前往小程序,Get更优阅读体验!
立即前往
首页
学习
活动
专区
工具
TVP
发布
社区首页 >专栏 >Hadoop之MapReduce04【客户端源码分析】

Hadoop之MapReduce04【客户端源码分析】

作者头像
用户4919348
发布2019-04-17 17:50:10
3980
发布2019-04-17 17:50:10
举报
文章被收录于专栏:波波烤鸭波波烤鸭波波烤鸭

  本文是基于hadoop2.6.5的源码分析。

客户端源码分析

启动的客户端代码

public static void main(String[] args) throws Exception {
	// 创建配置文件对象
	Configuration conf = new Configuration(true);
	
	// 获取Job对象
	Job job = Job.getInstance(conf);
	// 设置相关类
	job.setJarByClass(WcTest.class);
	
	// 指定 Map阶段和Reduce阶段的处理类
	job.setMapperClass(MyMapperTask.class);
	job.setReducerClass(MyReducerTask.class);
	
	// 指定Map阶段的输出类型
	job.setMapOutputKeyClass(Text.class);
	job.setMapOutputValueClass(IntWritable.class);
	
	// 指定job的原始文件的输入输出路径 通过参数传入
	FileInputFormat.setInputPaths(job, new Path(args[0]));
	FileOutputFormat.setOutputPath(job, new Path(args[1]));
	// 提交任务,并等待响应
	job.waitForCompletion(true);
}

1.Configuration 对象

  Configuration 用来存储相关的配置文件。在该类中有一段static代码块

在这里插入图片描述
在这里插入图片描述

2.Job对象的获取

  我们来看下Job对象的实例化过程。

// 获取Job对象
Job job = Job.getInstance(conf);

进入getInstance(conf)方法。

  public static Job getInstance(Configuration conf) throws IOException {
    // create with a null Cluster
    JobConf jobConf = new JobConf(conf);
    return new Job(jobConf);
  }

Job类中同样有static代码块。

在这里插入图片描述
在这里插入图片描述

进入loadResources方法

在这里插入图片描述
在这里插入图片描述

3.waitForCompletion

  该方法的执行过程比较复杂,我们慢慢来分析,首先来看下简化的时序图

在这里插入图片描述
在这里插入图片描述

3.1waitForCompletion

public boolean waitForCompletion(boolean verbose
                                   ) throws IOException, InterruptedException,
                                            ClassNotFoundException {
    // 判断任务的状态,如果是DEFINE就提交
    if (state == JobState.DEFINE) {
      submit();
    }
    if (verbose) {
      // 监听并且输出任务信息
      monitorAndPrintJob();
    } else {
      // get the completion poll interval from the client.
      int completionPollIntervalMillis = 
        Job.getCompletionPollInterval(cluster.getConf());
      while (!isComplete()) {
        try {
          // 间隔判断是否执行完成
          Thread.sleep(completionPollIntervalMillis);
        } catch (InterruptedException ie) {
        }
      }
    }
    return isSuccessful();
  }

3.2submit

  进入submit方法查看

  public void submit() 
         throws IOException, InterruptedException, ClassNotFoundException {
    // 再次确认任务状态
    ensureState(JobState.DEFINE);
    // 默认使用new APIs
    setUseNewAPI();
    // 初始化cluster对象
    connect();
    // 根据初始化得到的cluster对象生成JobSubmitter对象
    final JobSubmitter submitter = 
        getJobSubmitter(cluster.getFileSystem(), cluster.getClient());
    // 
    status = ugi.doAs(new PrivilegedExceptionAction<JobStatus>() {
      public JobStatus run() throws IOException, InterruptedException, 
      ClassNotFoundException {
      	// 进入 submitJobInternal 方法查看
        return submitter.submitJobInternal(Job.this, cluster);
      }
    });
    //将job的状态设置为RUNNING
    state = JobState.RUNNING;
    LOG.info("The url to track the job: " + getTrackingURL());
   }

