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Hadoop学习总结之二:HDFS读写过程解析

时间:2012-04-27 01:22:59  来源:  作者:

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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