hdfs源码分析第一弹

1. hdfs定义

HDFS is the primary distributed storage used by Hadoop applications. A HDFS cluster primarily consists of a NameNode that manages the file system metadata and DataNodes that store the actual data.

2. hdfs架构

3. hdfs实例

  作为文件系统，文件的读写才是核心：

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import java.io.File;
import java.io.IOException;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.FSDataInputStream;
import org.apache.hadoop.fs.FSDataOutputStream;
import org.apache.hadoop.fs.Path;

public class HadoopDFSFileReadWrite {
  
  static void usage () {
    System.out.println("Usage : HadoopDFSFileReadWrite <inputfile> <output file>");
    System.exit(1);
  }
  
  static void printAndExit(String str) {
    System.err.println(str);
    System.exit(1);
  }

  public static void main (String[] argv) throws IOException {
    Configuration conf = new Configuration();
    FileSystem fs = FileSystem.get(conf);

    if (argv.length != 2)
      usage();
    
    // Hadoop DFS deals with Path
    Path inFile = new Path(argv[0]);
    Path outFile = new Path(argv[1]);
   
    // Check if input/output are valid
    if (!fs.exists(inFile))
      printAndExit("Input file not found");
    if (!fs.isFile(inFile))
      printAndExit("Input should be a file");
    if (fs.exists(outFile))
      printAndExit("Output already exists");

    // Read from and write to new file
    FSDataInputStream in = fs.open(inFile);
    FSDataOutputStream out = fs.create(outFile);
    byte buffer[] = new byte[256];
    try {
      int bytesRead = 0;
      while ((bytesRead = in.read(buffer)) > 0) {
        out.write(buffer, 0, bytesRead);
      }
    } catch (IOException e) {
      System.out.println("Error while copying file");
    } finally {
      in.close();
      out.close();
    }
  }
}

上述示例，将一个文件的内容复制到另一个文件中，具体步骤如下：

第一步：创建一个文件系统实例，给该实例传递新的配置。

Configuration conf = new Configuration();
FileSystem fs = FileSystem.get(conf);

第二步：获取文件路径

// Hadoop DFS deals with Path
    Path inFile = new Path(argv[0]);
    Path outFile = new Path(argv[1]);
   
    // Check if input/output are valid
    if (!fs.exists(inFile))
      printAndExit("Input file not found");
    if (!fs.isFile(inFile))
      printAndExit("Input should be a file");
    if (fs.exists(outFile))
      printAndExit("Output already exists");

第三步：打开文件输入输出流，将输入流写到输出流中：

    // Read from and write to new file
    FSDataInputStream in = fs.open(inFile);
    FSDataOutputStream out = fs.create(outFile);
    byte buffer[] = new byte[256];
    try {
      int bytesRead = 0;
      while ((bytesRead = in.read(buffer)) > 0) {
        out.write(buffer, 0, bytesRead);
      }
    } catch (IOException e) {
      System.out.println("Error while copying file");
    } finally {
      in.close();
      out.close();
    }

上面文件读写功能涉及到了文件系统FileSystem、配置文件Configuration、输入流/输出流FSDataInputStream/FSDataOutputStream

 4. 基本概念分析

    4.1 文件系统

　　文件系统的层次结构如下所示：

　　文件系统有两个重要的分支，一个是分布式文件系统，另一个是“本地”（映射到本地连接的磁盘）文件系统，本地磁盘适用于比较少的hadoop实例和测试。绝大部分情况下使用分布式文件系统，hadoop 分布式文件系统使用多个机器的系统，但对用户来说只有一个磁盘。它的容错性和大容量性使它非常有用。

　　4.2 配置文件

　　配置文件的层次结构如下：

我们关注的是HdfsConfiguration，其涉及到的配置文件有hdfs-default.xml和hdfs-site.xml：

  static {
    addDeprecatedKeys();

    // adds the default resources
    Configuration.addDefaultResource("hdfs-default.xml");
    Configuration.addDefaultResource("hdfs-site.xml");

  }

 

　　4.3 输入/输出流

　　　　输入/输出流和文件系统相对应，先看一下输入流：

　　

其中，HdfsDataInputStream是FSDataInputStream的实现，其构造函数为：

  public HdfsDataInputStream(DFSInputStream in) throws IOException {
    super(in);
  }

DFSInputStream层次结构如下图所示：

　　在了解一下输出流：

　　

其中，重点是HdfsDataOutputStream，其构造函数为：

  public HdfsDataOutputStream(DFSOutputStream out, FileSystem.Statistics stats,
      long startPosition) throws IOException {
    super(out, stats, startPosition);
  }

DFSOutputStream 的层次结构为：

 

参考文献：

【1】http://hadoop.apache.org/docs/r2.6.0/hadoop-project-dist/hadoop-hdfs/HdfsUserGuide.html

【2】http://hadoop.apache.org/docs/r2.6.0/hadoop-project-dist/hadoop-hdfs/HdfsDesign.html

【3】http://wiki.apache.org/hadoop/HadoopDfsReadWriteExample

【4】http://blog.csdn.net/gaoxingnengjisuan/article/details/11177049