3.3 submitJobInternal

/**
*
* 检查job的输入输出规范
* 计算job的InputSplit
* 如果需要的话,设置需要的核算信息对于job的分布式缓存
* 复制job的jar和配置文件到分布式文件系统的系统目录
* 提交作业执行以及监控它的状态
*/
 JobStatus submitJobInternal(Job job, Cluster cluster) 
  throws ClassNotFoundException, InterruptedException, IOException {

    //检查job的输出空间 
    checkSpecs(job);
	
    Configuration conf = job.getConfiguration();
    // 将MapReduce框架加入分布式缓存中
    addMRFrameworkToDistributedCache(conf);
	// 初始化job的工作根目录并返回path路径
    Path jobStagingArea = JobSubmissionFiles.getStagingDir(cluster, conf);
    //configure the command line options correctly on the submitting dfs
    InetAddress ip = InetAddress.getLocalHost();
    if (ip != null) {
      submitHostAddress = ip.getHostAddress();
      submitHostName = ip.getHostName();
      conf.set(MRJobConfig.JOB_SUBMITHOST,submitHostName);
      conf.set(MRJobConfig.JOB_SUBMITHOSTADDR,submitHostAddress);
    }
    //  为job分配一个名字
    JobID jobId = submitClient.getNewJobID();
    job.setJobID(jobId);
    // 获得job的提交路径,也就是在jobStagingArea目录下建一个以jobId为文件名的目录
    Path submitJobDir = new Path(jobStagingArea, jobId.toString());
    JobStatus status = null;
    // 进行一系列的配置
    try {
      conf.set(MRJobConfig.USER_NAME,
          UserGroupInformation.getCurrentUser().getShortUserName());
      conf.set("hadoop.http.filter.initializers", 
          "org.apache.hadoop.yarn.server.webproxy.amfilter.AmFilterInitializer");
      conf.set(MRJobConfig.MAPREDUCE_JOB_DIR, submitJobDir.toString());
      LOG.debug("Configuring job " + jobId + " with " + submitJobDir 
          + " as the submit dir");
      // get delegation token for the dir
      TokenCache.obtainTokensForNamenodes(job.getCredentials(),
          new Path[] { submitJobDir }, conf);
      
      populateTokenCache(conf, job.getCredentials());

      // generate a secret to authenticate shuffle transfers
      if (TokenCache.getShuffleSecretKey(job.getCredentials()) == null) {
        KeyGenerator keyGen;
        try {
          keyGen = KeyGenerator.getInstance(SHUFFLE_KEYGEN_ALGORITHM);
          keyGen.init(SHUFFLE_KEY_LENGTH);
        } catch (NoSuchAlgorithmException e) {
          throw new IOException("Error generating shuffle secret key", e);
        }
        SecretKey shuffleKey = keyGen.generateKey();
        TokenCache.setShuffleSecretKey(shuffleKey.getEncoded(),
            job.getCredentials());
      }
	  // 这个方法实现文件上传	
      copyAndConfigureFiles(job, submitJobDir);
      Path submitJobFile = JobSubmissionFiles.getJobConfPath(submitJobDir);
      
      // Create the splits for the job
      LOG.debug("Creating splits at " + jtFs.makeQualified(submitJobDir));
      // 方法内部会根据我们之前的设置,选择使用new-api还是old-api分别进行分片操作
      int maps = writeSplits(job, submitJobDir);
      conf.setInt(MRJobConfig.NUM_MAPS, maps);
      LOG.info("number of splits:" + maps);

      // write "queue admins of the queue to which job is being submitted"
      // to job file.
      String queue = conf.get(MRJobConfig.QUEUE_NAME,
          JobConf.DEFAULT_QUEUE_NAME);
      AccessControlList acl = submitClient.getQueueAdmins(queue);
      conf.set(toFullPropertyName(queue,
          QueueACL.ADMINISTER_JOBS.getAclName()), acl.getAclString());

