrorIn, replyOut,

                                     mirrorAddr, null, targets.length);

          ......

        } finally {

          // close all opened streams

          IOUtils.closeStream(mirrorOut);

          IOUtils.closeStream(mirrorIn);

          IOUtils.closeStream(replyOut);

          IOUtils.closeSocket(mirrorSock);

          IOUtils.closeStream(blockReceiver);

        }

      }

    BlockReceiver的receiveBlock函数中,一段重要的逻辑如下:

      void receiveBlock(

          DataOutputStream mirrOut, // output to next datanode

          DataInputStream mirrIn,   // input from next datanode

          DataOutputStream replyOut,  // output to previous datanode

          String mirrAddr, BlockTransferThrottler throttlerArg,

          int numTargets) throws IOException {

          ......

          //不断的接受package,直到结束

          while (receivePacket() > 0) {}

          if (mirrorOut != null) {

            try {

              mirrorOut.writeInt(0); // mark the end of the block

              mirrorOut.flush();

            } catch (IOException e) {

              handleMirrorOutError(e);

            }

          }

          ......

      }

    BlockReceiver的receivePacket函数如下:

      private int receivePacket() throws IOException {

        //从客户端或者上一个节点接收一个package

        int payloadLen = readNextPacket();

        buf.mark();

        //read the header

        buf.getInt(); // packet length

        offsetInBlock = buf.getLong(); // get offset of packet in block

        long seqno = buf.getLong();    // get seqno

        boolean lastPacketInBlock = (buf.get() != 0);

        int endOfHeader = buf.position();

        buf.reset();

        setBlockPosition(offsetInBlock);

        //将package写入下一个DataNode

        if (mirrorOut != null) {

          try {

            mirrorOut.write(buf.array(), buf.position(), buf.remaining());

            mirrorOut.flush();

          } catch (IOException e) {

            handleMirrorOutError(e);

          }

        }

        buf.position(endOfHeader);       

        int len = buf.getInt();

        offsetInBlock += len;

        int checksumLen = ((len + bytesPerChecksum - 1)/bytesPerChecksum)*

                                                                checksumSize;

        int checksumOff = buf.position();

        int dataOff = checksumOff + checksumLen;

        byte pktBuf[] = buf.array();

        buf.position(buf.limit()); // move to the end of the data.

        ......

        //将数据写入本地的block

        out.write(pktBuf, dataOff, len);

        /// flush entire packet before sending ack

        flush();

        // put in queue for pending acks

        if (responder != null) {

          ((PacketResponder)responder.getRunnable()).enqueue(seqno,

                                          lastPacketInBlock);

        }

        return payloadLen;

      }

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  • 原文地址:https://www.cnblogs.com/licheng/p/1957729.html
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