增加作业提交的中文注释。

hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-core/src/main/java/org/apache/hadoop/mapreduce/JobResourceUploader.java

@@ -202,10 +202,13 @@ private void uploadResourcesInternal(Job job, Path submitJobDir)
     Map<String, Boolean> archiveSCUploadPolicies =
         new LinkedHashMap<String, Boolean>();
 
+    // 将配置文件上传到staging目录，并且将上传好的路径添加到配置mapreduce.job.cache.files中
     uploadFiles(job, files, submitJobDir, mapredSysPerms, replication,
         fileSCUploadPolicies, statCache);
+    // 将jar文件上传到staging目录，并且将上传好的路径添加到配置mapreduce.job.cache.files中
     uploadLibJars(job, libjars, submitJobDir, mapredSysPerms, replication,
         fileSCUploadPolicies, statCache);
+    // 将归档保信息上传到staging目录，将上传好的路径放到配置mapreduce.job.cache.archives中
     uploadArchives(job, archives, submitJobDir, mapredSysPerms, replication,
         archiveSCUploadPolicies, statCache);
     uploadJobJar(job, jobJar, submitJobDir, replication, statCache);

hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-core/src/main/java/org/apache/hadoop/mapreduce/JobSubmitter.java

@@ -143,8 +143,9 @@ JobStatus submitJobInternal(Job job, Cluster cluster)
     checkSpecs(job);
 
     Configuration conf = job.getConfiguration();
+    // 分布式缓存优化
     addMRFrameworkToDistributedCache(conf);
-
+    // 获取Staging目录
     Path jobStagingArea = JobSubmissionFiles.getStagingDir(cluster, conf);
     //configure the command line options correctly on the submitting dfs
     InetAddress ip = InetAddress.getLocalHost();
@@ -154,6 +155,7 @@ JobStatus submitJobInternal(Job job, Cluster cluster)
       conf.set(MRJobConfig.JOB_SUBMITHOST,submitHostName);
       conf.set(MRJobConfig.JOB_SUBMITHOSTADDR,submitHostAddress);
     }
+    // 从yarn上面获取Yarn ApplicationId
     JobID jobId = submitClient.getNewJobID();
     job.setJobID(jobId);
     Path submitJobDir = new Path(jobStagingArea, jobId.toString());
@@ -167,6 +169,7 @@ JobStatus submitJobInternal(Job job, Cluster cluster)
       LOG.debug("Configuring job " + jobId + " with " + submitJobDir 
           + " as the submit dir");
       // get delegation token for the dir
+      // 获取访问hdfs的token
       TokenCache.obtainTokensForNamenodes(job.getCredentials(),
           new Path[] { submitJobDir }, conf);
       
@@ -190,9 +193,10 @@ JobStatus submitJobInternal(Job job, Cluster cluster)
         LOG.warn("Max job attempts set to 1 since encrypted intermediate" +
                 "data spill is enabled");
       }
-
+      // 将需要上传的文件拷贝到submitJobDir下面，将上传的结果添加到指定的配置中。
       copyAndConfigureFiles(job, submitJobDir);
 
+      // 获取job.xml的具体路径
       Path submitJobFile = JobSubmissionFiles.getJobConfPath(submitJobDir);
       
       // Create the splits for the job
@@ -248,6 +252,7 @@ JobStatus submitJobInternal(Job job, Cluster cluster)
       // Now, actually submit the job (using the submit name)
       //
       printTokens(jobId, job.getCredentials());
+      // 真正提交作业的流程
       status = submitClient.submitJob(
           jobId, submitJobDir.toString(), job.getCredentials());
       if (status != null) {

hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-jobclient/src/main/java/org/apache/hadoop/mapred/YARNRunner.java

@@ -327,6 +327,7 @@ public JobStatus submitJob(JobID jobId, String jobSubmitDir, Credentials ts)
 
     // Submit to ResourceManager
     try {
+      // 提交作业
       ApplicationId applicationId =
           resMgrDelegate.submitApplication(appContext);
 
@@ -580,6 +581,7 @@ public ApplicationSubmissionContext createApplicationSubmissionContext(
         ByteBuffer.wrap(dob.getData(), 0, dob.getLength());
 
     // Setup ContainerLaunchContext for AM container
+    // 构造AM命令。
     List<String> vargs = setupAMCommand(jobConf);
     ContainerLaunchContext amContainer = setupContainerLaunchContextForAM(
         jobConf, localResources, securityTokens, vargs);

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-client/src/main/java/org/apache/hadoop/yarn/client/api/impl/YarnClientImpl.java

@@ -315,6 +315,7 @@ public YarnClientApplication createApplication()
     }
 
     //TODO: YARN-1763:Handle RM failovers during the submitApplication call.
+    // 提交作业。
     rmClient.submitApplication(request);
 
     int pollCount = 0;
@@ -328,6 +329,7 @@ public YarnClientApplication createApplication()
                                   YarnApplicationState.KILLED);		
     while (true) {
       try {
+        // 等待作业提交的结果。
         ApplicationReport appReport = getApplicationReport(applicationId);
         YarnApplicationState state = appReport.getYarnApplicationState();
         if (!waitingStates.contains(state)) {
@@ -338,7 +340,7 @@ public YarnClientApplication createApplication()
           LOG.info("Submitted application " + applicationId);
           break;
         }
-
+        // 作业提交超时。
         long elapsedMillis = System.currentTimeMillis() - startTime;
         if (enforceAsyncAPITimeout() &&
             elapsedMillis >= asyncApiPollTimeoutMillis) {

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-resourcemanager/src/main/java/org/apache/hadoop/yarn/server/resourcemanager/ClientRMService.java

@@ -683,7 +683,7 @@ public SubmitApplicationResponse submitApplication(
     }
 
     try {
-      // call RMAppManager to submit application directly
+      // call RMAppManager to submit application directly  调用RMAppManager提交作业。
       rmAppManager.submitApplication(submissionContext,
           System.currentTimeMillis(), userUgi);