      // removing jobtoken referrals before copying the jobconf to HDFS
      // as the tasks don't need this setting, actually they may break
      // because of it if present as the referral will point to a
      // different job.
      TokenCache.cleanUpTokenReferral(conf);

      if (conf.getBoolean(
          MRJobConfig.JOB_TOKEN_TRACKING_IDS_ENABLED,
          MRJobConfig.DEFAULT_JOB_TOKEN_TRACKING_IDS_ENABLED)) {
        // Add HDFS tracking ids
        ArrayList<String> trackingIds = new ArrayList<String>();
        for (Token<? extends TokenIdentifier> t :
            job.getCredentials().getAllTokens()) {
          trackingIds.add(t.decodeIdentifier().getTrackingId());
        }
        conf.setStrings(MRJobConfig.JOB_TOKEN_TRACKING_IDS,
            trackingIds.toArray(new String[trackingIds.size()]));
      }

      // 提交规划文件 job.split wc.jar ...
      writeConf(conf, submitJobFile);
      
      //
      // Now, actually submit the job (using the submit name)
      // 提交任务
      printTokens(jobId, job.getCredentials());
      status = submitClient.submitJob(
          jobId, submitJobDir.toString(), job.getCredentials());
      if (status != null) {
        return status;
      } else {
        throw new IOException("Could not launch job");
      }
    } finally {
      if (status == null) {
        LOG.info("Cleaning up the staging area " + submitJobDir);
        if (jtFs != null && submitJobDir != null)
          jtFs.delete(submitJobDir, true);

      }
    }
  }

3.4writeSplits

  private int writeSplits(org.apache.hadoop.mapreduce.JobContext job,
      Path jobSubmitDir) throws IOException,
      InterruptedException, ClassNotFoundException {
    JobConf jConf = (JobConf)job.getConfiguration();
    int maps;
    if (jConf.getUseNewMapper()) {
     //进入
      maps = writeNewSplits(job, jobSubmitDir);
    } else {
      maps = writeOldSplits(jConf, jobSubmitDir);
    }
    return maps;
  }

3.5writeNewSplits

  int writeNewSplits(JobContext job, Path jobSubmitDir) throws IOException,
      InterruptedException, ClassNotFoundException {
    Configuration conf = job.getConfiguration();
    // 根据我们设置的inputFormat.class通过反射获得inputFormat对象
    InputFormat<?, ?> input =
      ReflectionUtils.newInstance(job.getInputFormatClass(), conf);
	// 获取分片信息
    List<InputSplit> splits = input.getSplits(job);
    T[] array = (T[]) splits.toArray(new InputSplit[splits.size()]);

    // sort the splits into order based on size, so that the biggest
    // go first
    Arrays.sort(array, new SplitComparator());
    // 将分片的信息写入到jobSubmitDir --job.split文件中
    JobSplitWriter.createSplitFiles(jobSubmitDir, conf, 
        jobSubmitDir.getFileSystem(conf), array);
    return array.length;
  }

3.6 getSplits

  public List<InputSplit> getSplits(JobContext job) throws IOException {
    Stopwatch sw = new Stopwatch().start();
    // 最小值
    long minSize = Math.max(getFormatMinSplitSize(), getMinSplitSize(job));
    // 最大值
    long maxSize = getMaxSplitSize(job);

    // generate splits
    List<InputSplit> splits = new ArrayList<InputSplit>();
    List<FileStatus> files = listStatus(job);
    for (FileStatus file: files) {
      Path path = file.getPath();
      long length = file.getLen();
      if (length != 0) {
        BlockLocation[] blkLocations;
        if (file instanceof LocatedFileStatus) {
          blkLocations = ((LocatedFileStatus) file).getBlockLocations();
        } else {
          FileSystem fs = path.getFileSystem(job.getConfiguration());
          blkLocations = fs.getFileBlockLocations(file, 0, length);
        }
        if (isSplitable(job, path)) {
          // 获取block大小
          long blockSize = file.getBlockSize();
          // 获取splitSize大小
          long splitSize = computeSplitSize(blockSize, minSize, maxSize);

          long bytesRemaining = length;
          while (((double) bytesRemaining)/splitSize > SPLIT_SLOP) {
            int blkIndex = getBlockIndex(blkLocations, length-bytesRemaining);
            splits.add(makeSplit(path, length-bytesRemaining, splitSize,
                        blkLocations[blkIndex].getHosts(),
                        blkLocations[blkIndex].getCachedHosts()));
            bytesRemaining -= splitSize;
          }

          if (bytesRemaining != 0) {
            int blkIndex = getBlockIndex(blkLocations, length-bytesRemaining);
            splits.add(makeSplit(path, length-bytesRemaining, bytesRemaining,
                       blkLocations[blkIndex].getHosts(),
                       blkLocations[blkIndex].getCachedHosts()));
          }
        } else { // not splitable
          splits.add(makeSplit(path, 0, length, blkLocations[0].getHosts(),
                      blkLocations[0].getCachedHosts()));
        }
      } else { 
        //Create empty hosts array for zero length files
        splits.add(makeSplit(path, 0, length, new String[0]));
      }
    }
    // Save the number of input files for metrics/loadgen
    job.getConfiguration().setLong(NUM_INPUT_FILES, files.size());
    sw.stop();
    if (LOG.isDebugEnabled()) {
      LOG.debug("Total # of splits generated by getSplits: " + splits.size()
          + ", TimeTaken: " + sw.elapsedMillis());
    }
    return splits;
  }

3.7computeSplitSize

protected long computeSplitSize(long blockSize, long minSize,
                                long maxSize) {
  return Math.max(minSize, Math.min(maxSize, blockSize));
}

3.8 submitJobInternal

回到 submitJobInternal方法中

	// 提交规划文件 job.split wc.jar ...
      writeConf(conf, submitJobFile);
      
      //
      // Now, actually submit the job (using the submit name)
      // 提交任务
      printTokens(jobId, job.getCredentials());
      status = submitClient.submitJob(
          jobId, submitJobDir.toString(), job.getCredentials());
      if (status != null) {
        return status;
      } else {
        throw new IOException("Could not launch job");
      }
    } finally {
      if (status == null) {
        LOG.info("Cleaning up the staging area " + submitJobDir);
        if (jtFs != null && submitJobDir != null)
        	// 删除规划文件
          jtFs.delete(submitJobDir, true);

      }
    }

至此整理流程代码看完~ 详细的可以多看下源码

本文参与 腾讯云自媒体分享计划,分享自作者个人站点/博客。
原始发表:2019年04月03日,如有侵权请联系 cloudcommunity@tencent.com 删除

本文分享自 作者个人站点/博客 前往查看

如有侵权,请联系 cloudcommunity@tencent.com 删除。

本文参与 腾讯云自媒体分享计划  ,欢迎热爱写作的你一起参与!

评论
登录后参与评论
0 条评论
热度
最新
推荐阅读
目录
  • 客户端源码分析
    • 启动的客户端代码
      • 1.Configuration 对象
        • 2.Job对象的获取
          • 3.waitForCompletion
            • 3.1waitForCompletion
            • 3.2submit
            • 3.3 submitJobInternal
            • 3.4writeSplits
            • 3.5writeNewSplits
            • 3.6 getSplits
            • 3.7computeSplitSize
            • 3.8 submitJobInternal
        相关产品与服务
        云 HDFS
        云 HDFS(Cloud HDFS,CHDFS)为您提供标准 HDFS 访问协议,您无需更改现有代码,即可使用高可用、高可靠、多维度安全、分层命名空间的分布式文件系统。 只需几分钟,您就可以在云端创建和挂载 CHDFS,来实现您大数据存储需求。随着业务需求的变化,您可以实时扩展或缩减存储资源,CHDFS 存储空间无上限,满足您海量大数据存储与分析业务需求。此外,通过 CHDFS,您可以实现计算与存储分离,极大发挥计算资源灵活性,同时实现存储数据永久保存,降低您大数据分析资源成本。
        领券
        问题归档专栏文章快讯文章归档关键词归档开发者手册归档开发者手册 Section 归档